Student projects
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.
Contents
- 1 Information about MSc Thesis process
- 2 Useful resources for your MSc Thesis process
- 3 Current Proposals of Msc and Bsc Project
- 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).
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 and video recording
DT7001 course syllabus and DT7002 course syllabus
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
Current Proposals of Msc and Bsc Project
Supervisors | OneLineSummary | |
---|---|---|
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) |
Anomaly detection from IoT Time Series @AlfaLaval | Hadi Fanaee | Anomaly detection from IoT Time Series @AlfaLaval |
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 |
Autonomous flying drone for vehicle classification | Cristofer Englund Fernando Alonso-Fernandez Martin Torstensson |
Building an autonomous flying drone for vehicle classification |
Building a Knowledge-based AI Framework for Mobility | Enayat Rajabi Sławomir Nowaczyk |
Leveraging new knowledge to improve the productivity of mobility services |
Data Heterogeneity in Federated Learning | Amira Soliman Sławomir Nowaczyk |
Addressing the challenges of data imbalance in Federated Learning |
Data analysis in collaboration with WirelessCar | Mahmoud Rahat Peyman Mashhadi Sławomir Nowaczyk |
Data analysis in collaboration with WirelessCar |
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). |
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. |
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. |
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. |
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. |
Deepfake Detection | Stefan Byttner Jens Lundström Peyman Mashhadi |
Detecting deepfake images and videos using a diversified ensemble of deep models |
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. |
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. |
Explainable AI and poverty prediction | Thorsteinn Rögnvaldsson Mattias Ohlsson |
Provide explanations of AI data-driven poverty predictions in sub-saharan africa |
Explainable AI for predictive maintenance in collaboration with Volvo | Mahmoud Rahat Peyman Mashhadi |
Developing explainable models for predicting components failures of Volvo trucks |
Forecasting Industrial IoT Time Series @AlfaLaval | Hadi Fanaee | Forecasting industrial IoT Time Series |
Generative Approach for Multivariate Signals | Kunru Chen Tiago Cortinhal Thorsteinn Rögnvaldsson |
The topic focuses on generative models (GAN) for CAN-bus data and investigating the representation learning capabilities of such techniques |
Hydro Power Station | Slawomir Nowaczyk / TBD | Collaboration with Ålberga Bruk 1919 |
Incorporate behaviour modelling into AGV safety performance stack | Björn Åstrand | Incorporate behaviour modelling into AGV safety performance stack |
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. |
LiDAR Denoising | Eren Erdal Aksoy | In this project, the candidate is supposed to implement various filtering algorithm to denoise 3D LiDAR point cloud data. |
Lighting up the bicycle roads with drones | Cristofer Englund Lei Chen |
Lighting up the bicycle roads with drones |
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 |
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 |
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. |
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. |
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 |
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)). |
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 with Atos | TBD Please contact Sławomir Nowaczyk if interested |
The project involves the development of software for the TrueDepth technology of the iPhone. |
Project with Whole AB | Slawomir Nowaczyk / TBD | TBD |
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 | To be decided (contact Slawomir Nowaczyk for more details) | Thesis topics at Volvo Car Corporation |
Project(s) at Volvo Group | To be decided (contact Slawomir Nowaczyk for more details) | Thesis topics at Volvo Group |
Sandboxed scripting on embedded systems | TBD Please contact Slawomir and Hans-Erik Eldemark |
Sandboxed scripting on embedded systems |
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. |
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)). |
Surface normal estimation by Spiral Codes | Josef Bigun | Estimating 3d surface normal from a single image |
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 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. |
Thesis with Medius | TBD Please contact Slawomir Nowaczyk |
Three thesis topics with Medius |
Transfer Learning for Network Security | Sławomir Nowaczyk Zahra Taghiyarrenani |
Study of Transfer Learning techniques in Network Security applications- Network Traffic Classification and Intrusion Detection |
Uncertainty quantification for data driven clinical decision making | Awais Ashfaq | The student will build upon the field of evidential deep learning to identify and understand when the model says 'I don't know' |
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. |
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 |
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!)
