Member role: PhD Student

I am an ELLIS PhD student in the Medical Image Computing department at the German Cancer Research Center (DKFZ). Before starting my PhD, I worked as a Junior Data Scientist at AstraZeneca in Gothenburg (Sweden) and as a Research Assistant at Uppsala University.

My current research focuses on improving model generalizability across clinical settings, with a particular emphasis on brain imaging. I am developing a stroke identification algorithm designed to perform robustly in multi-centric environments. I am also collaborating with the University of Amsterdam on analyzing temporal brain image data to extract patterns that enhance model generalization.

I have received several travel grants for international research stays during my PhD, as well as excellence scholarships during my Bachelor’s and Master’s studies.

I am currently a PhD student in the group of Fred Hamprecht at the Interdisciplinary Centre for Scientific Computing (IWR) of Heidelberg University. My background is physics and I am primarily interested in how we may use our intuition and tools from theoretical physics to understand and improve machine learning methods. I first became interested in this during my masters thesis where (among other things) I worked on a grand canonical MCMC sampling algorithm for inference problems. [1] In my PhD, I am working on inference problems on manifolds particularly the simplex (ie inference problems where the parameters are distributions themselves). The physical methods we use mostly stem from differential geometry (as in general relativity and information geometry) and our applications are also in physics, namely cosmology.

Iza is a PhD student at Saarland University. Her research lies at the intersection of natural language processing and computational psycholinguistics. She explores how language models can both implement and inform theories of human language processing. Her work examines correlations between model behavior (e.g., word probabilities) and human data such as eye movements during reading.

I am a PhD student of the ELIZA Zuse School in Berlin, where I am working with Frank Noé and Klaus-Robert Müller on AI4Science. My research focuses on generative models for dynamical biophysical systems. I also just love geeking out about all things computer science — from machine learning and physics to weird algorithms and cool hacks.

I am a third year ELLIS Ph.D. at TU Darmstadt (UKP Lab), Germany and the University of Cambridge, UK. I am supervised by Prof. Iryna Gurevych and Prof. Anna Korhonen. My research interests lie at the intersection of NLP and ML. Specifically, I am interested in:
– Cross-lingual generalization (e.g., plasticity, early period of training, memorization vs generalization, spurious correlations etc.)
– Culturally aware and adapted NLP
– Multimodality
Previously, I studied at the University of Toronto, where I obtained both of my undergraduate and master’s degrees. My master’s research was under the supervision of Prof. Brendan Frey (PSI Lab, Toronto ML Group). I have been working in the industry for nearly a decade in the domain of NLP before I went back to school. I worked at Canadian start-ups like Meta (acquired by CZI), Wattpad (acquired by NAVER WEBTOON), and ElementAI.

Nick Heppert is a Doctoral Researcher at the University of Freiburg, part of ELLIS and an ELIZA Fellow since March 2024. His research focuses on robot learning, with an emphasis on perception for robotic manipulation. He holds an M.Sc. in Autonomous Systems from TU Darmstadt and has conducted research at Stanford University and the Toyota Research Institute. His most influential publication, “CARTO: Category and Joint Agnostic Reconstruction of ARTiculated Objects” (CVPR 2023), addresses generalizable 3D perception of articulated objects for robotics. He has published at top robotics and machine learning conferences, including IROS, ICRA, CVPR, and CoRL. Nick actively contributes to the research community as a reviewer for RA-L, ICRA, and IROS, and through organizing academic workshops. He has also mentored over 10 Master’s students at the University of Freiburg. His work aims to bridge perception and manipulation to enable more capable and adaptable robotic systems. He is also part of the interdisciplinary ReScaLe project, which focuses on developing responsible and scalable learning for robots assisting humans, with particular attention to social impact and regulatory dimensions.

I am an ELLIS PhD student supervised by Dieter Büchler (University of Alberta, Max Planck Institute for Intelligent Systems), Ingmar Posner (University of Oxford), and Bernhard Schölkopf (Max Planck Institute for Intelligent Systems). My research interests generally lie in reinforcement learning and robotics. More concretely, I am interested in the role of action representations in reinforcement learning, discovering and exploiting structure in the learning process, and applying reinforcement learning to muscular robots for solving dynamic tasks.