Babak Salimi, assistant professor in the Halıcıoğlu Data Science Institute, will present "Post-hoc Explanations for ML Models Using Contrastive Counterfactuals."
Babak Salimi is an assistant professor in the Halıcıoğlu Data Science Institute (HDSI) and affiliated with the Department of Computer Science and Engineering at University of California, San Diego. Before joining UC San Diego, he was a postdoctoral research associate in the Department of Computer Science and Engineering, University of Washington, where he worked with Prof. Dan Suciu and the database group. He received his Ph.D. from the School of Computer Science at Carleton University, advised by Prof. Leopoldo Bertossi. His research seeks to unify techniques from theoretical data management, causal inference and machine learning to develop a new generation of decision-support systems that help people with heterogeneous background to interpret data. His ongoing work in causal relational learning aims to develop the necessary conceptual foundations to make causal inference from complex relational data. Further, his research in the area of responsible data science develops needed foundations for ensuring fairness and accountability in the era of data-driven decisions. His research contributions have been recognized with a Research Highlight Award in ACM SIGMOD, a Best Demonstration Paper Award at VLDB and a Best Paper Award in ACM SIGMOD.
Meeting ID: 813 8190 4325
The Responsible Data Science and AI Speaker Series discusses topics such as explainability, reproducibility, biases, data curation and governance, and privacy. The series is co-organized by Associate Professor Jana Diesner and Assistant Professor Nigel Bosch at the iSchool at Illinois and hosted by the iSchool's Center for Informatics Research in Science and Scholarship (CIRSS).
This event is sponsored by Center for Informatics Research in Science and Scholarship