Difference between revisions of "Student projects"
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| − | + | The new thesis topic (for students starting in '''November 2024''') are listed below.<br> | |
| − | + | You should choose a topic by '''Monday, 28th of October, 12:00 noon''': submit three preferences using [https://forms.gle/ngYNJKNwcsMP3aE7A this form]. | |
| − | + | ||
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| − | ''' | + | |
== Information about MSc Thesis process == | == Information about MSc Thesis process == | ||
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[https://hh.se/student-web/content-a-z/thesis-information-for-students-at-school-of-information-technology.html MSc thesis project information] (the LaTeX template can be found here) and [https://hh.se/student-web/content-a-z/thesis-templates.html information about accessibility and the official front cover you should use]<br> | [https://hh.se/student-web/content-a-z/thesis-information-for-students-at-school-of-information-technology.html MSc thesis project information] (the LaTeX template can be found here) and [https://hh.se/student-web/content-a-z/thesis-templates.html information about accessibility and the official front cover you should use]<br> | ||
| − | MSc thesis Introductory lecture: [https://bidaf.hh.se/public/ | + | MSc thesis Introductory lecture: [https://bidaf.hh.se/public/2024.09.30-MSc-project-intro.pdf slides from 2024.09.30] and [https://bidaf.hh.se/public/2020.10.15-MSc-project-intro.mp4 video recording] (from a few years back, but mostly still applicable) |
[https://bidaf.hh.se/public/DT7001-course-description-2019.pdf MSc thesis Course Description] | [https://bidaf.hh.se/public/DT7001-course-description-2019.pdf MSc thesis Course Description] | ||
| Line 19: | Line 15: | ||
[https://www.hh.se/sitevision/proxy/student-web/content-a-z/course-syllabus.html/svid12_16be565916914b791c7d0bd8/752680950/se_proxy/utb_kursplan.asp?kurskod=DT7001&revisionsnr=20&format=pdf&lang=EN DT7001 course syllabus] and [https://www.hh.se/sitevision/proxy/student/innehall-a-o/kursplan.html/svid12_464ca102168ed1f8d3b1293f/752680950/se_proxy/utb_kursplan.asp?kurskod=DT7002&revisionsnr=4%2C1&format=pdf DT7002 course syllabus] | [https://www.hh.se/sitevision/proxy/student-web/content-a-z/course-syllabus.html/svid12_16be565916914b791c7d0bd8/752680950/se_proxy/utb_kursplan.asp?kurskod=DT7001&revisionsnr=20&format=pdf&lang=EN DT7001 course syllabus] and [https://www.hh.se/sitevision/proxy/student/innehall-a-o/kursplan.html/svid12_464ca102168ed1f8d3b1293f/752680950/se_proxy/utb_kursplan.asp?kurskod=DT7002&revisionsnr=4%2C1&format=pdf DT7002 course syllabus] | ||
| − | Plagiarism course: [https://academy.sitehost.iu.edu/index.html https://academy.sitehost.iu.edu/index.html] | + | Plagiarism course: [https://academy.sitehost.iu.edu/index.html https://academy.sitehost.iu.edu/index.html]<br> |
| + | Another course, from Umeå University, which includes genAI (in Swedish, but with English subtitles available): [https://oer.ub.umu.se/en/plagiarism/#/ https://oer.ub.umu.se/en/plagiarism/#/] | ||
[https://bidaf.hh.se/public/CivilingenjorPresentation2023.pdf Civilingenjör Presentation 2023] Specialisations Artificial Intelligence (TACDA) and Robotics and autonomous systems (TACIS) | [https://bidaf.hh.se/public/CivilingenjorPresentation2023.pdf Civilingenjör Presentation 2023] Specialisations Artificial Intelligence (TACDA) and Robotics and autonomous systems (TACIS) | ||
| Line 49: | Line 46: | ||
* Social aspects of the work are rarely discussed | * Social aspects of the work are rarely discussed | ||
| − | == Current Proposals of Msc and Bsc Project (as of Autumn | + | == Current Proposals of Msc and Bsc Project (as of Autumn 2024) == |
| − | {{#ask: [[Category:StudentProject]] [[StudentProjectStatus::Open]] [[Modification date::>1 January | + | {{#ask: [[Category:StudentProject]] [[StudentProjectStatus::Open]] [[Modification date::>1 January 2024]] |
| ?Supervisors | | ?Supervisors | ||
| ?OneLineSummary | | ?OneLineSummary | ||
| Line 75: | Line 72: | ||
Those project proposals may still be valid, but contact supervisors before assuming so. | Those project proposals may still be valid, but contact supervisors before assuming so. | ||
| − | {{#ask: [[Category:StudentProject]] [[StudentProjectStatus::Open]] [[Modification date::≤1 January | + | {{#ask: [[Category:StudentProject]] [[StudentProjectStatus::Open]] [[Modification date::≤1 January 2024]] | limit=100 |
| ?Supervisors | | ?Supervisors | ||
| ?OneLineSummary | | ?OneLineSummary | ||
| Line 332: | Line 329: | ||
<span style="color:#cc4444"> | <span style="color:#cc4444"> | ||
| + | For those who didn't make it for the report submission last week, the next deadline for sending in the halftime report is Sunday, 7 April at 23:59 -- using [https://forms.gle/aiFqUW5AxcoD3RrE9 this form].<br> | ||
| + | <br> | ||
| + | The first batch of the halftime presentations will take place on 25-26 March (detailed schedule is [https://docs.google.com/spreadsheets/d/1K0TZNllTSeyWr7mhvwscSf-2IXRSvCBnbBU8mJPQf78/edit#gid=2059471719 here]). Please note that attending the halftime presentations (at least the majority of them) is mandatory -- and I '''will be''' taking attendance lists! | ||
| + | <br> | ||
| + | </span> | ||
| + | |||
| + | <span style="color:#cc4444"> | ||
| + | The second batch of the halftime presentations will take place on Thursday, 18 April (detailed schedule is [https://docs.google.com/spreadsheets/d/1K0TZNllTSeyWr7mhvwscSf-2IXRSvCBnbBU8mJPQf78/edit#gid=2059471719 here]). Please note that attending the halftime presentations (at least the majority of them) is mandatory -- and I '''will be''' taking attendance lists!<br> | ||
| + | |||
| + | '''Half-time presentations''' should be 20 minutes long (plus ~10 minutes for questions) and must cover the goals/objectives, expected contribution/novelty, results achieved so far, and a refined plan on how to proceed. | ||
| + | </span> | ||
| + | |||
| + | <span style="color:#cc4444"> | ||
| + | The deadline for final MSc reports (as always, supervisor-approved) is Friday, '''24 May 2024''', at 23:59. Use [https://forms.gle/yAqFkiiBBTnBf6Dw8 this Google form] to send your report to examiners. | ||
| + | |||
| + | Make sure to have at least '''two iterations''' of feedback on the report, so you should send the initial draft to your supervisors '''more or less right now'''.<br> | ||
| + | Remember that you also need to email the final report to the '''opponent'''. The opponent is decided by your supervisors, and it is generally one of the teachers/researchers here at ITE. | ||
| + | |||
| + | The final presentations will be in '''weeks 22 and 23'''. I'll make a schedule when I receive all your reports, but the time slots you can find already now in the same Google Sheet document as all the previous schedules. If you have any constraints, please let me know in the comments when submitting your report, and I'll do my best to accommodate them. | ||
| + | |||
| + | Final presentations should be '''15 minutes''' long and must cover the goals/objectives, final contribution/novelty, the results, and conclusions from your work. It will be followed by 25-30 minutes of questions/discussion with the opponent (selected by the supervisor) and the examiners. Be advised that 15 minutes is very short, so you should carefully select what do you talk about, focusing on the most important aspects. | ||
| + | |||
| + | If you don't make it this time, the next opportunity will be in late August/early September. | ||
| + | </span> | ||
| + | |||
| + | <span style="color:#cc4444"> | ||
| + | The second deadline for final MSc reports (as always, supervisor-approved) is Sunday, '''15 September 2024''', at 23:59. Use [https://forms.gle/yAqFkiiBBTnBf6Dw8 this Google form] to send your report to examiners. If that deadline is problematic for you, discuss it with your supervisors and contact Slawomir. | ||
| + | |||
| + | If you don't make it this time, the next (and final) opportunity will be in December. | ||
</span> | </span> | ||
Latest revision as of 15:59, 20 October 2024
The new thesis topic (for students starting in November 2024) are listed below.
You should choose a topic by Monday, 28th of October, 12:00 noon: submit three preferences using this form.
Contents
- 1 Information about MSc Thesis process
- 2 Useful resources for your MSc Thesis process
- 3 Current Proposals of Msc and Bsc Project (as of Autumn 2024)
- 4 Draft Proposals of Msc and Bsc Project (do not pick this unless you have checked with the supervisor!)
- 5 Older Proposals of Msc and Bsc Project
- 6 Ongoing Projects
- 7 Completed Msc and Bsc Project
- 8 Internal Drafts
Information about MSc Thesis process
This page contains some information about the MSc thesis project (courses DT7001 and DT7002 and ET7002).
