My name is Johannes A. Stork and I am an Associate Senior Lecturer and WASP Assistant Professor of machine learning at Örebro University where I work at the Center for Applied Autonomous Sensor Systems (AASS). There, I also joined the Autonomous Mobile Manipulation Lab (AMM) as a founding member. My main research interests are in machine learning with interpretable models and autonomous intelligent systems.
Short Bio. In spring of 2020, I started my position as WASP Assistant Professor as part of the Wallenberg AI, Autonomous Systems and Software Program (WASP), Sweden’s largest ever individual research program and major national initiative for strategic basic research, education, and faculty recruitment. From 2018 to 2020, I held a position as Associate Senior Lecturer as part of the vice chancellor’s strategic initiative for faculty development. Before joining AASS in 2018, I was a post-doctoral researcher and before that PhD. student in Computer Science (Computer Vision and Robotics) at the Computer Vision and Active Perception Lab (CVAP) at the Royal Institute of Technology (KTH) in Stockholm. I did my post-graduate research as a member of Danica Kragic’s research group where my co-supervisors were Carl Henrik Ek and Yasemin Bekiroglu. Before that, I spent several years of my undergraduate studies at the University of Freiburg, Germany, as a student research assistant at the Social Robotics Lab of Kai O. Arras. I hold a MSc. and a BSc. degree in Computer Science with concentration in Artificial Intelligence and Robotics from Freiburg University.
News and Recent Results
June 15, 2021 (Open position)
We have an opening for a doctoral student position in machine learning.
June 14, 2021 (Project granted)
Our KKS Synergy project TeamRob where I am involved in two of the sub-projects has been granted.
May 5, 2021 (Open position)
We have an opening for a post-doc in machine learning.
April 1, 2021 (Project start)
Our Vinnova SIP-STRIM project with company partners Epiroc and Algoryx starts.
February 15, 2020 (New team member)
Jean-Paul Ivan joins the team as a doctoral student.
September 23, 2020 (Publication accepted)
Science Robotics print my commentary paper about learning to adapt.
November 2, 2020 (Project completed)
Our Vinnova SIP-STRIM pre-study project HosePredict with company partner Epiroc on modeling hydraulic hoses for underground mining machines finished successfully.
April 1, 2020
I am starting my new position as WASP Assistant Professor of machine learning.
I am is currently involved the following research projects:
- Safe Remote Drilling through Predictive Modeling of Hydraulic Hoses, Vinnova SIP-STRIM, key person / co-applicant
- Predictive Modeling of Hydraulic Hoses for Underground Mining / HosePredict, Vinnova SIP-STRIM pre-study, principle investigator
- WASP Assistant Processor, Wallenberg AI, Autonomous Systems and Software Program, principle investigator
Group and Supervision
I am currently (co-)supervising the following doctoral students:
- Yuxuan Yang (Örebro University), Deformable Linear Object Model Learning with Physics-based Priors, with T. Stoyanov
- Quantao Yang (Örebro University), Reinforcement Learning in Continuous Spaces with Interactively Acquired Knowledge-based Models, with T. Stoyanov
- Jean-Paul Ivan (Örebro University), Robust Gaussian Process for Continual Learning, with T. Stoyanov
- David Caceres Dominguez (Örebro University, Suzuki), Mobile Manipulator Co-worker for Automation of the Drawing Line, with T. Stoyanov and E. Schaffernicht
- Marco Iannotta (Örebro University, Suzuki), Mobile Manipulator Co-worker for Assembly, with T. Stoyanov and E. Schaffernicht
- Alan Lahoud (Örebro University, H&M), Combining Machine Learning and Optimization for Decision Making, with F. Pecora and M. Trincavelli
- Andrey Rudenko (Örebro University, Bosch), Human Motion Prediction for Service Robots, with A.J. Lilienthal and K.O. Arras
- Tiago Almeida (Örebro University), Learning Human Behaviors from Human Robot Interaction, with O. Martinez Mozos and A.J. Lilienthal
- Dino Hüllmann (Örebro University, BAM), Gas Source Localization and Gas Distribution Mapping using an Open Path Gas Detector and Unmanned Aircraft, with A.J. Lilienthal and P.P. Neumann
Alumni Doctoral Students
I previously (co-)supervised the following doctoral students:
- Isac Arnekvist (KTH Royal Institute of Technology), Transfer Learning using low-dimensional Representations in Reinforcement Learning, with D. Kragic
- Mia Kokic (KTH Royal Institute of Technology), Learning for Task-oriented Grasping, with D. Kragic
- Joshua Haustein (KTH Royal Institute of Technology), Robot Manipulation Planning Among Obstacles: Grasping, Placing and Rearranging, with D. Kragic
- Weihao Yuan (Hong Kong University of Science and Technology), Learning Perception and Motion Planning in Robotic Manipulation, with M.Y. Wang
- Haoran Song (Hong Kong University of Science and Technology), TBA, with M.Y. Wang
- Akshaya Thippur (KTH Royal Institute of Technology), TBA, with P. Jensfelt
- Learning Theory and Reinforcement Learning (2020), WASP Graduate School, PhD.-level course, course responsible
- DT505A: Sensors and Sensing (2020, 2021), Örebro University, Master-level course, course responsible
- DT506A: AI on the Web (2020, 2021), Örebro Univeristy, Master-level course, course responsible
- Reinforcement Learning Parts 1 and 2 (2019, 2020, 2021), SMART(ER) at Örebro University, Master-level course, course responsible
- DD3359: Reinforcement Learning (2017, 2018), KTH Royal Institute of Technology, PhD.-level course, lecturing and course management
- DT2359: Artificial Intelligence (2012, 2013, 2014, 2015), KTH Royal Institute of Technology, Master-level course, lecturing and tutoring