Osman Ali Mian

IKIM - the Institute for Artificial Intelligence in Medicine

Previously CISPA Helmholtz Center For Information Security

Email: [fullname] [at] outlook [dot] com

About

My research is about causal discovery and inference, and to reason how it can be used to make machine learning robust. I work on inventing privacy-preserving, federated causal discovery algorithms under mild assumptions such that these methods can be applied to real-world scenarios. You can view my CV, last updated in March 2025, here.

News

[28-Feb-2025] 🎉🎉 I successfully defended my Ph.D. thesis titled 'Practically Applicable Causal Discovery' with distinction Magna Cum Laude. The promotion committee, consisted of Profs. Raimund Seidel, Murat Kocaoglu, Isabel Valera, and Jilles Vreeken. You can read the thesis here. 🎉🎉
[01-Dec-2024] I have started in a new role as Post Doctoral Researcher at Trustworthy Machine Learning group at IKIM – Institute for Artificial Intelligence in Medicine in Essen.
[17-May-2024] Our work on causal discovery from continually arriving episodic data was accepted at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2024.
[27-Mar-2024] I will give a talk at the Trustworthy Machine Learning group at IKIM – Institute for Artificial Intelligence in Medicine in Essen on 15-Apr-2024.
[22-Mar-2024] I will give a talk at CAUSE Junior Researcher Day Spring 2024 at Technical University of Munich (TUM) on 11-Apr-2024.
[03-Jan-2024] Our work on causal discovery from episodic data was accepted at The Fourth Workshop of Artificial Intelligence for Time Series Analysis (AI4TS) at AAAI 2024.
[20-Dec-2023] Our work on continual learning of causal networks was accepted for oral presentation at The Second AAAI Bridge Program on Continual Causality at AAAI 2024.
[25-Apr-2023] I will be attending AISTATS 2023 in Valencia, Spain to present, PERI, our proposed approach for Federated Causal Discovery.
[22-Feb-2023] I gave a talk at the Causality Discussion Group where I presented ORION, Our proposed approach for causal discovery and intervention detection over multiple environments. You can find the recorded talk here.
[21-Nov-2022] I will be working as an Applied Science Intern at Amazon from Dec 2022 until April 2023. The internship will be about applying Causal Learning to Natural Language Understanding.
[02-Sep-2022] I had a chance to talk about my work on causal machine learning in TL;DR, CISPA's first podcast series. You can stream the podcast here.

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