Post-Doctoral Fellows

Post-Docs that are listed here are recipients of the highly competitive ETH AI Center Post-Doctoral Fellowship. They are focused on advancing interdisciplinary AI research and are connected with two or more research groups of the ETH AI Center.

Dr. Anna Susmelj

More details

representation learning, self-supervised learning, domain generalisation, domain adaptation, causality, biomedical imaging, computer vision

Dr. Benjamin Moseley

More details

scientific machine learning, physics-informed neural networks, differential equations

Dr. Carmen Amo Alonso

More details

natural language processing, control theory, autonomous systems

Dr. Christina Tsalicoglou

More details

3D computer vision, scientific machine learning, data-driven modeling, physics-informed neural networks

Dr. Diane Duroux

More details

precision medicine, graph theory, recommender system, multimodal learning

Dr. Etienne Bamas

More details

theoretical computer science, approximation algorithms, learning-augmented algorithms

Dr. Francis Engelmann

More details

3D scene understanding, 3D semantic instance segmantation, 3D object detection, 3D computer vision

Dr. Georgios Kissas

More details

scientific machine learning, operator learning, data-driven model discovery, precision medicine

Dr. Ido Hakimi

More details

natural language processing, optimization, efficient machine learning systems

Dr. Neda Davoudi

More details

multi-modal analysis, biomedical imaging, computer vision

Dr. Shkurta Gashi

More details

machine learning, ubiquitous computing, health monitoring, multimodal learning

Dr. Pei-Yu Wu

external page More details

multimodal learning, explainable AI , data mining, building stock analysis

Dr. Yudi Dai

More details

3D Computer Vision, scene mapping, scene-aware 4D human motion capturing， human-scene interaction reconstruction

Post-​​Doctoral Fellows

Post-Doctoral Fellows