MSc thesis project information (the LaTeX template can be found here) and information about accessibility and the official front cover you should use
MSc thesis Introductory lecture: slides from 2024.09.30 and video recording (from a few years back, but mostly still applicable)
DT7001 course syllabus and DT7002 course syllabus
Plagiarism course: https://academy.sitehost.iu.edu/index.html
Another course, from Umeå University, which includes genAI (in Swedish, but with English subtitles available): https://oer.ub.umu.se/en/plagiarism/#/
Civilingenjör Presentation 2023 Specialisations Artificial Intelligence (TACDA) and Robotics and autonomous systems (TACIS)
Useful resources for your MSc Thesis process
A YouTube course from Lund University on academic writing (in English and in Swedish)
Teaching Technical Writing Using the Engineering Method course from Tufts University
A checklist based on common issues:
- The link to contemporary development within the area is often weak; theses rarely discuss international research sufficiently in-depth (use the references poorly)
- Clear research questions are often missing (having a clear research question that is answered in the report usually results in a much clearer evaluation and conclusions.)
- The text must argue for the research questions, hypothesis, methods and results; often, there is no argument to support the choice.
- Citations should not be used as a word in a sentence, e.g., "as [1] says ..."
- Make sure your figure/table captions are informative; all figures must be references in the text
- The abstract should be clear, specifying exactly what is to be investigated and why
- Results should be put in context to the previous works that they identified in the report
- Social aspects of the work are rarely discussed
Current Proposals of Msc and Bsc Project (as of Autumn 2024)
| Supervisors | OneLineSummary | |
|---|---|---|
| AI-driven Automotive Service Market Logistics | Sławomir Nowaczyk TBD |
This project, in collaboration with Volvo Logistics, focuses on using state-of-the-art methods based on meta-learning to improve demand forecasting, inventory management and spare parts availability at Volvo dealers and warehouses. |
| Adapt LoCoMotif to forklift data | Kunru Chen ... |
LoCoMotif is a novel TSMD method able to discover motifs that have different lengths (variable-length motifs), exhibit slight temporal differences (time-warped motifs), and span multiple dimensions (multivariate motifs) |
| Adaptive Obfuscation Techniques for Privacy- Preserving Machine Learning in IoT Edge De- vices | Mahdi Fazeli | This master thesis project focuses on developing an adaptive obfuscation frame- work for protecting multi-modal data in resource-constrained IoT environments. |
| Anomaly Detection for Time Series using Diffusion Approaches | Sławomir Nowaczyk & TBD | Development of Anomaly Detection techniques based on diffusion models (instead of autoencoders) for time series data |
| Concept Re-identification to Explain Online Continual Learning | Sepideh Pashami Nuwan Gunasekara |
This project aims to apply techniques from recurrent concept drifts to explain the predictions of Online Continual Learning methods. |
| Deep Decision Forest | Sławomir Nowaczyk | Designing a deep model that uses decision trees instead of artificial neurons |
| Dynamic Churning-Based Logic Locking for Enhanced Hardware Security | Mahdi Fazeli | This project aims to explore and implement advanced logic locking techniques to improve the security of integrated circuits (ICs) against modern attacks. |
| Enhancing the Accuracy of CSI-Based Positioning in Massive MIMO Systems | Hazem Ali Ali Nada |
CSI-Based Positioning in Massive MIMO Systems |
| Evaluating the Digital Tools for Promoting Sustainable Food Consumption | Azadeh Sarkheyli | To identify the key features and functionalities of sustainable food apps in Sweden |
| Evaluating the Effects of Social Media on Educational Sustainability in Sweden | Azadeh Sarkheyli | The research analyzes sentiment in social media data related to educational sustainability practices and outcomes in Sweden. |
| Evolving Kolmogorov-Arnold Networks | Mohammed Ghaith Altarabichi | This project aims to enhance the architecture of Kolmogorov-Arnold Networks (KANs) by optimizing key components such as loss functions, activation functions, initialization methods, and learning processes to improve their performance and interpretability. |
| Explainable Decision Forest | Sławomir Nowaczyk Hamid Sarmadi Sepideh Pashami |
Designing an explainable decision forest classifier for fault detection |
| Fault detection using acoustic signals through anomaly detection | Elena Haller Peyman Mashhadi |
Fault detection using acoustic signals through anomaly detection |
| Foundation Models for Time Series Analysis | Zahra Taghiyarrenani Yuantao Fan Ali amirahmadi |
Explore the use of large pre-trained time-series foundation models (TSFM) and design fine-tuning strategies on tasks of interest |
| Graph Neural Networks for Multivariate Time Series Data Analysis | Prayag Tiwari Guojun Liang |
Our project aims to analyze multivariate time series through the innovative application of graph neural networks. |
| Hydro Power Station | TBD (contact Slawomir Nowaczyk if interested) | Collaboration with Ålberga Bruk 1919 |
| Investigating depression signs among older adults using Swedish National Registry Data | Mahmoud Rahat | Investigating depression signs among older adults using Swedish National Registry Data |
| Joint Analysis of Multimodal data on climate change for the educational purpose | Sławomir Nowaczyk Zeinab Shahbazi Carlos Silla |
Exploring climate change data using machine learning and deep learning |
| Knowledge graphs in healthcare | Grzegorz J. Nalepa | Investigae the use of KG in healthcare applications |
| Machine Learning-based optimization of physical activity | Cristofer Englund Kevin Hernandez Diaz |
The project should be able to detect the difference between the current exercise and a reference version of the exercise. |
| Mapping SFO mitigation/Linearization algorithms, trade-off between memory and computation on GPU | Hazem Ali (HH) Håkan Johansson (LiU) |
investigating the parallelisation and mapping of Sampling Frequency Offset algorithms |
| Multi-modal Weather type Classifier | Eren Erdal Aksoy | Camera, LiDAR, and Radar based weather type classification using deep neural networks on the K-RADAR dataset |
| Multitask Learning in Autonomous Driving | Eren Erdal Aksoy | The student should annotate 3D point cloud data for semantic segmentation and object detection. A new deep learning model needs to be implemented to learn both tasks. |
| Object Tracking and Anticipation | Eren Erdal Aksoy | The thesis presents an experimental study of different object-tracking and trajectory anticipation algorithms in the context of autonomous driving. |
| Predicting Energy Consumption for Heavy-Duty Vehicles via Time Series Embeddings (in collaboration with Volvo) | Yuantao Fan & TBD | Develop deep learning based methods for time series forecasting; explore self-supervised learning methods for multi-variate time series embeddings |
| Project opportunities at ElectronicArts | TBD | Each year there are several project opportunities at Electronic Arts |
| Project opportunities at HMS | TBD | Each year there are several project opportunities at HMS (a company with motto of "We create products that enable industrial equipment to communicate and share information") |
| Project opportunities at RISE | TBD | Each year there are several project opportunities at RISE (Research Institutes of Sweden) |
| Project opportunities at Toyota | TBD | Each year there are several project opportunities at Toyota |
| Project opportunities at zenseact | TBD | Each year there are several project opportunities at zenseact |
| Project opportunity at PERIsign | Abdallah Alabdallah & TBD | Peritonitis (inflammation of the peritoneum) detection via EMG-signals. |
| Project with chargefinder.com | TBD Please contact Sławomir Nowaczyk if interested |
Use data to create a machine learning model that can predict estimated availability of a specific charger based on day, time and maybe other external factors (holiday, weather) |
| Project(s) at Volvo Cars Corporation | TBD | Thesis topics at Volvo Car Corporation |
| Project(s) at Volvo Group | TBD | Thesis topics at Volvo Group |
| Protein Language Models for drug discovery | Prayag Tiwari Ali Amirahmadi |
Leveraging the sequence-based transformer protein language model for improving potential drug targets identification |
| Reliability Analysis and Assessment of Multi- Core System-on-Chip through Transaction Pro- filing and Machine Learning | Mahdi Fazeli | |
| Resilience of ML Hardware Accelerators Against Accuracy Degrading Trojans | Mahdi Fazeli | The goal of this project is to assess the resilience of machine learning (ML) hardware accelerators, with a specific focus on Convolutional Neural Network (CNN) accelerators, when subjected to Trojan attacks aimed at degrading their accuracy. |
| SCANIA Project: Graph neural networks for anomaly detection | Sepideh Pashami | Graph neural networks for anomaly detection |
| Secure IP Core Design Through LLM-Driven Logic Locking | Mahdi Fazeli | |
| Securing Internet of Autonomous Vehicles with Light-weight Authentication | Hazem Ali Mohamed Eldefrawy |
investigating the HW/SW design of light-weight authentication for IoAV |
| The CatFish project | To be decided (contact Slawomir Nowaczyk for more details) | The project within Innovation Lab called CatFish has the aim of collecting data from water bodies through a system of drones |
| The healthcare data mining with advance AI technology | Guojun Liang Prayag |
The cardiovascular health care project |
| Thesis in connection with KEEPER project | Sławomir Nowaczyk TBD |
KEEPER – knowledge creation for efficient and predictable industrial operations |
| Time series anomaly detection for Heavy-duty vehicles (in collaboration with Volvo) | Yuantao & TBD | Detecting anomalies in multivariate time series data via learned representations |
| Trajectory prediction algorithms for intention sharing in Micromobility | Elena Haller Amira Soliman Oscar Amador Molina |
Self-prediction of trajectories by Vulnerable Road Users to share their intentions with vehicles. |
| Utilization of Foundation Models for Federated Learning | Zahra Taghiyarrenani Yuantao Fan Ali amirahmadi |
This thesis aims to leverage Foundation Models and develop new aggregation paradigms to overcome challenges in Federated Learning. |
| XAI for yoga posture recognition | Cristofer Englund Kevin Hernandez Diaz |
To analyze the classification of yoga postures and the potential misclassification due to occlusion and perspective of images |
If you've added a project and it didn't show up, wait for cache to update, or press "refresh" button at top of the page! (refreshing the page in the browser is not always enough)
(make sure to give your project a name before clicking the button!)
