Ashok Srivastava is NASAís principal scientist for Data Mining and Systems Health Management, providing technical and programmatic leadership for two large research programs, and making substantial contributions in the field of aviation safety.
Since 2002, he has led the Intelligent Data Understanding group at NASA Ames Research Center and set the strategic direction of data mining within the agency. The group performs research and development of advanced machine learning and data mining algorithms in support of NASA missions.
From 2007 to 2010, he served as principal investigator of the Integrated Vehicle Health Management (IVHM) Project, an advanced technology project concerned with detection, diagnosis, prognosis, and mitigation of adverse events during aircraft flight. The project covered nearly 100 NASA employees and contractors, nearly 40 academic and industry partnerships, and two international partnerships, with a budget of approximately $120 million over five years.
He was recognized with the NASA Associate Administratorís Award for the IVHM Data Mining Team, as well as the IEEE Computer Society Technical Achievement Award for pioneering contributions to intelligent information systems. He also won a Top 10 Data Mining Case Study award from the IEEE Conference on Data Mining for his work in the applications of Data Mining to Aviation Safety.
He is a senior member of IEEE, and he has published more than 90 papers in peer-reviewed conferences and journals. His work ranges from fundamental algorithm development in data mining to well-developed, high-impact technologies.
Prior to joining NASA, he was senior director of analytic services at Blue Martini Software, where his responsibilities included management of PhD and MS-level analysts, group profitability, technical design of data mining studies, and development of new data mining algorithms for e-commerce systems.
From 1996 to 2000, he was a senior consultant for data mining analytical services at IBM. His responsibilities included research, design, and development of clustering and predictive models for applications in forecasting volatility, yield forecasting, and analysis of business-to-business corporate banking transactions.
He earned his bachelorís in electrical engineering at CU-Boulder in 1991, his masterís in 1993, and his PhD in 1996. He has fostered long-term collaborations with CUís Cooperative Institute for Research in Environmental Sciences and the Center for Environmental Technology in the Department of Electrical, Computer, and Energy Engineering.
He and his wife, Lynn Waelde, who received her PhD in psychology at CU-Boulder, live in Mountain View, California.