Karin Murthy is a manager and research staff member at IBM's T. J. Watson Research Center. Her expertise is in information management and analytics. She is a member of IBM's Academy of Technology.
Karin currently leads the Yorktown Think Lab where she is responsible for delivering extraordinary client experiences: connecting clients to IBM researchers and their work and helping clients envision how IBM can help them transform the way they do business.
In 2018 Karin co-lead the 2019 Global Technology Outlook (GTO). The GTO is IBM Research's vision of the future of IT, highlighting emerging and disruptive technology trends, markets, and business models.
From 2013 to 2017 Karin was part of the Services Research department working on improving IT service delivery tools and processes through analytics and cognitive technologies. She co-lead the Cognitive Delivery Insights platform, a key component of GTS’s IBM Services Platform with Watson. Her work resulted in a corporate award, five outstanding technical achievement awards, and a research division award.
Prior to joining Watson, Karin spent five years at IBM Research in India where she worked primarily on bridging the gap between structured and unstructured information to allow joint analysis. For example, she developed solutions to make Master Data Management (MDM) content-aware. Specifically, Karin was the technical lead for developing research technology into IBM InfoSphere MDM Extension for Unstructured Text Correlation released in June 2013. Her work received an outstanding technical achievement and a research division award.
Between 2005 and 2008, Karin was at IBM's Almaden Research Center in the US where she worked on next-generation RFID data management. Next to conducting research on efficient query processing, data mining, and data privacy, she has co-developed Theseos query middleware to enable the sharing of RFID data across independent organizations. Her work has contributed to several IBM products and solutions.
Karin received her Ph.D. degree in computer science from the University of Munich in Germany in 2004. Her dissertation research focused on similarity search and data mining for complex objects. She has published in international conferences and journals. She has also been a reviewer, program committee member, and general chair for international journals, conferences, and workshops. She has taught various subjects in computer science to both graduate and undergraduate students and supervised projects and dissertations.