Draft Proposals of Msc and Bsc Project (do not pick this unless you have checked with the supervisor!)
| Supervisors | OneLineSummary | Status | |
|---|---|---|---|
| Browser Extensions Updates | Pablo Picazo | Clustering and analyzing browser extensions by update frequency | Draft |
| Explainable AI for predictive maintenance in collaboration with Volvo | Mahmoud Rahat Peyman Mashhadi |
Developing explainable models for predicting components failures of Volvo trucks | Draft |
| High Precision Power Use Measurement Device for Raspberry PI | Wojciech Mostowski Per Sandrup Joel Nyholm |
Design and build a device from measuring power draw of a Raspberry PI with high precision to power profile software. | Draft |
| Human Value Detection | Pablo Picazo | Given a textual argument and a human value category, classify whether or not the argument draws on that category. | Draft |
| Image Retrieval for Arguments | Pablo Picazo | Given a controversial topic, the task is to retrieve images (from web pages) for each stance (pro/con) that show support for that stance. | Draft |
| No Signal Left to Chance | Pablo Picazo | Identify download patterns as a useful signal for analyzing browser extensions. | Draft |
| Optimizing Energy Consumption in Maritime Transportation with Machine Learning Methods (in collaboration with Cetasol) | Sławomir Nowaczyk Yuantao Fan Hadi Fanaee Or Mohamed Abuella |
Develop machine learning methods for forecasting fuel consumption, path, and motion planning, with historical data from furries operation. | Draft |
| Project with HMS | Peyman Mashhadi Yuantao Fan |
Few-shot Learning for Quality Inspection | Draft |
| Representation Learning for Fault Detection and Prognosis | Yuantao Fan | Characterise the observed system using representation learning techniques, for fault detection and remaining useful life prediction | Draft |
Older Proposals of Msc and Bsc Project
Those project proposals may still be valid, but contact supervisors before assuming so.
| Supervisors | OneLineSummary | Modification dateThis property is a special property in this wiki. | |
|---|---|---|---|
| Leveraging LLMs for Clinical Note Annotation and Uncertainty Estimation | Awais Ashfaq Prayag Tiwari |
The student will investigate the potential of LLMs to simplify clinical note annotation along with uncertainty estimation, contributing to improved healthcare data management. | 27 October 2023 07:33:38 |
| Machine Learning for Segmentation of Lensed Galaxies: Distinguishing Source Galaxies from Gravitational Lenses | Tiago Cortinhal Idriss Gouigah Eren Erdal Aksoy Margherita Grespan Hareesh Thuruthipilly |
Machine Learning for Segmentation of Lensed Galaxies: Distinguishing Source Galaxies from Gravitational Lenses | 25 October 2023 11:18:41 |
| Multi-modal risk prediction models on osteoporotic fracture, myocaridal infarction and stroke | Kobra Etminani (Farzaneh) TBD Peder Wiklund (from Region Halland) Markus Lingman (from Region Halland) |
develop and evaluate how well a multimodal model derived from the regional healthcare information platform, with or without the CT-derived measures, can predict the risk of subsequent osteoporotic fracture, myocardial infarction and stroke | 16 October 2023 07:31:42 |
| Federated learning in automotive industry | Zahra Taghiyarrenani Sławomir Nowaczyk Sepideh Pashami |
Federated learning in automotive industry | 14 October 2023 09:40:25 |
| Generative Approach for Multivariate Signals | Kunru Chen Thorsteinn Rögnvaldsson Abdallah Alabdallah |
The topic focuses on generative models (VAE) for CAN-bus data and investigating the representation learning capabilities of such techniques | 12 October 2023 15:27:46 |
| Clock Glitch Attacks on Embedded IoT Devices: An FPGA-Based Exploration | Mahdi Fazeli | this thesis aims to provide a comprehensive understanding of the vulnerabilities and potential countermeasures associated with clock glitch attacks on FPGA based IoT devices | 10 October 2023 18:15:07 |
| Be The Change: Video Analysis for Environmental Sustainability | Sławomir Nowaczyk Zeinab Shahbazi |
Analysis of online climate change video contents and identification of video features rendering a video ‘effective’ using machine learning techniques | 10 October 2023 13:43:43 |
| Multivariate Time Series Analysis with Irregularly Sampled Data | Awais Ashfaq Prayag Tiwari |
The student will devise methods for handling irregularly sampled multivariate time series data, addressing missing data and modeling temporal relationships for applications in healthcare | 9 October 2023 08:47:30 |
| SimpleText: Automatic Simplification of Scientific Texts | Pablo Picazo-Sanchez | Automatic Simplification of Scientific Texts | 9 October 2023 07:48:17 |
| Ideology and Power Identification in Parliamentary Debates | Pablo Picazo-Sanchez | Ideology and Power Identification in Parliamentary Debates | 9 October 2023 07:47:55 |
| EXIST: sEXism Identification in Social neTworks | Pablo Picazo-Sanchez | sEXism Identification in Social neTworks | 9 October 2023 07:47:32 |
| AI for sustainability management and reporting | Eric Järpe Cristofer Englund |
Connect AI models to sustainability / ESG (social, environmental, and governance) to enable automated processing related to EU sustainability regulations. | 6 October 2023 11:12:32 |
| Analyzing Privacy Policies (NLP) -- Malware Analysis | Pablo Picazo-Sanchez | Analyzing Privacy Policies (NLP) -- Malware Analysis | 6 October 2023 07:49:12 |
| Securing Multi-Processor System-on-Chips: Assessing Vulnerabilities to Hardware Trojans Through Thermal Profiles | Mahdi Fazeli | This master's thesis project is dedicated to conducting a comprehensive security assessment of modern multi-processor System-on-Chips (MPSoCs) equipped with multiple thermal sensors. | 6 October 2023 07:21:22 |
| V2X Intention Sharing for E-Bikes and E-Scooters | Oscar Amador Molina Elena Haller |
Design and implementation of a protocol that enables Vulnerable Road Users to share their intentions with vehicles. | 3 October 2023 11:46:01 |
| Uncertainty quantification for data driven clinical decision making | Awais Ashfaq Sławomir Nowaczyk |
The student will build upon the field of evidential deep learning to identify and understand when the model says 'I don't know' | 29 September 2023 08:36:57 |
| Improving Time-series Generative Adversarial Networks (GANs) for Generating Electronic Health Records (EHRs) | Amira Soliman Atiye Sadat Hashemi |
Synthetic Electronic Health Records | 27 September 2023 09:34:30 |
| On the explainability of Graph Neural Networks: an application in credit scoring | Atiye Sadat Hashemi Peyman Mashhadi |
On the explainability of Graph Neural Networks: an application in credit scoring | 26 September 2023 12:01:04 |
| Towards robustness of post hoc Explainable AI methods | Parisa Jamshidi Peyman Mashhadi Jens Lundström |
Towards robustness of post hoc Explainable AI methods | 26 September 2023 07:03:28 |
| Secure Hardware Accelerators for Machine Learning: Design, Evaluation, and Mitigation of Vulnerabilities | Mahdi Fazeli and Ahmad Patooghy (North Carolina University US) |
This master's project focuses on investigating the security of hardware accelerators designed for machine learning | 26 September 2023 07:01:40 |
| Body posture alignment feedback using xAI | Cristofer Englund Fernando Alonso-Fernandez |
Extracting the body alignment in different postures and giving feedback to reduce harm during physical exercise | 22 September 2023 13:25:34 |
| The effect of a mixed-capability vehicular fleet on Vulnerable Road User safety | Elena Haller Oscar Amador Molina |
Investigation of the effect of different levels of connection, cooperation, and automation (e.g., local awareness, collective perception, statistics) on road safety and traffic efficiency for future mobility scenarios including pedestrians and cyclists. | 20 September 2023 06:59:26 |
| Network-assisted positioning in confined spaces using 802.11 Access Layer information | Oscar Amador Molina Elena Haller |
Proof of Concept of a Position-and-Time entity based on 802.11 to enable embedded beaconing systems (e.g., a “connected reflective vest”) for workers in confined spaces where satellite-based positioning is not possible. | 19 September 2023 11:49:33 |
| Analysing comments (NLP) for Malware Analysis | Pablo Picazo-Sanchez | Analysing the comments of users in the WebStore to look for malware patterns | 30 August 2023 07:57:02 |
| Evaluation of JAX in AI/ML software engineering | Veronica Gaspes Sławomir Nowaczyk |
Analysis of the benefits of JAX (and/or similar solutions) in terms of performance, development time, module reusability, etc. | 30 August 2023 07:09:55 |
| Transfer Learning for Network Security | Sławomir Nowaczyk Zahra Taghiyarrenani |
Study of Transfer Learning techniques in Network Security applications- Network Traffic Classification and Intrusion Detection | 30 August 2023 07:02:37 |
| Automatic Idea Detection from social media for Controlling and Preventing Healthcare-Associated Infections (with funding opportunity) | Fabio Gama Mahmoud Rahat Peyman Mashhadi |
This project aims to use advanced NLP tools to automatically detect interesting ideas by processing text available in the medical forums to address the Healthcare-associated infections problem in the hospitals | 30 October 2022 10:45:00 |
| Automated Inference regarding Goals in Elite Football Data | Andreas Summrina Kunru Martin |
Automated Inference regarding Goals in Elite Football Data | 26 October 2022 07:25:57 |
| Digital Twin - AFRY | TBD (Wojciech Mostowski) | Digital twin for consulting firm | 26 October 2022 07:03:05 |
