PhD Students I Co-Advise/d, and Work/ed with:

Makram Chahine – PhD Student, Computer Science, CSAIL MIT. 9/2021 – Present
Topic: Understanding Memory in Deep Learning

Tsun-Hsuan Wang – PhD Student, Computer Science, CSAIL MIT. 11/2020 – Present
Topic: Liquid Networks for Causality and Interactions in Multi-agent Systems

Noel Loo – PhD Student, Computer Science, CSAIL MIT. 10/2021 – Present
Topic: Robust Decision-Making by Kernel Methods

Aaron Ray – PhD Student, Computer Science, CSAIL MIT. 3/2021 – 5/2022
Topic: Liquid Networks for End-to-end Causal Navigation

Lucas Liebenwein – PhD Student, Computer Science, CSAIL MIT. 1/2020 – 1/2022
Topic: Understanding Continuous-Depth Neural Models

Alexander Amini – PhD Student, Computer Science, CSAIL MIT. 1/2018 – Present
Topic: Liquid Networks for End-to-end Autonomy

Mathias Lechner – PhD Student, Computer Science, IST Austria. 10/2017 – Present
Topic: Liquid Networks and Understanding Recurrent Neural Networks

Zahra Babaei – PhD Student, Computer Science, TU Wien. 1/2020 – Present
Topic: Brain-inspired Deep Learning Architectures

Daniel Pasterk – PhD Student, Computer Science, TU Wien. 1/2020 – 5/2022
Topic: Learning with Convergence Guarantees

Sophie Gruenbacher – PhD Student, Computer Science, TU Wien. 1/2020 – Present
Topic: Verification of Continuous-time Neural Models

Luigi Berducci – PhD Student, Computer Science, TU Wien. 5/2020 – 11/2020
Topic: Model-based Deep RL for Autonomous Racing

Axel Brunnbauer – PhD Student, Computer Science, TU Wien. 4/2020 – 11/2020
Topic: Model-based and Model-free Deep RL for Autonomous Racing

MSc & BSc Students I supervise/d:

Patrick Kao – M.Eng. in Computer Science at MIT, Sep 2021 – May 2022
Topic: Decision-making with Continuous Depth Models

Ryan Shubert – M.Eng. in Computer Science at MIT, Jun 2021 – May 2022
Topic: Multi-agent RL with continuous-depth models

Nicole Stiles – B.Sc. in Computer Science at MIT, Feb 2021 – Oct 2021
Topic: Scaling density estimation with Neural ODEs

Catherine Zhang – B.Sc. in Computer Science at Harvard, Aug 2020 – Nov 2021
Topic: Reinforcement Learning with Transformers

Jordan E. Docter – B.Sc. in Computer Science at MIT, Aug 2020 – April 2021
Topic: Robot learning with Transformers

Charles Vorbach – B.Sc. in Computer Science at MIT, Jul 2020 – May 2021
Topic: Learning continuous-time neural controllers for drone navigation

William Chen – B.Sc. in Computer Science at MIT, Aug 2020 – Mar 2021
Topic: End-to-end Multi-agent Drone navigation

Hannes Barntner – M.Sc. in Computer Engineering at TU Wien, Oct 2020 – Mar 2021
Thesis Topic: Learning long-term dependencies by continuous-time models

Axel Brunnbauer – M.Sc. in Computer Engineering at TU Wien, Jul 2020 – Jul 2021
Thesis Topic: Real-world model-based reinforcement learning

Stefan Sietzen – M.Sc. in Visual Computing at TU Wien, Jan 2020 – Present
Thesis Topic: Robustness analysis in deep learning models

Mathias Lechner – M.Sc. in Computer Engineering at TU Wien, Oct 2016 – Oct 2017
Thesis Title: Brain-inspired Neural Control
Won the Best Thesis Award at TU Wien’s Faculty of Informatics
Now: Ph.D. student in Machine Learning at IST Austria

Marc Javin – M.Sc. in Computer Engineering at TU Wien, Feb 2018 – Nov 2018
Thesis Title: A Hybrid Optimization suite for Biologically-inspired Neuronal Circuits
Now: Deep Learning Engineer at emotion3D

David Lung – M.Sc. in Computer Engineering at TU Wien, Jan 2017 – Dec 2018
Thesis title: OpenWorm: Design and Evaluation of Neural Circuits on the Virtual Worm, C. elegans
Now: Ph.D. student in bio-inspired machine learning at TU Wien

Bernhard Müllner – M.Sc. in Computer Engineering, TU Wien, Nov 2018 – Oct 2019
Thesis title: Better end-to-end object detection in low SNR environments with Time-of-Flight Cameras
Now: Software Engineer at BECOM Systems GmbH

Magdalena Fuchs – M.Sc. in Biomedical Engineering at TU Wien, Jan 2017 – Jun 2018
Thesis Title: Principles of Learning and Memory in the Nervous System of C. elegans
Now: Product Development Engineer at Lohmann & Rauscher

Ondrej Balún – M.Sc. in Computer Engineering, TU Wien, Dec 2015 – Jan 2017
Thesis Title: Towards Distributed Controllers Based on C. elegans Locomotory Neural Network
Now: IAM Expert Group Lead at Ventum Consulting

Zahra Babaei – B.Sc. in Computer Engineering at Sharif University of Technology, Jul 2018 – Oct 2018.
Internship Project: Deep learning for brain data,
Now: Ph.D. student at TU Wien

Julian Posch – B.Sc. in Physics, Universität Wien, Mar 2019 – Sep 2019
Internship Project: What happens inside a Neural network
Now: Machine Learning M.Sc. student at University of Amsterdam

Benjamin Kulnik – B.Sc. in Electrical Eng. at TU Wien, Oct 2017 – Feb 2018
Thesis Title: A Grid-Search Algorithm for Selecting the Optimal Structure in Deep Neural Networks
Now: Master student at TU Wien, AI Engineer at Infineon Austria