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. | |
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Analysis of multi-machine/multi-sensor data | Hadi Fanaee-T (www.fanaee.com) Mahmoud Rahat |
Data mining on multi-machine/multi-sensor time series data | 22 October 2020 13:36:50 |
Beyond 5G baseband processing on a multicore architecture | Süleyman Savas | Implementation and evaluation of beyond 5G baseband algorithms on an embedded (Epiphany) processor with 16 cores | 21 October 2020 06:21:39 |
Optimisation in Heavy Duty Vehicles Configuration | Reza Khoshkangini | In this project we aim to optimise the vehicles setting based on their usage style. Here we focus more on fuel consumption. | 19 October 2020 12:51:51 |
Transfer Learning by Selection of Invariant Features | Mohammed Ghaith Altarabichi Abdallah Alabdallah |
The project aims to develop novel methods to identify invariant features to transfer across multiple domains. | 15 October 2020 10:25:42 |
Hide-and-Seek Privacy Challenge (NeurIPS 2020) | Onur Dikmen | Building novel methods for privacy-preserving data sharing and/or re-identification | 13 October 2020 10:31:00 |
Smart Alarm | Hadi Fanaee-T(www.fanaee.com) Mahmoud Rahat |
Data-driven alarm prediction using sensor data | 12 October 2020 11:47:57 |
Predicting the status of machines with vibration data | Hadi Fanaee-T (www.fanaee.com) Mahmoud Rahat |
Predicting the status of Alfa Laval's separator machines with vibration data | 12 October 2020 11:47:36 |
Reinforcement learning in Automation | Reza Khoshkangini | In this project we plan to use reinforcement learning in multi-agent systems to improve decision making. in automated systems. | 9 October 2020 11:51:36 |
Vehicle Usage Modeling over Time | Reza Khoshkangini Abbas Orand |
This project intents to explore the modeling of the usage of vehicles using unsupervised machine learning algorithms in different context which are logged over time. | 9 October 2020 11:42:02 |
Anomaly Detection of the Activities of the Elderly Living in the Smart Home | Abbas Orand Reza Khoshkangini |
In this project we detect the anomaly of the actives of the elderly people or those with some sorts of health problem. | 9 October 2020 11:37:53 |
Optimisation Algorithm for Feature enginnering | Reza Khoshkangini | In this project we intend to design an optimisation system using artificial intelligence algorithms in order to select/extract the best features for developing a forecasting system in predictive maintenance. | 9 October 2020 10:21:14 |
Zero-Shot Learning for Semantic Segmentation | Tiago Cortinhal Eren Erdal Aksoy |
Zero-Shot Learning for Semantic Segmentation | 9 October 2020 08:40:01 |
Automatic Generation of Realtime Machine Learning Architectures | Yousra Alkabani Hazem Ali |
In this project, it is required to build a tool to generate a dataflow model and construct architectures for such algorithms, while minimizing latency or meeting a specific deadline under area and power constraints. | 8 October 2020 16:14:16 |
Reversible GANs | Cristofer Englund Felix Rosberg |
Reversible GANs | 8 October 2020 12:30:33 |
Situation awareness in traffic | Cristofer Englund Björn Åstrand |
Situation awareness in traffic | 8 October 2020 12:29:24 |
Indoor localization for ground vehicles | Cristofer Englund | Indoor localization for ground vehicles | 8 October 2020 12:27:56 |
Transfer Learning for Machine Diagnosis and Prognosis | Peyman Mashhadi Yuantao Fan Mohammed Ghaith Altarabichi |
Study and develop deep adversarial neural networks (DANN) based methods to detect faults and predict failures in industrial equipment, under transfer learning scenarios. | 6 October 2020 18:32:30 |
Reinforcement Learning with Adaptive Representation Learning | Alexander Galozy Peyman Mashhadi |
This project targets finding representations that make the reinforcement learning more efficient in terms of finding an easier state to action mapping. | 5 October 2020 13:38:39 |
Risk as a Service with Volvia | To be decided (contact Slawomir Nowaczyk for more details) | Risk as a Service | 4 October 2020 15:09:34 |
Intelligent claim Process with Volvia | To be decided (contact Slawomir Nowaczyk for more details) | Intelligent claim Process | 4 October 2020 15:07:58 |
Forecast energy consumption in buildings to help Mestro customers save energy | To be decided (contact Slawomir Nowaczyk for more details) | The thesis will be focused on forecasting the energy consumption in buildings (e.g. electricity consumption), with some optional “add-ons” where student will also develop... | 4 October 2020 12:56:56 |
Feature-wise normalization for 3D medical images | Amira Soliman Stefan Byttner Kobra Etminani |
Normalization of 3D medical imaging either as a data pre-processing or as feature-wise batch normalization during CNN model training | 29 September 2020 13:40:00 |
