Prof. Vasudeva Varma is the head of Language Technologies Research Centre (LTRC), IIIT Hyderabad. He has served as the Dean (Research & Development), IIIT-H, and as the CEO of IIIT Hyderabad Foundation, one of the largest technology incubators in India that also managed IIIT-H's Intellectual Property and technology transfers. He has also co-founded Veooz Labs Pvt. Ltd., a social signal-based content discovery platform with social media search and analysis capabilities. He obtained his Ph.D. from the Department of Computer and Information Sciences at the University of Hyderabad in 1996. Prior to joining IIIT Hyderabad in 2002, he was the president of MediaCognition India Pvt. Ltd and Chief Architect at MediaCognition Inc. (Cupertino, CA). Earlier, he served as the Director of engineering and research at InfoDream Corporation, Santa Clara, CA. He also worked at Citicorp and Muze Inc. in New York as a senior consultant.
Dr. Manish Gupta is a Principal Applied Researcher at Microsoft India R&D Private Limited at Hyderabad, India. He is also an Adjunct Faculty at the International Institute of Information Technology, Hyderabad, and a visiting faculty at the Indian School of Business, Hyderabad. He received his Masters in Computer Science from IIT Bombay in 2007 and his Ph.D. from the University of Illinois at Urbana-Champaign in 2013. Before this, he worked for Yahoo! Bangalore for two years. His research interests are in the areas of web mining, data mining, and information retrieval. He has published more than 100 research papers in reputed refereed journals and conferences. He has also co-authored two books: one on Outlier Detection for Temporal Data and another one on Information Retrieval with Verbose Queries.
Dr. Niyati Chhaya is a Senior Computer Scientist at the Big Data Experience Lab, Adobe Research, Bangalore, India. Her research interests include affective computing, computational linguistics, natural language processing, and machine learning. Psycholinguistics, Computational Linguistics, and Machine learning put together can be efficiently leveraged to understand online users, their content preferences, and specifically their reactions including moods, opinions, and emotions. Niyati focuses on this research Affective Computing for Language and Text. Her work has applications towards Personalization at Scale for Content Authoring and towards creating personalized experiences. She completed her Ph.D. from the University of Maryland Baltimore County (UMBC) in September 2012. Her dissertation was on Joint Inference for Extracting Soft Biometric Text Descriptors from Patient Triage Images. She completed her M.S. in computer science from UMBC in May 2010 and B.E. from the University of Pune (India) in 2008. Her work experience includes research internships at the National Library of Medicine, National Institutes of Health, Bethesda, MD.