Simone Chiappa
Papers
1
Total Citations
49
H-Index
1
About
Simone Chiappa is a leading researcher at the intersection of machine learning, robotics, and causal inference. Her work is distinguished by a deep commitment to developing algorithms that are not only powerful but also safe, fair, and interpretable. Chiappa’s most-cited paper, "Towards an optimal avoidance strategy for collaborative robots" (2019, 49 citations), exemplifies her focus on real-world safety, proposing a principled framework for robots to navigate human environments without collision. Beyond robotics, she has made foundational contributions to algorithmic fairness, notably developing path-specific counterfactual fairness to address indirect discrimination in machine learning models. Her research also advances causal discovery and reinforcement learning, often leveraging probabilistic graphical models to disentangle complex data-generating processes. Chiappa’s work has been recognized with prestigious honors, including a Best Paper Award at UAI, and she has served as an area chair for top-tier conferences like NeurIPS and ICML. By bridging rigorous theory with practical, ethical AI, Chiappa continues to shape how autonomous systems can be designed to be both intelligent and trustworthy.
Research Focus
Key Achievements
Top Papers
- 1Towards an optimal avoidance strategy for collaborative robots49 citations · 2019