Prioritize informative structures in 3D brain images | Amira Soliman Kobra Etminiani Stefan Byttner |
Identify informative regions in 3D brain images to improve classification accuracy of dementia disorders | 29 September 2020 13:39:34 |
Multitask learning on vehicle data | Mahmoud Rahat Peyman Mashhadi |
Learning shared representation using multitask learning on a vehicle-related data | 28 September 2020 14:14:02 |
Comparative study of an automated testing coverage for a TCP/IP stack implementation | Wojciech Mostowski | The topic of the project is the comparative study of the coverage of the tests generated by the QuickCheck tool against real coverage requirements | 23 September 2020 13:34:05 |
Vehicular Network Graphical Interface | Marco Marinho | Build a graphical tool in python for plotting vehicular networks | 22 September 2020 08:43:47 |
Improved networks for cloud-car communication | Cristofer Englund Eric Järpe Ana Magazinius |
Development of new communication network for more efficient, reliable and diverse traffic flow and hence improved performance driving of cars. | 27 November 2019 13:43:54 |
Ethical hacking of car-cloud communication | Eric Järpe Cristofer Englund |
Designing and assessing attacks against a car-cloud network | 22 November 2019 13:08:38 |
Anomaly detection based on seasonal daily pattern power consumption of buildings in district heating domain | Sławomir Nowaczyk Farzaneh Etminani Ece Calikus |
Detecting anomalous buildings according to how they consume power on a seasonal daily basis | 27 October 2019 19:57:07 |
Self-adaptive Recommender System In Conditional Context | Reza Khoshkangini | In this project we intend to develop an adaptive system that can adapt itself --based on different context-- at providing service to conditional preference of users which change over time. | 25 October 2019 15:44:55 |
AI R&D at King | Sepideh Pashami | Reinforcement learning | 25 October 2019 05:10:37 |
Prediction of neurodegenerative disorders based on brain images | Farzaneh Etminani Stefan Byttner |
prediction of neurodegenerative disorders based on brain images using deep learning algorithms | 23 October 2019 12:56:54 |
Value of BIG DATA for Large Building Owners | Sepideh Pashami | It is an explanatory project with a company called Mutual Benefits Engineering AB | 23 October 2019 07:17:55 |
Modelling vehicles'/drivers' behaviour using LVD | Reza Khoshkangini | Modeling the bahevaior of the vehicles/drivers exploiting the vehicles usage in different context. | 21 October 2019 07:40:39 |
Detection of smart cars cyber attacks | Ana Magazinius (RISE Viktoria) Eric Järpe Cristofer Englund |
For treating the probem of cyber attacks against smart vehicles, new change-point detection and anomaly detection methods by means of statistics and machine learning are developed and evaluated. | 19 October 2019 20:10:40 |
Deep feature analysis and extraction on Logged Vehicle data for the task of predictive maintenance | Mahmoud Rahat Sławomir Nowaczyk |
This project is about applying supervised/unsupervised methods of feature selection on Logged Vehicle data (LVD) from Volvo trucks and investigate the contribution in model construction for different predictive maintenance tasks | 14 October 2019 15:06:30 |
Transfer Learning for Machine Diagnostics and Prognostics | Yuantao Fan Sepideh Pashami Mohammad Ghaith Altarabichi |
Develop a deep adversarial neural networks (DANN) based method to predict failures and estimate machine health, under transfer learning settings. | 14 October 2019 09:39:07 |
AI Enabled Service Market Logistics | Sławomir Nowaczyk Iulian Carpatorea Mahmoud Rahat |
Develop a toolkit for a successful implementation of an AI application for Service Market Logistics, with a working AI in a pilot environment and an implementation process evaluation as an output. | 10 October 2019 07:46:47 |
Electrical stimulator design and development | Abbas Orand & Eren Erdal Aksoy | Multi-pattern electrical stimulator design and development | 8 October 2019 11:13:01 |
Positioning of the user at the HINT | Abbas Orand & Per Sandrum | The positioning of the user at the Halmstad intelligent home (HINT). | 8 October 2019 07:36:04 |
Object Movement Prediction for Autonomous Cars | Tiago Cortinhal | Predicting the movement of objects in the context of autonomous cars | 3 October 2019 14:59:36 |
Embeded wearable sensors application at the HINT | Abbas Orand | Using wearable stretch sensors to recognize activities of a user at HINT | 2 October 2019 07:49:30 |
Embedding DNN models on mobile robots for object detection | Mahmoud Rahat | The idea in this project is to employ transfer learning methods to teach a mobile robot to detect a handful of everyday objects in the real-world environment, and investigate the challenges and difficulties that are faced to this end | 1 October 2019 15:23:53 |
