School of
Electrical Engineering
and Computer Science

I have/had the privilege of supervising researchers/students at KTH.

Postdoc Reseacher:
  • Yang Zhong
PhD students:
  • Miquel Martí i Rabadán (main-supervisor)
  • Zhu Mandy Xiaomeng (main-supervisor)
  • Louise Rixon Fuchs (main-supervisor)
  • Daniel Olof Sabel (main-supervisor)
  • Vladimir Li (main-supervisor)
  • Shuangshuang Cheng (co-supervisor)
  • Ali Razavian (main-supervisor, 2017)
  • Ali Ghardizadeh (co-supervisor, 2018)
  • Miroslav Valan (co-supervisor, Swedish Museum of Natural History, 2021)
  • Marcus Nordström (co-supervisor, 2023)
Research engineer:
  • Rickard Maus (2024)
  • Ennio Rampello (2022)
  • Frédéric Huy Tran (2021)
Master's students:
  • Oscar Danielsson, current
  • Jacob Hernberg, current
  • Olivia Herber, current
  • Jianting Guo, current
  • Teo Jansson Minne, current
  • Simon Ekman von Huth, Multi-Scale Task Dynamics in Transfer and Multi-Task Learning (2023)
  • Giovanni Castellano, Graph Neural Networks For Events Detection in Footbal (2023)
  • Sandra Tor, Football Trajectory Modeling Using Masked Autoencoders (2023)
  • Alessandro Sanvito, NeRF for Dynamic Scenes Modeling from In-the-Wild Monocular Videos with Humans (2023)
  • Love Marcus, Predicting user churn using temporal information (2022)
  • Oliver Petri, Using Deep Learning for Urban Change Detection On­board Satellites (2021)
  • Daniel Wass, Transformer learning for traffic prediction in mobile networks (2021)
  • Fredrik Segerhammar, Learning to Price Apartments in Swedish Cities (2021)
  • Oscar Eriksson, Scenario dose prediction for robust automated treatment planning in radiation therapy (2021)
  • Najib Yabari, Few-shot Learning with Deep Neural Networks for Visual Quality Control: Evaluations on a Production Line (2020)
  • Sergio Liberman, Dose Prediction from Partial Dose Calculations using Conditional Generative Adversarial Networks (2020)
  • Luca Marson, Enforcing low confidence class predictions for out of distribution data in deep convolutional networks (2020)
  • Panteleimon Myriokefalitakis, Real-time conversion of monodepth visual odometry enhanced network (2020)
  • Alessandro Soci, A study of feature contraction and logit squeezing on adversarial attacks (Universita degli Studi di Firenze, 2020)
  • Manon Deprette, Estimation of player trajectories from context in foolball games using AutoEncooders (2020)
  • Gustaf Jacobzon, Multi-site Organ Detection in CT Images using Deep Learning (2020)
  • Lucas Chizzali, Deep Learning based Turn Light Detection at Road Intersections for Autonomous Driving (2019)
  • Wenjie Yin, Machine Learning for Adaptive Cruise Control Target Selection (2019)
  • Xiao Wei, Deep Active Learning for 3D Object Detection for Autonomous Driving (2019)
  • Linus Härenstam-Nielsen, Deep Convolutional Networks with Recurrence for Eye-Tracking (2018)
  • Mathilde Caron, Unsupervised Representation Learning with Clustering in Deep Convolutional Networks (2018)
  • Mateusz Buda, A systematic study of the class imbalance problem in convolutional neural networks (2017)
  • Sudhanshu Mittal, Semi-supervised Learning for Real-world Object Recognition using Adversarial Autoencoders (2017)
  • Ondrej Holesovský, Compact ConvNets with Ternary Weights and Binary Activations (2017)
  • Oscar Friberg, Recognizing Semantics in Human Actions with Object Detection (2017)
  • Miquel Marti I Rabadan, Multitask Deep Learning models for real-time deployment in embedded systems (2017)
  • Vladimir Li, Evaluation of the CNN Based Architectures on the Problem of Wide Baseline Stereo Matching (2016)
  • Yanbei Chen, Language Semantic Embeddings in Deep Visual Representation (2016)
  • Ludvig Jansson, Automatic Matching of Multimodular Images in Live Golf Environments (2016)
  • Remi Blateyron, Automatic detection of manipulated packages by image comparison (2016)
  • Petter Djupfeldt, Dr. Polopoly - Intelligent System Monitoring (2016)
  • Georgios Dikaros, Energy Efficient Motion Capturing System Using Low-Power Image Sensor (2015)
  • Ioannis Papakostas, Efficient Motion Capturing and Variable Refresh Rate Display System Utilizing CAAC-IGZO Semiconductor FETs (2015)
  • Dennis Sångberg, Automated Glioma Segmentation in MRI using Deep Convolutional Networks (2015)
  • Johan Johansson, Interest Point Detectors and Descriptors for IR Images: An Evaluation of Common Detectors and Descriptors on IR images (2015)
  • Johan Wikström, Evaluating supervised machine learning algorithms to predict recreational fishing success: A multiple species, multiple algorithms approach (2015)
  • Vladan Nikolic, Creating a Graph Database from a Set of Documents (2015)
  • Rickard Norlander, Finding wooden knots in images using ConvNets (2015)
  • Luis Fernando, Online DBSCAN for semi-supervised classification of sound spectra (2014)
  • Mikael Brudfors, Towards real-time, tracker-less 3D ultrasound guidance for spine anaesthesia (2014)
Bachelor's students:
  • Erik Dackander
  • Emil Raksanyi
  • Victor Eriksson
  • Thujeepan Varatharajah
  • Jamila Yusuf Isse
  • Chaimae El Ghouch
  • Apphiah Kabata
  • Felix Engström
  • Eli Pleaner
  • Safir Najafi
  • Ziad Salam
  • Christopher Lilthors
  • Samuel Philipson
Visiting researchers/students:
  • Romeo Lanzino (2023)
  • Hiroki Azuma (2023)
  • Shiu Mochiyama (2018)
  • Atsushi Kawasaki (2018)
  • Ryo Nakashima (2017)
  • Takayuki Sugiura (2017)
  • Yuto Yamaji (2017)
  • Yuta Shirakawa (2016)
  • Shinya Nawata (2016)
Published by: Atsuto Maki (atsuto + at +
Updated 2020-07-31