People
Martin Mundt (he/him)
OWLL Group Leader
Email: martin.mundt
_at_ tu-darmstadt.de
Martin is the OWLL research group leader at Hessian.AI and TU Darmstadt. He is also a board member of directors at the non-profit organization ContinualAI, was the Diversity & Inclusion chair at AAAI-24 and currently serves as Review Process Chair for CoLLAs 2024.
He was previously a postdoctoral researcher at the AI&ML lab at TU Darmstadt. He holds a PhD in computer science from Goethe University Frankfurt (2021), for which he has received a thesis award, prior to which he has completed a Bachelor’s (2013) and Master’s (2015) degree in physics.
PhD Students
Roshni Kamath (she/her)
Email: roshni.kamath
_at_ tu-darmstadt.de
Roshni Kamath is currently a PhD student in the OWLL Lab at the Computer Science Department of the TU Darmstadt & hessian.AI. Previously, she worked as a Research Associate and AI Consultant at Forschungs-zentrum Jülich. She worked as a Software Engineer before pursuing her Masters in Artificial Intelligence from Katholieke Universiteit (KU) Leuven.
Subarnaduti Paul
(he/him)
Email: subarnaduti.paul
_at_ tu-darmstadt.de
Subarnaduti Paul decided to follow his passion for research by joining the OWLL Lab as a Ph.D. student after successfully graduating from TU Munich in the summer of 2022. His field of expertise lies in Electronic Systems & AI. Previously, he was working as a Research Intern for the Innovation Lab at Bosch Rexroth. His Thesis was able to propose reliable solutions that can integrate deep learning into traditional industrial processes. He will bring his previous experiences to instill a new picture in the paradigm of Open World Learning.
Research Assistants
- Qi Li: Research assistant in 2023-2024 for project “CAIMAN: Continual Artificial Intelligence Models for Atmospheric Convection in Subtropical Regions“
Former members
- Robin Menzenbach: Master thesis: “Self-Expanding Variational Autoencoders“, completed in March 2024. Former teaching assistant in winter 2022/23
- Nick Lemke: Master thesis: “Distribution-Aware Replay for Continual MRI Segmentation“, co-supervised with Anirban Mukhopadhyay – GRIS TU Darmstadt, completed in March 2024
- Patrick Vimr: Master thesis: “Continual Causal Knowledge Distillation“, completed in December 2023
- Aleksandar Tatalovic: Bachelor thesis: “Continual Reinforcement Learning by Merging Models“, completed in October 2023
- Tobias Gockel: Master thesis, “Knowledge Distillation for Continual Learning in Sum Product Networks“, completed in September 2023
- Pranav Sureshkumar: Summer intern 2023 – DAAD WISE scholarship
- Uranik Berisha: Master thesis, “Progressive Probabilistic Circuits“, completed in May 2023
- Laura Boyette: Master thesis, “Deep Continual Learning with Intentional Forgetting“, completed in May 2023
- Zhanke Liu: Master thesis “Self-supervised Learning for Financial Time-Series Prediction via Transformers“, completed in April 2023
- Dhruvin Vadgama: teaching assistant for continual machine learning course tutorials, winter semester 2022/23
- Yves Neyraud: Master thesis “Active Latent Space Packing for Variational Open World Learning“, completed in February 2022
- Jesse-Jermaine Richter: Master thesis “Continual Learning with Dataset Distillation“, completed in October 2022 (co-supervised with Kristian Kersting)
- Sebastian Seer: Master thesis “Learning Neural Network Latent Space Distributions with Probabilistic Circuits to Address the Overconfidence Challenge” (co-supervised with Kristian Kersting), completed in July 2022
- Lars-Joel Frey: Bachelor thesis “Towards Unsupervised Federated Continual Machine Learning” (co-supervised with Kristian Kersting), completed in June 2022