Program Committee
Area Chair, RO-FoMo Workshop @ NeurIPS 2023: Workshop on Robustness of Few-shot and Zero-shot Learning in Foundation Models
Area Chair, TEACH Workshop @ ICML 2023: Workshop on Trustworthy, Enhanced, Adaptable, Capable and Human-centric Chatbots
Area Chair, RAI @ ICLR 2021: Workshop on Responsible AI
Program Committee, WCDMDE @ NeurIPS 2020: Workshop on Consequential Decision Making in Dynamic Environments
Program Committee, FAccTRec @ RecSys 2020: Workshop on Fairness, Accountability and Transparency in Recommender Systems
Reviewer: I regularly serve as a reviewer for conferences in the areas spanning Machine Learning | Data Mining | Information Retrieval
Invited Talks
Panelist on "AI Safety and Misinformation in LLMs" panel
WiNLP workshop, EMNLP 2023, Singapore, Dec 2023
Fairness without Demographics through Adversarially Reweighted Learning
Google Boulder, September 2021Fairness in Machine Learning: Challenges and Approaches
MSR Seminar Series @ Microsoft Research, Montreal, Canada, Dec 2020ML Fairness in Practice: Challenges and Approaches
Search Engine Meetup, Amsterdam, Netherlands, Nov 2020Operationalizing Individual Fairness for Algorithmic Decision Making
FACTS-IR @ SIGIR 2019, Paris, France, July 2019Fairness in Algorithmic Decision Making (Best Poster Award)
Women in Big Data 2019, Zurich, Switzerland, June 2019
Co-advising | Mentoring
Alexandru Tifrea (Ph.D. Intern at Google, ETH Zurich)
Yash Lal (Ph.D. Intern at Google, Stonybrook Uni.)
Anubrata Das (Ph.D. Intern at MPI, UT Austin)
Ayan Majumdar (M.Sc. Thesis, Saarland Uni.)
Radu Marginean (M.Sc. Intern, Uni. Zagreb)
Teaching
Guest Lecture on Fairness in Machine Learning, Machine Learning Course, Google Tech Exchange 2023
Teaching Assistant, Human Centered Machine Learning, Saarland University, Germany, Winter 2018-2019
Teaching Assistant, Information Retrieval and Data Mining, Saarland University, Germany, Winter 2017-2018
Teaching Assistant, Machine Learning and Data Mining, Aalto University, Finland, Autumn/Spring 2016-2017