Student projects

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Information about MSc Thesis process

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.

This page contains some information about the MSc thesis project (courses DT7001 and DT7002). Please start by reading the information below. Students are supposed to select thesis topics in October, but you are more than welcome to discuss with prospective supervisors before that! However, please observe that the list below is subject to change until 15th of October or so...

MSc thesis project information (the LaTeX template can be found here)

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

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!)

  Supervisors OneLineSummary Status
Analysis of multi-machine/multi-sensor data Hadi Fanaee-T (www.fanaee.com) Data mining on multi-machine/multi-sensor time series data Open
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. Open
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. Open
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 Open
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 Open
Data Heterogeneity in Federated Learning Amira Soliman
Sławomir Nowaczyk
Addressing the challenges of data imbalance in Federated Learning Open
Data analysis in collaboration with WirelessCar Mahmoud Rahat
Peyman Mashhadi
Sławomir Nowaczyk
Data analysis in collaboration with WirelessCar Open
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). Open
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. Open
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 Open
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... Open
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 Open
Hide-and-Seek Privacy Challenge (NeurIPS 2020) Onur Dikmen Building novel methods for privacy-preserving data sharing and/or re-identification Open
Indoor localization for ground vehicles Cristofer Englund Indoor localization for ground vehicles Open
Intelligent claim Process with Volvia To be decided (contact Slawomir Nowaczyk for more details) Intelligent claim Process Open
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 Open
Multitask learning on vehicle data Mahmoud Rahat
Peyman Mashhadi
Learning shared representation using multitask learning on a vehicle-related data Open
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
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. Open
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. Open
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 Open
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 Open
Project(s) at Volvo Cars Corporation To be decided (contact Slawomir Nowaczyk for more details) Thesis topics at Volvo Car Corporation Open
Project(s) at Volvo Group To be decided (contact Slawomir Nowaczyk for more details) Thesis topics at Volvo Group Open
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. Open
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. Open
Reversible GANs Cristofer Englund
Felix Rosberg
Reversible GANs Open
Risk as a Service with Volvia To be decided (contact Slawomir Nowaczyk for more details) Risk as a Service Open
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. Open
Situation awareness in traffic Cristofer Englund
Björn Åstrand
Situation awareness in traffic Open
Smart Alarm Hadi Fanaee-T(www.fanaee.com)
Mahmoud Rahat
Data-driven alarm prediction using sensor data Open
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 Open
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. Open
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. Open
Transfer Learning for Network Security Sławomir Nowaczyk
Zahra Taghiyarrenani
Study of Transfer Learning techniques in Network Security applications- Network Traffic Classification and Intrusion Detection Open
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. Open
Vehicular Network Graphical Interface Marco Marinho Build a graphical tool in python for plotting vehicular networks Open
Zero-Shot Learning for Semantic Segmentation Tiago Cortinhal
Eren Erdal Aksoy
Zero-Shot Learning for Semantic Segmentation Open


