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Madhav’s research focuses on improving decision-making in the wild for analysis of high-dimensional data by designing novel methods that integrate human and model expertise in real-time. His work emphasizes relation-discovery, revealing intricate patterns and connections to provide valuable insights. His research has contributed to publishing systems that enhance interoperability in open research data and provide understanding into cause and effect of policy-making decisions.
Madhav has completed his Masters in Computer Science with a focus in Data Science from the University of Zurich. His research interests span the area of applied machine learning, human-centered artificial intelligence (HCAI), and big data analytics.