Involved in the development of the Responsible AI Dashboard, which was released to the open source community as of December 2021. The dashboard integrates several mature efforts developed as a collaboration between Microsoft Research Aether Committee and Azure Machine Learning. Main functionalities focus on debugging machine learning models and responsible decision-making. Also involved in various research initiatives that study the societal impact of artificial intelligence as well as various quality-of-service aspects of AI including interpretability, reliability, accountability, and fairness.
Research Experience
Currently a researcher in the Adaptive Systems and Interaction group at Microsoft Research. Her research work lies in the intersection of human and machine intelligence, aiming at improving current systems either with better debugging tools or by optimizing them for human-centered properties. Main research directions include: Debugging and Failure Analysis of AI/ML Systems, and Human-AI Collaboration.
Education
Completed her PhD degree at ETH Zurich (Switzerland) in 2016, advised by Prof. Donald Kossmann and Prof. Andreas Krause. Her doctoral thesis focuses on building cost and quality-aware models for integrating crowdsourcing in the process of building machine learning algorithms and systems. In 2011, she completed her master studies in computer science in a double-degree MSc program at RWTH Aachen University (Germany) and University of Trento (Italy).
Background
AI/ML researcher working on ML Reliability, Robustness, and Human-AI Collaboration. Interests include Artificial Intelligence, AI & Society, Machine Learning, Systems, Human-AI collaboration, Reliable AND Accountable AI, Software Engineering for ML, Crowd Collective Intelligence.
Miscellany
Personal interests include traveling, having visited places like Albania, Washington State, and Zurich.