| Ultra-wideBand Antenna Array for Vehicular Communication | Amjad Iqbal | In this project, an ultra-wideband millimeter-wave antenna array will be designed to ensure high gain and channel capacity. | 25 October 2022 17:55:45 |
| Optimization of a 5G algorithm by parallelization | Hazem Ali | Optimization of a 5G algorithm by parallelization | 25 October 2022 13:28:43 |
| Action Library for Robot Execution | Eren Erdal Aksoy | Action Library for Robot Execution | 24 October 2022 11:34:54 |
| Multi-Sensor Fusion for Semantic Scene Understanding | Eren Erdal Aksoy | Multi-Sensor Fusion for Semantic Scene Understanding | 24 October 2022 11:32:09 |
| Developing a device for rapid water quality assessment | Ying Fu | develop a device with which a water sample may be analysed rapidly on the spot | 24 October 2022 08:15:04 |
| IoT Forensics | Mohamed Eldefrawy and Hazem Ali | To achieve a systematic approach for data extraction (i.e., imaging), forensically sound, from the hardware level | 19 October 2022 10:04:27 |
| Real-time bladder scanner | Pererik Andreasson | Real-time bladder scanner | 18 October 2022 06:30:21 |
| Deep Active Learning for LiDAR Point Cloud Segmentation | Abu Mohammed Raisuddin Eren Erdal Aksoy |
Active Learning to improve data efficiency for LiDAR point Cloud Segmentation | 12 October 2022 10:45:07 |
| A Reliable IoT Messaging Protocol Based on MQTT Standard | Mahdi Fazeli | In this project, we will modify the well-known IoT protocol, i.e., MQTT to consider a topic-based reliability strategy between the broker and subscribers. | 11 October 2022 12:27:51 |
| Explainable AI and poverty prediction | Thorsteinn Rögnvaldsson Mattias Ohlsson |
Provide explanations of AI data-driven poverty predictions in sub-saharan africa | 10 October 2022 20:32:24 |
| Graph Neural Networks for cardiovascular disease | Prayag Tiwari | The main goal of this project is to explore GNN for cardiovascular disease | 10 October 2022 20:26:27 |
| Zenseact Scalable Mapping | TBD | Scalable mapping through crowd sourcing | 10 October 2022 19:30:21 |
| Model-Based Testing of Zero-Copy Protocols | Wojciech Mostowski | Challenges in Model-Based Testing of Zero-Copy Protocols | 6 October 2022 12:02:49 |
| Investigation of spread spectrum techniques to reduce the electromagnetic interference in switch mode power supply | Maria De Lauretis Elena Haller |
The goal of the project is to investigate spread-spectrum-based PWM techniques to reduce the EMI in motor drivers caused by the SMPS | 5 October 2022 10:45:01 |
| Timeseries representation learning for EHR | Amira Soliman Stefan Byttner Kobra Etminani Omar Hamed Ali Amirahmadi |
Timeseries representation learning for Electronic Health Records | 5 October 2022 07:49:46 |
| Analysis of industrial time series | Hadi Fanaee | studying the recent advances in time series forecasting and their application in modelling time series of Alfa Laval's industrial machines | 4 October 2022 11:54:39 |
| Reconfigurable Orbital angular momentum (OAM) antenna for High-Speed Wireless Communications | Amjad Iqbal | In this project, a reconfigurable (operating modes will be controlled using p-i-n diodes) OAM antenna will be designed. | 3 October 2022 18:19:32 |
| Generating synthetic time series data in case of data scarcity | Alexander Galozy Peyman Mashhadi |
Generating synthetic time series data in case of data scarcity | 3 October 2022 14:14:46 |
| FLBench: A Comprehensive Experimental Evaluation of Federated Learning Frameworks | Sadi Alawadi Jens Lundström |
Exploring Federated Learning Frameworks | 3 October 2022 09:07:24 |
| Privacy-Preserved Generator for Generating Synthetic EHR data | Atiye Sadat Hashemi Jens Lundström Farzaneh Etminani |
Time-series GAN and generation of synthetic electrical health records | 3 October 2022 09:02:17 |
| Fair representation learning of electronic health records | Ali Amirahmadi Ece Calikus Kobra Etminani |
Fair representation learning of electronic health records | 3 October 2022 09:01:50 |
| Human-in-the-loop Discovery of Interpretable Concepts in Deep Learning Models | Ece Calikus | Interactive discovery of disentangled and interpretable concepts in Deep Learning Models | 3 October 2022 09:00:38 |
| Federated Learning Aggregation Strategies by Weight Exploration | Jens Lundström Amira Soliman Sadi Alawadi |
Investigation of aggregation strategies for federated learning | 3 October 2022 08:42:52 |
| Explainable AI by Training Introspection | Jens Lundström Peyman Mashhadi Amira Soliman Atiye Sadat Hashemi |
Research and development of novel XAI methods based on training process information | 3 October 2022 08:41:40 |
| Quantifying exercise-induced muscle fatigue by machine learning | Jens Lundström | Exploring machine learning methods on an EMG muscle fatigue pipeline | 3 October 2022 08:35:51 |
| Quantum Machine Learning models for predicting disease | Prayag Tiwari | explore quantum models, including hybrid (classical-quantum), and apply them to different disease prediction tasks | 2 October 2022 21:58:24 |
| Graph Neural Networks for Traffic Flow Forecasting | Prayag Tiwari Sławomir Nowaczyk |
The main goal of this project is to explore GNN for traffic flow forecasting | 2 October 2022 21:52:56 |
| Hardware Security Enhancement in Cyber-Physical Systems using Deep Learning-based Anomaly Detection | Mahdi Fazeli | In this project, we intend to employ a deep learning approach to detect anomalies in cyber-physical systems using data flow monitoring. | 1 October 2022 10:25:01 |
| Connected Safety Vest for Roadworkers | Oscar Amador Molina Alexey Vinel |
Development and testing of an embedded system for the protection of Vulnerable Road Users | 30 September 2022 17:46:53 |
| Multiband RF Rectifier for Self-Powered IoT Devices | Amjad Iqbal | In this project, Mutiband RF rectifiers will be designed for self-powered IoT devices | 30 September 2022 16:29:47 |
| Time Series Motif/Discord Discovery Under Context | Hadi Fanaee | How we can find the repeated or odd patterns in a large time series that is under influence of multiple contexts? | 30 September 2022 15:16:26 |
| Conditional GAN for better embedding and generation of medical codes | Stefan Byttner Amira Soliman Kobra Etminani Atiye Sadat Hashemi |
Synthetic data generation of Electronic Health Records with a focus on medical codes | 30 September 2022 14:57:34 |
| Road user behavior prediction | Cristofer Englund Björn Åstrand Fernando Alonso-Fernandez |
Road user behavior recognition and manipulation using deep learning | 23 September 2022 06:20:00 |
| Human ground robot interaction | Cristofer Englund Martin Cooney Fernando Alonso-Fernandez |
External communication from mobile robots to minimize conflicts with pedestrians | 23 September 2022 06:19:10 |
| Meta-learning for Multivariate Signals | Kunru Chen Anna Vettoruzzo Mohamed-Rafik Bouguelia |
Apply meta-learning algorithms to unlabelled time-series data to solve machine activity recognition problems. | 21 September 2022 12:13:19 |
| Fair Conformal Prediction | Ece Calikus | Our goal is to design algorithms using conformal prediction framework that make fair predictions across various groups based on e.g., age, sex, income. | 20 September 2022 13:03:49 |
| Wideband Dielectric Resonator Antenna Array for Autonomous Vehicles | Amjad Iqbal | In this project, a wideband millimeter-wave dielectric resonator antenna will be designed to ensure high gain and channel capacity. | 17 September 2022 19:12:21 |
| Model Heterogeneity in Federated Learning | Amira Soliman Sławomir Nowaczyk |
Group users within a federated learning environment into different learning overlays according to their behavioural similarities | 17 September 2022 16:52:35 |
| Data Heterogeneity in Federated Learning | Amira Soliman Sławomir Nowaczyk |
Addressing the challenges of data imbalance in Federated Learning | 17 September 2022 16:52:30 |
| Data analysis in collaboration with WirelessCar | Mahmoud Rahat Peyman Mashhadi Sławomir Nowaczyk |
Data analysis in collaboration with WirelessCar | 17 September 2022 16:52:21 |
| Deep stacked ensemble | Sławomir Nowaczyk Peyman Mashhadi |
This project aims at training multiple parallel deep networks in such a way to learn different representation of data which will be suitable to frame these networks in stacked ensemble framework. | 17 September 2022 16:52:09 |
| Open and Realistic smart City Activities Simulator (ORCAS) | Sławomir Nowaczyk Richard Bunk |
Create a simulation platform, loosely inspired by gamification, that is in principle capable of capturing the complexity of a complete city. | 17 September 2022 16:51:01 |
| Project with Atos | TBD Please contact Sławomir Nowaczyk if interested |
The project involves the development of software for the TrueDepth technology of the iPhone. | 17 September 2022 16:48:11 |
| Blockchain for polls and elections | To be decided (contact Slawomir Nowaczyk for more details) | Today, there is no blockchain solution that meets the requirements for polls/elections; therefore, we would like to develop our own | 21 August 2022 14:17:04 |
| LiDAR Denoising | Eren Erdal Aksoy | In this project, the candidate is supposed to implement various filtering algorithm to denoise 3D LiDAR point cloud data. | 27 October 2021 10:59:47 |
| Virtual reality to support traffic safety | Cristofer Englund Lei Chen |
The thesis is part of an ongoing project to develop drone-based lighting solutions for improving traffic safety and for encouraging travels to take bicycles. | 19 October 2021 14:28:33 |
| Lighting up the bicycle roads with drones | Cristofer Englund Lei Chen |
Lighting up the bicycle roads with drones | 19 October 2021 14:26:46 |
| Automatic Idea Detection for controlling Healthcare-associated infections | Peyman Mashhadi Mahmoud Rahat Fabio Gama |
