Talk on ShapleyBO at Integreat, April 30th, 14.15 CET
I am presenting our recent paper on explaining Bayesian Optimization by Shapley values at Integreat (Norwegian research center). The talk will be openly acce...
Hi there! 
I am a 3rd year PhD Candidate supervised by Thomas Augustin at the Department of Statistics at Ludwig-Maximilians-Universität (LMU) Munich. My research revolves around adaptive machine learing and online learning. I try to render such methods more reliable by representing the involved uncertainties, heavily relying on imprecise probabilities and borrowing from interpretable ML sometimes.
My position is partly funded by the Federal Statistical Office of Germany within the co-operation project “Machine Learning in Official Statistics” and I am part of the the Graduate Center of the Bavarian Research Institute for Digital Transformation (bidt) within the Bavarian Academy of Sciences (BAS).
I also teach several (under)graduate classes at our department and co-supervise bachelor and master theses. Potential thesis topics under my supervision can be found here. Besides, I do academic student counselling for our Bachelor program “Statistics and Data Science”.
Recent posts
1st Workshop on ML under Weakly Structured Information
Our group is organizing a workshop on Machine Learning under Weakly Structured Information at LMU on May 3 and 4. We are looking forward to talks by great sp...
Tiny Paper Accepted at ICLR Track 
Our paper “Partial Rankings of Optimizers” has been accepted for presentation at the ICLR 2024 Tiny Papers Track. Great collaboration with Hannah Blocher (eq...
Attending WUML in Munich 
I will attend the Workshop on Uncertainty in Machine Learning (WUML) in Munich, organized by Eyke Hüllermeier’s Chair. If you are also attending and want to ...
Paper Published in Machine Learning
Our paper “Learning De-Biased Regression Trees and Forests from Complex Samples” has been published in Machine Learning. The paper got accepted at the journa...
Talk and Poster at ACML 2023 in Istanbul
I will give a talk and present a poster on our recent work on de-biased regression trees and random forests at the 15th Asian Conference on Machine Learning ...
Giving a Talk at BAYSM
Looking forward to attending this year’s BAyesian Young Statisticians Meeting (BAYSM) hosted by the University of Connecticut, where my short paper has been ...
Talk at KI 2023 in Berlin
Giving a talk on our recent work on Bayesian pseudo-label selection at the 46th German Conference on Artificial Intelligence (KI 2023) in Berlin. See the con...
Poster at AABI
Our poster on how to select pseudo-labels in a Bayesian way (paper @UAI) was accepted for the Fifth Symposium on Advances in Approximate Bayesian Inference A...
Two Papers Accepted at UAI
Thrilled to annouce that our papers “Approximately Bayes-Optimal Pseudo-Label Selection” and “Robust Statistical Comparison of Random Variables with Locally ...
Paper Accepted at ISIPTA
Glad to share that our paper on robust pseudo-label selection was accepted for the 13th International Symposium on Imprecise Probabilities: Theories and Appl...
Will Join the Graduate Center at Bavarian Academy of Sciences 
Thrilled to annouce that I will become a fellow at the graduate center by the Bavarian Research Institute for Digital Transformation (bidt) within the Bavari...
Talk in Young Statisticians Lecture Series by IBS Early Career Group
I will give a talk on “Learning Under Weak Supervision: Some Insights From Decision Theory” as part of the Young Statisticians Lecture Series organized by th...
Paper Accepted at SUM
Very happy to share that our paper on cautious superset learning with applications to election polls was accepted for the 15th International Conference on Sc...
Paper Accepted at IUKM
Our paper “Accounting for Gaussian Process Imprecision in Bayesian Optimization” was accepted at the 9th International Symposium on Integrated Uncertainty in...
Under Construction
This site is currently under construction. Stay tuned for updates. You might also want to visit my LMU Website.