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. Alexander Hoyle

Dr. Alexander Hoyle

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natural language processing, computational social science, human-centered evaluation

Dr. Diane Duroux

Dr. Diane Duroux

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precision medicine, graph theory, recommender system, multimodal learning

Dr. Etienne Bamas

Dr. Etienne Bamas

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theoretical computer science, approximation algorithms, learning-augmented algorithms

Dr. Fanny Lehmann

Dr. Fanny Lehmann

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scientific machine learning, physics-based deep learning, high-performance simulation, Earth sciences

Dr. Georgios Kissas

Dr. Georgios Kissas

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

Gonçalo Guiomar

Dr. Gonçalo Guiomar

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synthetic cognition, computational neuroscience, reinforcement learning, large language models, external page generative art

Ido Hakimi

Dr. Ido Hakimi

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natural language processing, optimization, efficient machine learning systems

Dr. Marina Esteban

Dr. Marina Esteban

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precision medicine, probabilistic machine learning, explainability, mechanistic modelling, multimodal learning, cancer research

Yudi Dai

Dr. Karolina Ewa Stanczak

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natural language processing, alignment, AI safety

Mubashara Akhtar

Dr. Mubashara Akhtar

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natural language processing, vision-language reasoning, benchmarking & evaluation.

 

Dr. Neda Davoudi

Dr. Neda Davoudi

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multi-modal analysis, biomedical imaging, computer vision

Dr. Pei-Yu Wu

Dr. Pei-Yu Wu

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

Dr. Shkurta Gashi

Dr. Shkurta Gashi

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machine learning, ubiquitous computing, health monitoring, multimodal learning

 

Yudi Dai

Dr. Yudi Dai

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


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