This project aims to use advanced NLP tools to automatically detect interesting ideas by processing text available in the medical forums to address the Healthcare-associated infections problem in the hospitals | 19 October 2021 08:57:23 |
| Autonomous flying drone for vehicle classification | Cristofer Englund Fernando Alonso-Fernandez Martin Torstensson |
Building an autonomous flying drone for vehicle classification | 18 October 2021 11:38:05 |
| Modeling patient trajectories using different representation learning techniques | Stefan Byttner Kobra Etminani Amira Soliman |
Modeling Electronic Health Record (EHR) data and predict future events for specific patients | 12 October 2021 08:23:46 |
| Visual Transformers for 3D medical images Classification: use-case neurodegenerative disorders | Stefan Byttner Kobra Etminani Amira Soliman |
Using visual transformers for predicting the diagnosis of multiple neurodegenerative brain disorders | 12 October 2021 08:12:05 |
| Advanced AI based anonymization of traffic video data | Fernando Alonso-Fernandez Yury Tarakanov (Viscando) Felix Rosberg (Berge) |
Advanced AI based anonymization of traffic video data (with Viscando and Berge) | 11 October 2021 12:59:13 |
| Surface normal estimation by Spiral Codes | Josef Bigun | Estimating 3d surface normal from a single image | 11 October 2021 11:30:50 |
| Forecasting Industrial IoT Time Series @AlfaLaval | Hadi Fanaee | Forecasting industrial IoT Time Series | 9 October 2021 23:45:15 |
| Anomaly detection from IoT Time Series @AlfaLaval | Hadi Fanaee | Anomaly detection from IoT Time Series @AlfaLaval | 9 October 2021 23:44:45 |
| Deep neural network optimization for path prediction in vessels! | Reza Khoshkangini Enayat Rajabi |
The purpose of this thesis is analyzing a ferry dataset to identify the most optimal path using deep-net. | 6 October 2021 13:45:59 |
| The effect of contextual information on fuel consumption using Explainable AI! | Reza Khoshkangini Enayat Rajabi |
There are many factors that can minimize pollutions and maximize energy efficiency and fuel consumption in vessels. | 6 October 2021 13:43:51 |
| Predicting electricity generation capacity in solar and wind power plants based on meteorological data using machine learning algorithms | Reza Khoshkangini Ramin Sahba Amin Sahba |
ML algorithms will be used to analyze meteorological data to predict the electricity generation capacity of solar and wind power plants. This project is a collaboration between Halmstad and Sam Houston University (USA)). | 6 October 2021 12:58:35 |
| Deep clustering for vehicle operation type | Reza Khoshkangini Peyman Mashhadi |
In this project, deep clustering will be used on the logged vehicle data (LVD) to find the best representation of vehicles’ operation to explain the behavior of the vehicles over time. | 6 October 2021 06:48:09 |
| Semi-supervised deep learning model to optimally charge and discharge the batteries of electric cars and balance distribution of electrical energy in the power grid | Reza Khoshkangini Amin Sahba Ramin Sahba |
A semi-supervised deep learning model will be developed to optimally charge and discharge the batteries of electric cars while they are connected to the power grid. (In collaboration with Sam Houston State University (USA)). | 6 October 2021 06:44:05 |
| Incorporate behaviour modelling into AGV safety performance stack | Björn Åstrand | Incorporate behaviour modelling into AGV safety performance stack | 5 October 2021 20:35:17 |
| Optimising Energy Consumption for Ferries in Collaboration with Cetasol | Yuantao Fan Peyman Mashhadi |
This project aims at developing data-driven methods to understand ferry operations and optimise enegery consumption | 5 October 2021 20:05:46 |
| Deepfake Detection | Stefan Byttner Jens Lundström Peyman Mashhadi |
Detecting deepfake images and videos using a diversified ensemble of deep models | 5 October 2021 15:53:22 |
| Intrusion detection and prevention for IIoT using Ensemble Deep Network | Reza Khoshkangini Mohamed Eldefrawy |
In this project students will work on network data and try to detect malicious behavior using ensemble deep network. | 5 October 2021 08:02:00 |
| Deep Networks for Semantic Scene Understanding | Eren Erdal Aksoy | The candidate will implement a neural network to detect spatial relations between objects in the scene. For instance, the book is on the table or the spoon is in the cup. | 4 October 2021 09:08:13 |
| Deep Graph Networks for Future Graph Prediction | Eren Erdal Aksoy | In this project, the candidate is supposed to implement a deep graph network that receives a set of graphs as input and returns the predicted next upcoming graph(s). | 4 October 2021 08:57:49 |
| Music style transfer | Peyman Mashhadi Yuantao Fan |
Develop a system that receives a piece of music in one genre and changes/transfers its style into another genre, using machine learning algorithms. | 3 October 2021 15:34:06 |
| Security analysis of IIoT connectivity protocols | Mohamed Eldefrawy Yousra Alkabani |
Potential security vulnerabilities of IIoTs platform connectivity protocols, such as CoAP and MQTT will be studied. | 29 September 2021 20:26:14 |
| Project with Whole AB | Slawomir Nowaczyk / TBD | TBD | 28 September 2021 08:55:26 |
| Building a Knowledge-based AI Framework for Mobility | Enayat Rajabi Sławomir Nowaczyk |
Leveraging new knowledge to improve the productivity of mobility services | 22 September 2021 18:33:42 |
| Effecient implementation of DL models on embedded platforms | Nesma Rezk Yuantao Fan Sławomir Nowaczyk |
In this project, we optimize DL models to run efficiently on resource-bounded embedded platforms. | 20 September 2021 15:47:17 |
| … further results | |||
Ongoing Projects
| ThesisAuthor | OneLineSummary | Supervisors | |
|---|---|---|---|
| Analyzing white blood cells in blood samples using deep learning techniques | To analyze white blood cell content in blood samples using deep learning techniques. | Mattias Ohlsson | |
| Article Identification for Inventory List in a Warehouse Environment | Yang Gao | Article Identification for Inventory List in a Warehouse Environment | Björn Åstrand Saeed Gholami Shahbandi |
| Automatic Generation of Descriptive Features for Predicting Vehicle Faults | Vandan Revanur Ayodeji Olanrewaju Ayibiowu |
Automatic Generation of Descriptive Features for Predicting Vehicle Faults | Mahmoud Rahat Reza Khosh |
| Chess playing humanoid robot by vision | Joseph T. Sachin | Chess playing humanoid robot by vision | Josef Bigun |
| Face and eye categorization and detection | Zhao Cui Albert Hoxha |
To build a new database of face and eye images of different species and to evaluate holistic and local detection algorithms | Fernando Alonso-Fernandez |
| Forklift Trucks Usage Analysis | This project is about applying machine learning methods to have a better understanding for the usage of forklifts trucks in industrial application. | Kunru Chen Alexander Galozy |
|
| Human identification by handwriting of identity text | Identify a hand writer when repeated identity relevant text is available | Josef Bigun Fernando Alonso-Fernandez |
|
| Ice rink resurfacing system for selfdriving vehicles having spiral codes | ice rink resurfacing system for selfdriving vehicles having spiral codes | Josef Bigun | |
| Interactive Anomaly Detection | Anomalies can be relevant or irrelevant to the end-user. The goal of this thesis is to propose a new interactive anomaly detection method to leverage the user-feedback and learn to suggest more relevant anomalies. | Mohamed-Rafik Bouguelia Onur Dikmen |
|
| Modelling Health Recommender System using Hybrid Techniques | The goal of this project is to develop a health recommender system using existing machine learning techniques. | Hassan Mashad Nemati Rebeen Hamad |
|
| OpticalFlowFeaturesForEventDetection | Mohammad Afrooz Mehr Maziar Haghpanah |
Stefan Karlsson | |
| Pallet Rack Identification in Warehouse | Anil Kumar Kothapalli | Development of an identification algorithm for Pallet Rack Cells in a warehouse. Data acquisition is performed by a mobile robot via fisheye cameras and/or 3D sensors. | Björn Åstrand Saeed Gholami Shahbandi |
| Robot Cooking | Chandrashekhar Shankarrao Nasurade Vamsi Krishna Nathani |
Common sense for a robot to cook healthy food | Martin Cooney |
| Sensor fusion and machine learning for drone detection and classification | Sensor fusion and machine learning for drone detection and classification | Cristofer Englund Eren Erdal Aksoy Fernando Alonso-Fernandez |
|
| Smart sensor | Can Yang | Small smart sensors | Martin Cooney Håkan Petterson |
| Social touch for robots | Prateek | something with social robots | Martin Cooney |
| Traffic Estimation From Vehicle Data | Sowmya Tamidala | Estimate traffic density based on logged vehicle data | Sławomir Nowaczyk Iulian Carpatorea |
Completed Msc and Bsc Project
| ThesisAuthor | OneLineSummary | Supervisors | |
|---|---|---|---|
| "TROLL": a regenerating robot | Yinrong Ma | A robot which can detect faults on itself and try to mark or fix them | Martin Cooney Anita Sant'Anna |
| Activity monitoring for AAL | Jianyuan Ma Yinan Qiu |
Tracking of more than one person in a smart environment using fixed sensors and a mobile robot | Anita Sant'Anna |
| Adaptive warning field system | Adaptive warning field system | Björn Åstrand | |
| Analysis of Multi-Lingual Vehicle Service Histories | Iyanuoluwa Akanbi | Automatic translation and similarity evaluation of multi-lingual natural text descriptions of vehicle repair and maintenance operations | Sepideh Pashami Sławomir Nowaczyk |
| Assistance-seeking strategy for a flying robot during a healthcare emergency response | Jérémy Heyne | Assistance-seeking strategy for a flying robot during a healthcare emergency response | Anita Sant'Anna Yuantao Fan Martin Cooney |
