Student projects

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

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(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.