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MSIROM: Business Analytics | Industry Involvement

About the Judges

Rob High

Rob High is an IBM Fellow, Vice President and Chief Technology Officer, Watson Solutions, IBM Watson Group. He has overall responsibility to drive Watson technical strategy and thought leadership. As a key member of the IM Watson Group Leadership team, Rob works collaboratively with the Watson engineering, research, and development teams across IBM.

Prior to joining the Watson Solutions team, Rob was Chief Architect for the SOA Foundation and member of the IBM Academy of Technology, Rob championed an open industry architectural definition of the principles of business and IT alignment enabled by SOA and Business Process Optimization, as well as ensuring IBM's software and services portfolio is architecturally grounded to enable for efficient SOA-based solutions. This responsibility extended across the IBM software portfolio, including WebSphere, Rational, Tivoli, Lotus, and Information Management offerings.

Rob has 37 years of programming experience and has worked with distributed, object oriented, component-based transaction monitors for the last 26 years, including SOMObject Server, Component Broker, and the WebSphere Application Server. Rob previously served as Chief Architect for the WebSphere foundation with architectural responsibility for the WebSphere Application Server and the related products integrated on that core run time.

Salil Ahuja
Salil Ahuja is a Senior Product Manager in The IBM Watson Group. He has been working in the IT industry for over 12 years in a variety of positions ranging from development to client services. He spends majority of his time building innovative products that change trends and establish new markets. As a Senior Product Manager at IBM, he is focused on commercializing Watson and transforming the way information works for us. Salil Ahuja lives in Austin, Texas. In his spare time he enjoys the outdoors, theater and playing or watching basketball whenever possible. He can be contacted on LinkedIn.

 

Joydeep Ghosh

Joydeep Ghosh is currently the Schlumberger Centennial Chair Professor of Electrical and Computer Engineering at the University of Texas, Austin. He joined the UT-Austin faculty in 1988 after being educated at IIT Kanpur, (B. Tech '83) and The University of Southern California (Ph.D’88). He is the founder-director of IDEAL (Intelligent Data Exploration and Analysis Lab) and a Fellow of the IEEE. Dr. Ghosh has taught graduate courses on data mining and web analytics every year to both UT students and to industry, for over a decade. He was voted as "Best Professor" in the Software Engineering Executive Education Program at UT. 

Dr. Ghosh's research interests lie primarily in data mining and web mining, predictive modeling / predictive analytics, machine learning approaches such as adaptive multi-learner systems, and their applications to a wide variety of complex real-world problems. He has published more than 300 refereed papers and 50 book chapters, and co-edited over 20 books. His research has been supported by the NSF, Yahoo!, Google, ONR, ARO, AFOSR, Intel, IBM, and several others. He has received 14 Best Paper Awards over the years, including the 2005 Best Research Paper Award across UT and the 1992 Darlington Award given by the IEEE Circuits and Systems Society for the overall Best Paper in the areas of CAS/CAD. Dr. Ghosh has been a plenary/keynote speaker on several occasions such as MICAI'12, KDIR'10, ISIT'08, ANNIE’06 and MCS 2002, and has widely lectured on intelligent analysis of large-scale data. He served as the Conference Co-Chair or Program Co-Chair for several top data mining oriented conferences, including SDM'13, SDM''12, KDD 2011, CIDM’07, ICPR'08 (Pattern Recognition Track) and SDM'06. He was the Conf. Co-Chair for Artificial Neural Networks in Engineering (ANNIE)'93 to '96 and '99 to '03 and the founding chair of the Data Mining Tech. Committee of the IEEE Computational Intelligence Society. He has also co-organized workshops on high dimensional clustering, Web Analytics, Web Mining and Parallel/ Distributed Knowledge Discovery. 

Dr. Ghosh has served as a co-founder, consultant or advisor to successful startups (Stadia Marketing, Neonyoyo and Knowledge Discovery One) and as a consultant to large corporations such as IBM, Motorola and Vinson & Elkins. 

Rajiv Garg

Rajiv Garg is an Assistant Professor of Information, Risk, and Operation Management at McCombs School of Business. He received his PhD from the School of Information Systems and Management at the Heinz College, Carnegie Mellon University. He received graduate degrees in Computer Science and Electrical Engineering, both from University of Southern California and an undergraduate degree in Electrical Engineering from Indian Institute of Technology, Banaras Hindu University in India. His research interests are on the intersection of economics, marketing, and information systems with a focus on digital, social and mobile platforms. Rajiv is a senior member of IEEE and has been serving on the board of various small corporations in the past decade. Rajiv’s research work has appeared in the MIS Quarterly (MISQ), Journal of Management Information Systems (JMIS) and various peer reviewed conference proceedings.