Student projects

From ISLAB/CAISR

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.


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

MSc thesis Course Description

MSc thesis Grading Criteria

DT7001 course syllabus

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 Whole AB Slawomir Nowaczyk / TBD TBD
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!)

  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
Connected Safety Vest for Roadworkers Oscar Amador Molina
Alexey Vinel
Connected vehicular infrastructure 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
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
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

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.
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
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
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

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.