| Classifying heart diseases based on heart random numbers | Heart signal has entropy and can be used to generate random numbers. The idea is that, given a bunch of random numbers, we should predict if the source suffer from a desease | Pablo Picazo | |
| Collaborative Filtering Recommendation System Location Content-based | Analyze the content stored in Collaborative Filtering Recommendation System based on the location of the users | Pablo Picazo | |
| Consensus clustering for categorizing orthogonal vehicle operations | Dirar Sweidan | Discovering multiple clustering solutions, compare them, and find out if there is a single best (consensus) clustering, or multiple consistent clustering solutions. | Mohamed-Rafik Bouguelia Sławomir Nowaczyk |
| Constrained dynamic path planning for truck and trailer | Imanol Mugarza | Constrained dynamic path planning for truck and trailer | Iulian Carpatorea Sławomir Nowaczyk Jennifer David |
| Courteous robot guide for visitors to an intelligent home | Jiamiao Guo Yu Zhao |
Courteous robot guide for visitors to an intelligent home | Wagner de Morais Martin Cooney |
| Detecting Points of Interest for Robotic First Aid | Wolfgang Hotze | Detecting Points of Interest for Robotic First Aid | Anita Sant'Anna Martin Cooney |
| Detection and intention prediction of pedestrians in zebra crossings | Dimitrios Varytimidis | Detection and intention prediction of pedestrians in zebra crossings | Fernando Alonso-Fernandez Cristofer Englund Boris Duran |
| Evolutionary Behavior Trees for Multi-Agent Task-Oriented Environment | Milosz Mazur | Evolutionary generating Behavior Trees for use in multi-agent task-oriented environment. | Sławomir Nowaczyk |
| Exploration and Mapping of Warehouse Using Quadrotor Helicopters | Maytheewat Aramtattana Yuantao Fan |
Implementation of a navigation method for a flying robot (Quadrotor). The robot is assigned to explore and map the warehouse. | Björn Åstrand Saeed Gholami Shahbandi |
| F1tenth | F1tenth competition | Sławomir Nowaczyk Cristofer Englund Wojciech Mostowski |
|
| Finding patterns/motifs in time series data | Felix Nilsson | Finding patterns/motifs in time series data, for autonomous clustering or outlier detection | Thorsteinn Rögnvaldsson Mohamed-Rafik Bouguelia |
| FirstResponse | Gloria | First response to emergency situation in a smart environment using a mobile robot | Anita Sant'Anna |
| Fuzz testing of network protocols | Filip Kågesson | Investigation how fuzz testing of network protocols could be implemented and provide rapid robustness testing | Wojciech Mostowski |
| Graphical Traffic Scenario Editor | Iulian Carpatorea | Develop an interactive graphical application to draw vehicle paths and their surrounding environment, for rapid prototyping of traffic scenarios in intelligent vehicle research. | Roland Philippsen |
| Improved face tracking driven by optical flow | Andreas Ranftl | Face Tracking Using Optical Flow | Stefan Karlsson Fernando Alonso-Fernandez Josef Bigun |
| Improving MEDication Adherence through Person Centered Care and Adaptive Interventions iMedA | Alexander Galozy | Improving MEDication Adherence through Person Centered Care and Adaptive Interventions iMedA | Sławomir Nowaczyk Anita Sant'Anna |
| Integrating a new rigid-body dynamics model library with an existing whole-body controller | Anton Jerey Thomas Holleis Marlene Mohr |
Integrating a new rigid-body dynamics model library with an existing whole-body controller | Roland Philippsen |
| Investigating Robustness of DNNs | Matej Uličný | This master thesis project aims at characterizing sensitivity to classification of images (based on deep neural networks). | Jens Lundström Stefan Byttner |
| Label and Barcode Detection and Location in Large Field of View | Guanjie Meng Shabnam Darman |
Wide angle images are logged during a warehouse exploration. Design of a detection and localization method for barcodes (and/or labels) in the scope, based on such an acquisition is desired. | Björn Åstrand Saeed Gholami Shahbandi |
| Mixed-Reality Robot Platform | Norbert Gruenwald | Build foundations for our mixed-reality platform by integrating and demonstrating an extensible system with one or more robots, a simulator, some offboard sensors, and simple teleoperation. | Roland Philippsen |
| Mobile Social Robot for Healthcare | Matthias Mayr | Pilot study about a small interactive mobile robots for therapy and healthcare in homes. | Roland Philippsen Magnus Clarin |
| Model Volvo Truck Lifetime Repair History | Anton Palmqvist | Finding good representations for data-driven description of Volvo truck's repair and maintenance history | Sławomir Nowaczyk Sepideh Pashami |
| RAQUEL Robot Assisted QUiz Espying of Learners | Sanjana Arunesh Abhilash Padisiva |
RAQUEL Robot Assisted QUiz Espying Learners | Josef Bigun Martin Cooney Fernando Alonso Fernandez |
| RaspberryPiVolvoLogger | Anestis Zaganidis | RaspberryPi-based solution for logging CAN data on Volvo trucks | Sławomir Nowaczyk Yuantao Fan |
| Recurrent and Deep Learning for Machine Prognostics | Kunru Chen | Construct and optimise Recurrent Neural Networks for industrial applications on machine prognostics; Augmenting industrial data for supervised learning | Sławomir Nowaczyk Sepideh Pashami Yuantao Fan |
| Robot Artwork | Daniel Westerlund Sowmya Narasimman |
Capability for a robot to paint to express human feelings | Martin Cooney Maria Luiza Recena Menezes |
| Robotic First aid response | Tianyi Zhang and Yuwei Zhao | A robot system which assesses a person's state of health as a first step toward autonomous robotic first aid/ems | Martin Cooney Anita Sant'Anna |
| Sailboat Motion Planning using the Level-Set Method | Lin Ge Yifei Li |
Explore the use of Level-Set and Fast-Marching Methods to create time-optimal motions of a point in a plane subject to direction-dependent velocity. | Roland Philippsen |
| Smart Home Simulation | Solved by internal/external resources | Developing and evaluation of a smart home simulator and outlier detection methods. | Jens Lundström Antanas Verikas Sławomir Nowaczyk |
| Supervised/Unsupervised Electricity Customer Classification | Soniya Ghorbani | Consumer characterization framework based on knowledge discovery in smart meter data | Sławomir Nowaczyk Anita Sant'Anna Hassan Mashad Nemati |
| Thermal Detection of Subtle Human Cues for a Robot Magic Performance | (NOT AVAILABLE) | Thermal Detection of Subtle Human Cues for a Robot Magic Performance (NOT AVAILABLE HT22/VT23) | Martin Cooney |
| Vehicle Operation Classification | Karthik Bangalore Girijeswara | Classify modes of operation of Volvo vehicles based on on-board data | Sławomir Nowaczyk Yuantao Fan Mohamed-Rafik Bouguelia |
| Visual analysis for infotainment in car interiors | Josef Bigun Maycel Isaac Faraj |
Visual analysis to steer infotainment in car interiors | Josef Bigun Stefan Karlsson Maycel Isaac Faraj |
Internal Drafts
| OneLineSummary | ThesisAuthor | Supervisors | |
|---|---|---|---|
| A decision support system for reducing false alarms in ICU | Developing a clinical decision support system using machine learning and biomedical signal analysis techniques for an ICU setting. | Sławomir Nowaczyk Awais Ashfaq |
|
| Acumen Robot Model Series | Build a series of increasingly sophisticated robot models in Acumen, to (1) explore mathematical formulations and (2) create tutorials and didactic examples. | Roland Philippsen Walid Taha |
|
| Algorithm development for realtime route planning | Project at Sigma Technology | Thorsteinn Rögnvaldsson | |
| Analysing Engine Performance based on Vehicle Data | Estimate engine perfromance based on data logged on-board Volvo vehicles and using it for diagnostics, e.g. detection of cylinder heads in need of replacement | Sławomir Nowaczyk Magnus Svensson |
|
| Anomaly Detection for Predictive Maintenance with Elvaco | Anomaly Detection for Predictive Maintenance with Elvaco | Mohamed-Rafik Bouguelia Yuantao Fan |
|
| Anomaly detection in district heating data - with the Elvaco company | Project around predictive maintenance in district heating | Yuantao Fan Mohamed-Rafik Bouguelia |
|
| Clustering of battery usage pattern for Electric buses | Clustering of battery usage pattern for Electric buses | Sepideh Pashami Yuantao Fan |
|
| Convolutional Neural Network (CNN) responses when the number of classes increase | Convolutional Neural Network (CNN) features behaviour in the context of textures | Josef Bigun Fernando Alonso-Fernandez |
|
| Developing an Intelligent Data-Driven Chatbot for Enhanced Information Retrieval and Interaction | Design, implement, and evaluate a chatbot system capable of interacting with users and extracting pertinent information from data | Yuantao Fan Sławomir Nowaczyk |
|
| Development of surveillance methods for sterilizers | Development of surveillance methods for sterilizers | Thorsteinn Rögnvaldsson Sławomir Nowaczyk Stefan Byttner |
|
| Evaluation of Open Source Robot Simulators for Smart Mobility Applications | Can open source robot simulators serve as starting point for cloud services that support automotive R&D and V&V? | Roland Philippsen Saeed Gholami Shahbandi Christian Berger (Chalmers) |
|
| Explainable Anomaly Detection | Explainable anomaly detection in time series data utilising causal inference | Afroj Divan; Athulya Ashok | Yuantao Fan |
| Gait analysis using wearable sensors in Parkinson's disease | The project aims to develop a machine learning tool for the assessment of Parkinsonian gait in a natural environment | Taha Khan | |
| Merging Clothoids with B-Splines | Develop an approach to create natural clothoidal lane-change maneuvers for automobiles on lanes that are specified using B-splines. | Roland Philippsen | |
