I'll be joining the Research Center for Trustworthy Data Science and Security at TU Dortmund as a Professor to start the Causality Group this summer.

Until then, I am a Postdoctoral Researcher in the Computational Biology Group at ETH Zürich, and a member of the ELLIS society and the Swiss Institute for Bioinformatics (SIB). My research focuses on causality, information theory, and representation learning to approach modern challenges in the medical and biological domain. Prior to my current position, I was a Postdoc-Fellow at the ETH AI Center and part of the Medical Data Science Group. I did my PhD in the Exploratory Data Analysis group affiliated with the CISPA Helmholtz Center for Information Security and the Max Planck Institute for Informatics.

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I am actively searching for PhD students. Feel free to reach out! More details are provided here.

News

• (Feb 2024) Accepted poster at RECOMB on "Gene-level Inference of Regulatory effects As Factorization of Function of Expressions" or short GIRAFFE.
• (Jan 2024) Or submission "Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning" has been accepted to ICLR'24.
• (Jan 2024) I joined the Computational Biology Group led by Niko Beerenwinkel!
• (Nov 2023) Our work "Blood Glucose Forecasting from Temporal and Static Information in Children with T1D" has been accepted for publication at Frontiers in Pediatrics.
• (Nov 2023) Selected to be among the top reviewers at NeurIPS'23.
• (Oct 2023) New preprint "The Mixtures and the Neural Critics: On the Pointwise Mutual Information Profiles of Fine Distributions" is available!
• (Sep 2023) Two papers got accepted to NeurIPS'23: 1) "Beyond Normal: On the Evaluation of Mutual Information Estimators", and 2) "Effective Bayesian Heteroscedastic Regression with Deep Neural Networks".
• (Apr 2023) Our paper "On the Identifiability and Estimation of Causal Location-Scale Noise Models" got accepted to ICML'23.
• (Mar 2023) Our paper "3DIdentBox: A Toolbox for Identifiability Benchmarking" got accapted to the dataset track at CLeaR'23
• (Feb 2023) I received an AISTATS'23 Reviewer Award (awarded to top 10% best reviewers).
• (Jan 2023) Our submission "Identifiability Results for Multimodal Contrastive Learning" got accepted to ICLR'23.

For more updates access the news arxiv.

Activities

Reviewing for Conferences & Journals

• Reviewer for the Conference on Neural Information Processing Systems (NeurIPS'23 [Top 10% Reviewer Award])
• Reviewer for the International Conference on Machine Learning (ICML'22,23,24)
• Reviewer for the International Conference on Artificial Intelligence and Statistics (AISTATS'21,22 [Top 10% Reviewer Award],23[Top 10% Reviewer Award],24)
• PC Member for the SIAM International Conference on Data Mining (SDM'21)
• PC Member for the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'21)
• Reviewer for the Machine Learning for Health Symposium (ML4H'22,23)
• Reviewed for the journal Data Mining and Knowledge Discovery (DAMI'22)
• Reviewed for the journal IEEE Access in 2020
• Reviewer for the IEEE International Symposium on Information Theory (ISIT'19,20)
• PC Member for the workshops AAAI-ITCI'22 and NeurIPS-TS4H

Invited Talks

• Neuro-Mechanistic Modeling group, DFKI Saarbrücken, 2023
• Faculty of Business and Economics, University of Lausanne, 2023
• Statistical Colloquium, TU Dortmund, 2023
• Tutorial at Machine Learning Summer School in Healthcare and Biosciences, 2022
• Data Mining reading group, TU Eindhoven (virtual), 2020
• CWI Machine Learning Seminar, CWI Amsterdam, 2019
• Explanatory Data Analysis group, Leiden University, 2019