Hi there! 
I am a post-doctoral researcher in statistical learning at the Rational Intelligence Lab (ri-lab.org) within the CISPA Helmholtz Center for Information Security in Saabrücken, Germany. I am also affiliated the Department of Statistics at Ludwig-Maximilians-Universität (LMU) Munich, where I obtained my PhD in statistics under the advisorship of Thomas Augustin.
My research broadly revolves around uncertainty quantification, online learning (theory), and decision theory within machine learning. I try to render machine learning more reliable by representing the involved uncertainties, heavily relying on imprecise probabilities. I am also interested in interpretable machine learning and anything Bayesian. My first- (and co-)authored research has been published in Q1 journals like Knowledge-Based Systems, TMLR, (Machine Learning) and A*/A conferences like NeurIPS, ICML, ICLR, UAI, ECML-PKDD, (ACL, EMNLP).
I enjoy teaching a lot and teach several (under)graduate classes at our department. I also (co-)supervise bachelor and master theses. Potential thesis topics under my supervision can be found here.
I am part of the the Graduate Center of the Bavarian Research Institute for Digital Transformation (bidt) within the Bavarian Academy of Sciences (BAS). The graduate center is a great place to learn about the many facets of the digital world that are beyond my own research. Moreover, I am supported by the mentoring program of the Faculty of Mathematics, Computer Science and Statistics at LMU Munich. My mentor is Professor Konstantinos Panagiotou. Parts of my research are further funded by the Federal Statistical Office of Germany within the cooperation project “Machine Learning in Official Statistics”.
Great news: Our paper on “Self-Supervised Laplace Approximation for Bayesian Uncertainty Quantification” has been accepted to the Transactions on Machine Lea...
Great news: Our paper on “Self-Supervised Laplace Approximation for Bayesian Uncertainty Quantification” has been accepted to the Transactions on Machine Lea...
Happy to share our works on “Performative Learning Theory” and “Off-Policy Evaluation with Strategic Agents via Local Disclosure” has been accepted to ICML 2...
I am visiting the Stanford Trustworthy AI Research Lab (STAIR). I’ll present our work on empirical alignment and incentive-aware AI regulation – both motivat...
Our research on personalizing exosuits via interpretable Bayesian optimization was covered by Börsen-Zeitung, Germany’s main newspaper on financial markets.
I’m on my way to Porto to attend the European Conference on Machine Learning ECML-PKDD (Europe’s flagship conference on Machine Learning) in order to present...
Happy to share that today’s my first day at the Rational Intelligence (RI) Lab at CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. Th...
Our paper “GUARD: Glocal Uncertainty-Aware Robust Decoding for Effective and Efficient Open-Ended Text Generation” has been accepted to the findings track of...
Honored to receive the IJAR Young Researcher Award (Silver)
Happy to share that our collaboration with the Harvard SEAS Biodesign Lab has come to a successful end! Our paper “Explaining Bayesian Optimization by Shaple...
I’m presenting some work in progress at LUWSI, the 2nd edition of the workshop on Learning Under Weakly Structured Information (LUWSI) in Tübingen. Extremely...
I’m giving a talk at DAGStat, one of Germany’s major conferences on Statistics. I’ll present our paper on reciprocal learning on March 27 in session 21. Let ...
Pretty excited that both of my first-ever NeurIPS submissions got accepted, one of which as spotlight! This was a great team effort with Christoph Jansen, Ge...
Happy to share that our paper “Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text Generation” has been accepted for EMNLP 2024 Find...
I am spending this fall at Harvard University in Cambridge (MA, USA) to work with James Bailie and Xiao-Li Meng. We will investigate connections between onli...
I am giving a talk on reciprocal learning at the Seminar für Statistik (SfS), ETH Zürich on August 14th as part of the SfS-PhD Presentations. Drop me a messa...
Great news! Our paper “Imprecise Bayesian Optimization” has been accepted for publication in Knowledge-based Systems! This is joint work with my supervisor T...
Happy to share that the paper “Bayesian Data Selection” has been accepted at the 5th Workshop on Data-Centric Machine Learning (DMLR) at the International Co...
Our paper “Semi-Supervised Learning guided by the Generalized Bayes Rule under Soft Revision” has been accepted at the 11th International Conference on Soft ...
I will attend ICLR 2024 to present our paper “Partial Rankings of Optimizers”, which has been accepted at the ICLR 2024 Tiny Papers Track. Great collaboratio...
I am presenting our recent paper on explaining Bayesian Optimization by Shapley values at Integreat (Norwegian research center). The talk will be openly acce...
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...
Our paper “Partial Rankings of Optimizers” has been accepted for presentation at the International Conference on Learning Representations (ICLR) 2024 Tiny Pa...
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 ...
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...
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 ...
Looking forward to attending this year’s BAyesian Young Statisticians Meeting (BAYSM) hosted by the University of Connecticut, where my short paper has been ...
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...
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...
Thrilled to annouce that our papers “Approximately Bayes-Optimal Pseudo-Label Selection” and “Robust Statistical Comparison of Random Variables with Locally ...
Glad to share that our paper on robust pseudo-label selection was accepted for the 13th International Symposium on Imprecise Probabilities: Theories and Appl...
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...
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...
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...
Our paper “Accounting for Gaussian Process Imprecision in Bayesian Optimization” was accepted at the 9th International Symposium on Integrated Uncertainty in...
This site is currently under construction. Stay tuned for updates. You might also want to visit my LMU Website.