| MultiScale Microscopy Detailed | Master Thesis Project | Amir Etbaeitabari Mekuria Eyayu |
Stefan Karlsson Josef Bigun |
| Obstacle Identification from 3D Data for AGVs in a Warehouse Environment | Obstacle Identification from 3D Data for AGVs in a Warehouse Environment | Björn Åstrand Saeed Gholami Shahbandi |
|
| Path Planning | Path and Motion Planning for a Ferry | Sławomir Nowaczyk Yuantao Fan Hadi Fanaee Or Mohamed Abuella |
|
| Predicting Energy Consumption for Heavy-Duty Vehicles (in collaboration with Volvo) | Develop machine learning methods to forecast energy consumption for heavy-duty vehicles | Yuantao Fan Mahmoud Rahat |
|
| Representation of Complex Data Types for Machine Learning | Finding ways to represent complex data types (e.g. histograms) present in Logged Vehicle Database databse for machine learning-based fault prediction | Sławomir Nowaczyk Sepideh Pashami |
|
| Semantic Analysis of 2D Maps With a Metric-Topological Approach | Semantic Analysis of 2D Maps With a Metric-Topological Approach. | Björn Åstrand Saeed Gholami Shahbandi |
|
| Simulating Crowds for Traffic Safety Research | Integrate crowd simulation into a mixed-reality platform for development and testing of advanced automotive safety systems. | Roland Philippsen | |
| Thesis with Jayway | Thesis with Jayway | TBD | |
| Thesis with Medius | Three thesis topics with Medius | TBD Please contact Slawomir Nowaczyk |
|
| Time series anomaly detection for heavy-duty vehicles | Detecting anomalies in multivariate time series data collected from vehicle operations | Yuantao Fan Hamid Sarmadi |
Introduction lecture presenting the process and expectations on MSc project will take place on Monday, 14 October 2019 at 15:15.
The next opportunity for MSc presentations is on Monday, 23 September 2019 at 13:15 (contact Slawomir if you intend to make the presentation, so that we know how many to plan for). Also, make sure to send the supervisor-approved reports to the examiners a week before, so by 16 September 2019. After that we will have the final(!) opportunity sometime in late December/early January.
Final presentations should be 15 minutes long, and must cover the goals/objectives, final contribution/novelty, the results and conclusions from the work.
Final presentation is scheduled on Wednesday, 29 May 2019 [turns out Thursday is a holiday] (which means the examiners need to receive your reports by Thursday, 23 May 2019 at noon).
There will be a chance to re-do half-time presentations, for those who were not ready in March, around middle of May.
Half-time presentations should be 20 minutes long, and must cover the goals/objectives, expected contribution/novelty, results achieved so far, and a refined plan on how to proceed.
Topic selections are due on 27th of October 15:00 (use this GoogleForms link).
For students who started their MSc in 2018, the final opportunity to present their thesis will be on Friday, 13th of December 2019, at 16:00 (room F506). Deadline (strict!) for submitting reports is Wednesday, 11th of December, at noon.
Half-time seminar will be on 19th of February (preliminary time: 9-15, depending on number of projects that are ready in time). This means you should send the reports to the examiners on the 18th of February before lunch (this form). Please note that it's a bit earlier than I've indicated during the introductory lecture, as we've decided it makes more sense to provide this feedback sooner rather than later. The final seminar will be at the end of May (reports due in the middle of May).
Start report is due (approved by supervisors!) on 6th of December 23:59, and presentations will be done on 9th and 11th of December (you are expected to attend & listen both days).
You should prepare 10 minutes presentation, focusing on problem formulation, novelty & contribution, literature review and project plan.
The second chance for half-time presentations will be on Thursday, 12th of March (preliminary time: 13-16, depending on number of projects that are ready in time). This means you should send the reports to the examiners on the 11th of March before lunch (this form). The final seminar will be at the end of May (reports due in the middle of May).
Half-time presentations should be 20 minutes long (plus ~10 minutes for questions), and must cover the goals/objectives, expected contribution/novelty, results achieved so far, and a refined plan on how to proceed.
The final presentation is scheduled on Thursday, 28 May 2020 (which means the examiners and opponent need to receive your supervisor-approved reports by Thursday, 21 May 2020 at noon -- use this form to send your report to supervisors, and email it to the opponent).
Make sure to have at least two iterations of feedback on the report, so you should send the initial draft to your supervisors at latest in the first week of May. If you don't make it, the next opportunity will be at the end of August/beginning of September.
Final presentations should be 15 minutes long and must cover the goals/objectives, final contribution/novelty, the results and conclusions from the work. It will be followed by 15 minutes of questions/discussion with the opponent (selected by the supervisor) and the examiners. Be advised that 15 minutes is very short, so you should carefully select what do you talk about, focusing on the most important aspects.
The second opportunity for final presentations will be on Thursday, 3 September 2020 (done online, on Zoom)... which means the examiners and opponent need to receive your supervisor-approved reports by Friday, 28 August 2020 at noon -- use this Google form to send your report to examiners, and email it to the opponent.
Make sure to have at least two iterations of feedback on the report, so you should send the initial draft to your supervisors at latest in the first week of August (take into account any vacation plans!). If you don't make it, the next opportunity will be in December/January.
Introduction lecture presenting the process and expectations on MSc project will take place on Thursday, 15 October 2020 at 10:00 (sharp) through Zoom. The link should be available in your schedules.
Topic selection: provide a ranking of three preferred topics by Wednesday, 28th of October, 18:00 using this GoogleForm
A start report is due (approved by supervisors!) on 10th of December 23:59 (using this link).
Schedule for presentations in week 51 (you are expected to attend & listen to all) is available here (please observe some changes are still expected, mainly based on supervisors' availability, so please check it regularly).
You should prepare 10 minutes presentation, focusing on problem formulation, novelty & contribution, literature review and project plan.
Presentations Zoom link
The next deadline for start reports, for those who didn't make it this time, is 15th of January 23:59 (using this link).
For those who were not ready with halftime reports in March, there will be another opportunity on Wednesday, 12 May 2021 (the deadline for submitting reports is 9th of May, same Google Form)
Half-time presentations should be 20 minutes long (plus ~10 minutes for questions) and must precisely specify the goals/objectives, clearly explain the expected contribution/novelty, showcase the results achieved so far, and present a refined plan on how to proceed further.
The final seminar will be in about two weeks, preliminarily on 2nd, 3rd and/or 4th of June, depending on the number of projects that are ready (reports due on 25th of May at 12:00 noon, using this form).
The second opportunity for final presentations of MSc theses will be on Friday, 20 August 2021 (done online, on Zoom)... which means the examiners and opponent need to receive your supervisor-approved reports one week earlier -- use this Google form to send your report to examiners, and email it to the opponent.
Make sure to have at least two iterations of feedback on the report, so you should send the initial draft to your supervisors at the latest in the first week of August (take into account any vacation plans!). If you don't make it, the next opportunity will be in December/January.
Final presentations should be 15 minutes long and must cover the goals/objectives, final contribution/novelty, the results and conclusions from the work. It will be followed by 20-30 minutes of questions/discussion with the opponent (selected by the supervisor) and the examiners. Be advised that 15 minutes is very short, so you should carefully select what do you talk about, focusing on the most important aspects.
The next and final opportunity for half-time presentations will be in late August. Submit your reports on Google Form and email Slawomir to schedule the presentation.
Introduction lecture presenting the process and expectations on the MSc project will take place on Wednesday, 13 October 2021 at 15:15 in D315.
Please note that it will not appear in your schedule, since the course has not started yet.
Before the lecture, please watch the video recording and read updated slides.
This way, in the physical meeting we can focus on discussion and answering any questions you might have.
For the selection of thesis topics, you should provide a ranking of three preferred topics by Wednesday, 27 October 2021, 18:00 using GoogleForm.
A start report is due (approved by supervisors!) on 12th of December 18:00 using this form. This means that you should send a reasonably complete draft to your supervisors before the end of November, so that they have time to provide feedback, and you have time to incorporate this feedback into your final report...
Presentations will take place in week 50 (you are expected to attend & listen to all, or at least most, of them).