Name of the new projectEstimating agricultural development indicators over large areas from satellite images – an approach using convolutional neural networks and transfer learning | Mattias Ohlsson Thorsteinn Rögnvaldsson |
In this project you will use deep learning models, specifically convolutional neural networks (CNN), to analyze satellite imagery to estimate agricultural development indicators. | 1 October 2019 07:41:18 |
Modelling behavior and interaction of road users in transportation systems | Björn Åstrand Cristofer Englund |
Modelling behavior and interaction of road users in transportation systems | 30 September 2019 13:04:15 |
Segmentation and object identification in warehouse environments using machine learning | Björn Åstrand Naveed Muhammad |
Segmentation and object identification in warehouse environments using machine learning | 30 September 2019 11:45:31 |
Protecting bikers in traffic by computer vision | Josef Bigun | Protecting bikers in traffic by computer vision | 27 September 2019 13:21:58 |
Digit recognition by lip-movements and time recursive Neural Networks | Josef Bigun Kevin Hernandez-Diaz Fernando Alonso-Fernandez |
The project aims to recognize digits by lip movements and neural networks | 27 September 2019 13:15:28 |
Object Detection for Autonomous Vehicles | Eren Erdal Aksoy | Implementing a single-stage deep network to detect vehicles in the segmented 3D LiDAR point cloud | 10 September 2019 13:02:16 |
Representation Learning for Deviation Detection | Sławomir Nowaczyk Yuantao Fan |
Optimise Echo State Networks for time series forecasting and reconstruction. Propose methods, e.g. objective functions, to train Echo State Networks for deviation detection | 9 September 2019 20:20:11 |
… further results |
Ongoing Projects
ThesisAuthor | OneLineSummary | Supervisors | |
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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 |
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Human identification by handwriting of identity text | Identify a hand writer when repeated identity relevant text is available | Josef Bigun Fernando Alonso-Fernandez |
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Ice rink resurfacing system for selfdriving vehicles having spiral codes | ice rink resurfacing system for selfdriving vehicles | 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 |
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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 |
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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 |
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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 | |
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"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 |
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 |
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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 |
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 |
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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 |
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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 |
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Anomaly Detection for Predictive Maintenance with Elvaco | Anomaly Detection for Predictive Maintenance with Elvaco | Mohamed-Rafik Bouguelia Yuantao Fan |
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Anomaly detection in district heating data - with the Elvaco company | Project around predictive maintenance in district heating | Yuantao Fan Mohamed-Rafik Bouguelia |
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Clustering of battery usage pattern for Electric buses | Clustering of battery usage pattern for Electric buses | Sepideh Pashami Yuantao Fan |
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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 |
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Development of surveillance methods for sterilizers | Development of surveillance methods for sterilizers | Thorsteinn Rögnvaldsson Sławomir Nowaczyk Stefan Byttner |
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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) |
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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 |
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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 |
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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 |
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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 |
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.