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
Clustering of battery usage pattern for Electric buses Sepideh Pashami
Yuantao Fan
Clustering of battery usage pattern for Electric buses Draft
F1tenth Sławomir Nowaczyk
Cristofer Englund
Wojciech Mostowski
F1tenth competition 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
A study about the future and usability of Bio-electronic “smart” implants in humans Taha Khan
Stefan Nordlander
Feasibility study on bioimplants in humans.
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.
AI R&D at King Sepideh Pashami Reinforcement learning
ActNormal Tony Larsson
Stefan Byttner
Cristofer Englund
Driving Behavior Model Identification
Agent and object detection and classification in a warehouse setting Björn Åstrand
Naveed Muhammad
Detection, and classification of different agents (manual driven forklift trucks, other robots, humans) and objects (such as pallets) in a warehouse environment
Air Surveillance for Airport Safety Using Autonomous Vehicles Cristofer Englund
Fernando Alonso-Fernandez
Air Surveillance for Airport Safety Using Autonomous Vehicles
Analyzing Human Motion using Inertial Sensors Siddhartha Khandelwal
Nicholas Wickström
Develop an algorithm that can detect walking events from accelerometers positioned at different parts of the body.
Anomaly Detection on Truck Histograms Sepideh Pashami
Peter Berck
Anomaly Detection on Truck Histograms
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
Anomaly ranking of District Heating Substations Ece Calikus
Sławomir Nowaczyk
Implementing anomaly ranking algorithm to monitor district heating substations.
Automatic Machine Learning (AUTO-AUTO-ENCODER!) Sławomir Nowaczyk
Sepideh Pashami
Automatic configuration algorithm for autoencoders
Barcode mapping in warehouses Björn Åstrand
Saeed Gholami Shahbandi
Using barcode detection and decoding for mapping the infrastructure and inventory of warehouses
Behaviour modeling and classification of vehicles at a roundabout Björn Åstrand
Naveed Muhammad
Modeling of behaviour, classification based on behaviour, and detection of anomalous behaviour in traffic at a roundabout.
Biases in electronic health records Awais Ashfaq
Sławomir Nowaczyk
To evaluate the impact of sample bias on the predictive value of machine learning models built using EHR data
Bowling: human motion quantification + ball quantification Stefan Karlsson Study visual parameters to quantify human and ball motion, aiming to be better bowling player
CACC Tony Larsson
Stefan Byttner
Cristofer Englund
Traffic situation estimator for adaptive cruise control (ACC)
Comprehending low-dimensional manifolds of temporal data from the home Jens Lundström
Eric Järpe
Rebeen Hamad
Study and development of tools and methods for the visualization of (temporal) human activity patterns.
Contactless monitoring of blood pressure using photoplethysmography Taha Khan A camera-based system for non-invasive monitoring of blood pressure
Convolutional Neural Network (CNN) features behaviour in the context of textures Josef Bigun
Kevin Hernandez-Diaz
Fernando Alonso-Fernandez.
The project aims to quantify the behaviour of Convolutional Neural Network (CNN) features in the context of textures.
CoopSim Stefan Byttner
Cristofer Englund
Simulation of cooperative systems behavior in the presence of faults
Cross-Spectrum Ocular Identity Recognition via Deep Learning Kevin Hernandez-Diaz
Fernando Alonso-Fernandez
Josef Bigun
Cross-Spectrum Ocular Identity Recognition via Deep Learning
Data Mining In a Warehouse Inventory Björn Åstrand A study of feature selection and distance measures for clustering big number of categories (>1000) and novelty detection in warehouse environment.
Data mining for fault diagnostics in cyberphysical systems Thorsteinn Rögnvaldsson
Stefan Byttner
Data mining for fault diagnostics in cyberphysical systems
Deep Recurrent Networks for Machine Prognostics Sławomir Nowaczyk
Sepideh Pashami
Yuantao Fan
Construct and optimise Recurrent Neural Networks for industrial applications on machine prognostics; Augmenting industrial data for supervised learning
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
Deep learning and Back Order Solutions Sławomir Nowaczyk Deep learning and Back Order Solutions
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.
Detecting Faults and Estimating Missing Values in Smart Meter Data Sławomir Nowaczyk
Anita Sant'Anna
Hassan Mashad Nemati
Finding outliers and missing energy consumptions, and replace them with estimated values
Detecting changes in causal relations Sepideh Pashami
Sławomir Nowaczyk
Monitoring the operation of bus fleet by tracking the changes in causal network
Detecting different types of machines based on usage Sławomir Nowaczyk
Pablo del Moral
This project is about studying how can we distinguish among different types of machines based on their usage.
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.
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
Driver Prediction for Automative Industry Stefan Karlsson
Cristofer Englund
Investigate if and how it is possible to predict the drivers actions and inentions in a predefined limited number of scenarios
Dynamic Objects Detection and Tracking Björn Åstrand
Naveed Muhammad
Dynamic Objects Detection and Tracking in Warehouses, Using 3D Sensors.
Electrical stimulator design and development Abbas Orand & Eren Erdal Aksoy Multi-pattern electrical stimulator design and development
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
Embeded wearable sensors application at the HINT Abbas Orand Using wearable stretch sensors to recognize activities of a user at HINT
Emergency vehicle movement prediction Cristofer Englund
Stefan Byttner
Emergency vehicle movement prediction
Estimating Architectural Properties of Buildings Based on Heating Data Ece Calikus
Sławomir Nowaczyk
Heating operation is heavily dependent on the specifics of the installation, and understanding this relation is important for improving reliability and energy efficiency
Ethical hacking of car-cloud communication Eric Järpe
Cristofer Englund
Designing and assessing attacks against a car-cloud network
Exploring, modelling and optimization of home care regions Wagner O. De Morais
Jens Lundström
This project is about developing tools and methods for optimization of health care resources using machine learning as the central technology.
Gait analysis using wearable sensors in Parkinson's disease Taha Khan The project aims to develop a machine learning tool for the assessment of Parkinsonian gait in a natural environment
Human Motion Analysis using Inertial Sensors Siddhartha Khandelwal
Nicholas Wickström
Compare and evaluate accelerometer and gyroscopes for analyzing human motion in real-world applications.
Identity verification of humans performing physical activities Siddhartha Khandelwal
Fernando Alonso-Fernandez
Nicholas Wickström
To verify the identity of an individual performing a particular activity with sensors placed at different parts of the body
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.
Improving MEDication Adherence through Person Centered Care and Adaptive Interventions Sławomir Nowaczyk
Alexander Galozy
Improving MEDication Adherence through Person Centered Care and Adaptive Interventions
Intelligible patient representation for outcome prediction of congestive heart failure patients Sławomir Nowaczyk
Awais Ashfaq
Generating patient representation using EHR data
Machine Learning and LeadTime Prediction Sławomir Nowaczyk Machine Learning and LeadTime Prediction
Meta-learning for evaluation and implementation of predictive maintenance solution Pablo del Moral
Sławomir Nowaczyk
Finding the best strategy to schedule a predictive maintenance intervention optimizing the cost of unexpected breakdowns against unuseful visits to the workshop.
Mining For Meanings In Robot Maps Saeed Gholami Shahbandi
Björn Åstrand
To build a hybrid map by augmenting the intrinsic kinematic model of a mobile robot to a spatial map, and semi-supervised learning of meanings towards self/situation awareness.
… 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
FirstResponse Gloria First response to emergency situation in a smart environment using a mobile robot Anita Sant'Anna
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
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
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)
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

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.