You should prepare 10 minutes presentation, focusing on problem formulation, novelty & contribution, literature review and project plan.
For those students who started in January, the initial report is due (approved by supervisors!) on 30th of January at 16:00 using this form. This means that you should send a reasonably complete draft to your supervisors quite soon, so that they have time to provide feedback, and you have time to incorporate this feedback into your report...
Presentations will take place in week 5, probably on Friday, 4 February 2022.
You should prepare 10 minutes presentation, focusing on problem formulation, novelty & contribution, literature review and project plan.
Dear students, you should have received an email with a link to Google Spreadsheet with thesis topics assignment. It was sent to all those who submitted thesis topic selections using GoogleForm. If you have not received it, please let me (Slawomir) know ASAP.
Half-time reports are due tomorrow. However, I have been hearing that many of you have problems making the deadline. Thus, we've decided to offer an (additional) second opportunity -- in two weeks. If you can have a good quality report ready tomorrow you should still submit it, since timeliness is an important part of MSc project.
If you cannot, on the other hand, your next deadline for sending the reports to the examiners is Friday, 01 April 2022, at lunchtime (using this form).
Presentations, in that case, will be sometime in week 14.
Half-time presentations will be in week 12, probably between Wednesday, 23 March and Friday, 25 March 2022 (depending on number of projects that are ready in time).
This means the deadline for sending the reports to the examiners is the Friday, 18 March 2022, lunchtime (using this form).
The final seminar will be at the end of May (reports due in the middle of May).
The schedule for half-time presentations has now been updated with (preliminary) presentation times for those who submitted their reports on the second deadline: https://docs.google.com/spreadsheets/d/1FK-OjzhQdIbfMkeyvGLneJzSV6znejgG9fG19Wv1VXU/edit#gid=223334201
Half-time presentations should be 20 minutes long (plus ~10 minutes for questions), and must cover the goals/objectives, expected contribution/novelty, results achieved so far, and a refined plan on how to proceed.
Final presentations of MSc theses will be primarily on Wednesday, 1 June and Thursday, 2 June... which means the examiners and opponent need to receive your supervisor-approved reports one week earlier -- use this Google form (deadline: Wednesday, 25 May 2021 at 12:00 noon) to send your report to examiners, and email it to the opponent.
Make sure to have at least two iterations of feedback on the report, so you should send the initial draft to your supervisors at the latest in the second week of May. If you don't make it, the next opportunity will be in late August/early September.
Final presentations should be 15 minutes long and must cover the goals/objectives, final contribution/novelty, the results and conclusions from the work. It will be followed by 25-30 minutes of questions/discussion with the opponent (selected by the supervisor) and the examiners. Be advised that 15 minutes is very short, so you should carefully select what do you talk about, focusing on the most important aspects.
You should pick your topic (select three, in order of preference) by Wednesday, 26th of October, 18:00. Submit your choice on this GoogleForm.
The introduction lecture presenting the process and expectations of the MSc project took place on Monday, 3 October 2022. Slides are available below.
The start reports are due on December 8th at 21:00 (using this form); presentations will take place in week 50.
Please remember that the report must be approved by supervisors first, so a reasonable schedule is: on the 25th of November send the report to supervisors; around the 2nd of December, you get feedback; then you have a week to address the comments.
For those who begin the Thesis course in January, the start report is due on Wednesday, 25th of January (make sure to also account for supervisor approval and revision time).
The second deadline for half-time reports, for those who didn't make it in March, is Monday, 17th of April (using this form).
The deadline for half-time reports is Wednesday, 15th of March (using this form), and the half-time presentations will be scheduled in week 12.
Half-time presentations should be 20 minutes long (plus ~10 minutes for questions) and must cover the goals/objectives, expected contribution/novelty, results achieved so far, and a refined plan on how to proceed.
Please remember that the report must be approved by supervisors first, so a reasonable schedule is: send the report to supervisors around the 1st of March; around the 8th of March, you get feedback; then you have a week to address the comments.
The deadline for final MSc reports (as always, supervisor-approved) is Tuesday, 23 May 2023, at 12:00 noon. Use this Google form to send your report to examiners.
Make sure to have at least two iterations of feedback on the report, so you should send the initial draft to your supervisors at the latest in the second week of May. If you don't make it, the next opportunity will be in late August/early September.
Remember that you also need to email the final report to the opponent. The opponent is decided by your supervisors, and it is generally one of the researchers here at ITE.
The final presentations will be in week 22. I'll make a schedule when I receive all your reports, but the time slots you can find already now in the same Google Sheet document as all the previous schedules. If you have any constraints, please let me know in the comment when submitting your report, and I'll do my best to accommodate them.
Final presentations should be 15 minutes long and must cover the goals/objectives, final contribution/novelty, the results, and conclusions from your work. It will be followed by 25-30 minutes of questions/discussion with the opponent (selected by the supervisor) and the examiners. Be advised that 15 minutes is very short, so you should carefully select what do you talk about, focusing on the most important aspects.
For students starting their MSc Thesis course in November 2023 (or January 2024), we'll have and introduction lecture on Friday, 29 September at 9:00 in room S1078.
For those who are planning to do the halftime or final MSc presentation now after summer, the deadline for submitting the report is Thursday, 31 August. We'll then try to schedule presentations in the first half of September. The third and final opportunity for thesis defense will be in December 2023, or possibly January 2024.
Submit final reports using this Google form and half-time reports using this form.
Make sure to have at least two iterations of feedback on the report, so you should send the initial draft to your supervisors early enough. Also, remember that you also need to email the final report to the opponent. The opponent is decided by your supervisors, and it is generally one of the researchers here at ITE.
Final presentations should be 15 minutes long and must cover the goals/objectives, final contribution/novelty, the results, and conclusions from your work. It will be followed by 25-30 minutes of questions/discussion with the opponent (selected by the supervisor) and the examiners. Be advised that 15 minutes is very short, so you should carefully select what do you talk about, focusing on the most important aspects.
Half-time presentations should be 20 minutes long (plus ~10 minutes for questions) and must cover the goals/objectives, expected contribution/novelty, results achieved so far, and a refined plan on how to proceed.
I've sent out emails with (preliminary) topic assignments. If you've submitted the topic selection form, but did not receive this email, contact me (Slawomir) ASAP!
You should pick your topic (select three, in order of preference) by Wednesday, 25th of October, 18:00. Submit your choice on this GoogleForm.
The introduction lecture presenting the process and expectations of the MSc project took place on Friday, 29 September 2023. Slides from that lecture are available below.
The schedule for the Project Proposal presentations is now available in the GoogleSheet.
For those who didn't quite make it on Friday, there will be an additional report deadline on Wednesday, 20 December, with presentations in week 2.
A reminder: the deadline for the "project proposal" report is the 8th of December at 17:00 (please submit it here).
Remember that it must be approved by the supervisor first, and you need to give them sufficient time to read it, provide feedback, *and* for yourselves to incorporate this feedback. This means that you should send a reasonably complete draft to your supervisors as soon as possible if you haven't done it yet...
Presentations will take place in week 50 (you are expected to attend & listen to all, or at least most, of them).
For students starting the thesis work in LP3, the deadline for the project proposal is 25 January at 17:00 (please submit it here).
Presentations will be scheduled one/two weeks later (you are expected to attend & listen to all, or at least most, of them).
You should prepare 10 minutes presentation, focusing on problem formulation, novelty & contribution, literature review, and project plan.
For the halftime report, the middle of March deadline is common for all.
For those who didn't make it for the report submission last week, the next deadline for sending in the halftime report is Sunday, 7 April at 23:59 -- using this form.
The first batch of the halftime presentations will take place on 25-26 March (detailed schedule is here). Please note that attending the halftime presentations (at least the majority of them) is mandatory -- and I will be taking attendance lists!
The second batch of the halftime presentations will take place on Thursday, 18 April (detailed schedule is here). Please note that attending the halftime presentations (at least the majority of them) is mandatory -- and I will be taking attendance lists!
Half-time presentations should be 20 minutes long (plus ~10 minutes for questions) and must cover the goals/objectives, expected contribution/novelty, results achieved so far, and a refined plan on how to proceed.
The deadline for final MSc reports (as always, supervisor-approved) is Friday, 24 May 2024, at 23:59. Use this Google form to send your report to examiners.
Make sure to have at least two iterations of feedback on the report, so you should send the initial draft to your supervisors more or less right now.
Remember that you also need to email the final report to the opponent. The opponent is decided by your supervisors, and it is generally one of the teachers/researchers here at ITE.
The final presentations will be in weeks 22 and 23. I'll make a schedule when I receive all your reports, but the time slots you can find already now in the same Google Sheet document as all the previous schedules. If you have any constraints, please let me know in the comments when submitting your report, and I'll do my best to accommodate them.
Final presentations should be 15 minutes long and must cover the goals/objectives, final contribution/novelty, the results, and conclusions from your work. It will be followed by 25-30 minutes of questions/discussion with the opponent (selected by the supervisor) and the examiners. Be advised that 15 minutes is very short, so you should carefully select what do you talk about, focusing on the most important aspects.
If you don't make it this time, the next opportunity will be in late August/early September.
The second deadline for final MSc reports (as always, supervisor-approved) is Sunday, 15 September 2024, at 23:59. Use this Google form to send your report to examiners. If that deadline is problematic for you, discuss it with your supervisors and contact Slawomir.
If you don't make it this time, the next (and final) opportunity will be in December.
