معرفی
H. V. Jagadish serves as the Edgar F Codd Distinguished University Professor and Bernard A Galler Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan's College of Engineering. He directs the Michigan Institute for Data Science (MIDAS) and leads the NSF-funded Framework for Integrative Data Equity Systems (FIDES), following a career that included heading AT&T Labs' Database Research Department prior to joining Michigan in 1999.
His academic foundation includes a Ph.D. from Stanford University, with prior appointments at AT&T Labs and the University of Illinois.
Research spans database systems, data management, and data science, emphasizing data integration across heterogeneous sources and usability for non-technical users through schema design, natural language querying, and analytics with missing data. Current work focuses on equity, ethics, and fairness in AI, developing methods to identify and mitigate data inequities while ensuring societal benefits of data science. His white papers and National Academies presentations have shaped big data research agendas.
Major honors include:
- Fellow of the ACM (2003)
- Fellow of the AAAS (2018)
- ACM SIGMOD Contributions Award (2013)
- David E Liddle Research Excellence Award (2008)
- Stephen S. Attwood Award
- Distinguished Faculty Award from the University of Michigan (2019)
He has secured multiple NSF grants (IIS 0741620, IIS 1017296, IIS 1250880, 1741022, 1934565) supporting database usability and data equity research, mentored numerous graduate students, and created the widely adopted Data Science Ethics MOOC available on EdX, Coursera, and FutureLearn. His h-index of 96 reflects 200+ major publications and 38 patents.
As MIDAS Director, he oversees university-wide data science initiatives while leading the EECS database research group and formerly directing the Software Systems Laboratory. His FIDES institute remains central to developing equitable data systems, with ongoing work expanding into AI policy frameworks.
