Student projects

From ISLAB/CAISR

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 deadline for half-time reports is Wednesday, 15th of March and the half-time presentations will be scheduled in week 12.


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 2022.10.03 and video recording (from a few years back, but mostly still applicable)

MSc thesis Course Description

MSc thesis Grading Criteria

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

How to write an abstract

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

  Supervisors OneLineSummary
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.
Action Library for Robot Execution Eren Erdal Aksoy Action Library for Robot Execution
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
Automated Inference regarding Goals in Elite Football Data Andreas
Summrina
Kunru
Martin
Automated Inference regarding Goals in Elite Football Data
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
Be The Change: Video Analysis for Environmental Sustainability Ece Calikus
Sławomir Nowaczyk
Analysis of online climate change video contents and identification of video features rendering a video ‘effective’ using machine learning techniques
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
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
Connected Safety Vest for Roadworkers Oscar Amador Molina
Alexey Vinel
Development and testing of an embedded system for the protection of Vulnerable Road Users
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 Active Learning for LiDAR Point Cloud Segmentation Abu Mohammed Raisuddin
Eren Erdal Aksoy
Active Learning to improve data efficiency for LiDAR point Cloud Segmentation
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.
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
Digital Twin - AFRY TBD (Wojciech Mostowski) Digital twin for consulting firm
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 by Training Introspection Jens Lundström
Peyman Mashhadi
Amira Soliman
Atiye Sadat Hashemi
Research and development of novel XAI methods based on training process information
FLBench: A Comprehensive Experimental Evaluation of Federated Learning Frameworks Sadi Alawadi
Jens Lundström
Exploring Federated Learning Frameworks
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.
Fair representation learning of electronic health records Ali Amirahmadi
Ece Calikus
Kobra Etminani
Fair representation learning of electronic health records
Federated Learning Aggregation Strategies by Weight Exploration Jens Lundström
Amira Soliman
Sadi Alawadi
Investigation of aggregation strategies for federated learning
Generating synthetic time series data in case of data scarcity Alexander Galozy
Peyman Mashhadi
Generating synthetic time series data in case of data scarcity
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
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
Graph Neural Networks for cardiovascular disease Prayag Tiwari The main goal of this project is to explore GNN for cardiovascular disease
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.
Human ground robot interaction Cristofer Englund
Martin Cooney
Fernando Alonso-Fernandez
External communication from mobile robots to minimize conflicts with pedestrians
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
Hydro Power Station Slawomir Nowaczyk / TBD Collaboration with Ålberga Bruk 1919
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
IoT Forensics Mohamed Eldefrawy and Hazem Ali To achieve a systematic approach for data extraction (i.e., imaging), forensically sound, from the hardware level
Joint Analysis of Multimodal data on climate change for the educational purpose Prayag Tiwari
Sławomir Nowaczyk
Ece Calikus
Exploring climate change data using machine learning and deep learning
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.
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
Model-Based Testing of Zero-Copy Protocols Wojciech Mostowski Challenges in Model-Based Testing of Zero-Copy Protocols
Multi-Sensor Fusion for Semantic Scene Understanding Eren Erdal Aksoy Multi-Sensor Fusion for Semantic Scene Understanding
Multiband RF Rectifier for Self-Powered IoT Devices Amjad Iqbal In this project, Mutiband RF rectifiers will be designed for self-powered IoT devices
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.
Optimization of a 5G algorithm by parallelization Hazem Ali Optimization of a 5G algorithm by parallelization
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
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 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
Quantifying exercise-induced muscle fatigue by machine learning Jens Lundström Exploring machine learning methods on an EMG muscle fatigue pipeline
Quantum Machine Learning models for predicting disease Prayag Tiwari explore quantum models, including hybrid (classical-quantum), and apply them to different disease prediction tasks
Real-time bladder scanner Pererik Andreasson Real-time bladder scanner
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.
… further results

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Draft Proposals of Msc and Bsc Project (do not pick this unless you have checked with the supervisor!)

  Supervisors OneLineSummary Status
Analysis of ocular image synthesis for cross-spectral recognition Kevin Hernández-Diaz
Josef Bigun
Fernando Alonso-Fernandez
analyze the performance of generative model for image-to-image translation of ocular images between different spectrum Draft
Browser Extensions Updates Pablo Picazo Clustering and analyzing browser extensions by update frequency Draft
Classifying heart diseases based on heart random numbers Pablo Picazo 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 Draft
Collaborative Filtering Recommendation System Location Content-based Pablo Picazo Analyze the content stored in Collaborative Filtering Recommendation System based on the location of the users 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
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
Identify boundary or, corner test cases for AD/ADAS functions using ML in MIL and HIL environment Sławomir Nowaczyk
Wojciech Mostowski
Identify boundary or, corner test cases for AD/ADAS functions using ML in MIL and HIL environment 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
Mobile App Vulnerable Road Users Oscar Amador Molina
Alexey Vinel
Design, development, and evaluation of a mobile app for the protection of Vulnerable Road Users in a test track 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
Reinforcement Learning applied in mobile health application for hypertion Farzaneh Etminani
Sławomir Nowaczyk
Alexander Galozy
Design a Reinforcement Learning applied in mobile health application for improving medication adherence in hypertensive patients 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
Thermal Detection of Subtle Human Cues for a Robot Magic Performance Martin Cooney Thermal Detection of Subtle Human Cues for a Robot Magic Performance (NOT AVAILABLE HT22/VT23) 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.
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
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' 13 October 2021 11:32:21
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
Transfer Learning for Network Security Sławomir Nowaczyk
Zahra Taghiyarrenani
Study of Transfer Learning techniques in Network Security applications- Network Traffic Classification and Intrusion Detection 20 September 2021 15:48:07
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
Sandboxed scripting on embedded systems TBD
Please contact Slawomir and Hans-Erik Eldemark
Sandboxed scripting on embedded systems 7 January 2021 16:19:04
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
… 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 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
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
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
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)
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
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

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.