As founding Head of the interdisciplinary Data Science program here at WPI, I take great pleasure in doing all in my power to support the Data Science community in all its facets from research collaborations, and new educational initiatives to our innovative industry-sponsored and mentored Graduate Qualifying projects at the graduate level.

Having served as the primary advisor and mentor of over 43 Ph.D. students who have secured successful professional careers in computing, I'm proud of all the great accomplishments of students I have had the opportunity to collaborate with. With an h-index of 65, I have authored well over 600 publications (with over 16,000 citations), numerous patents, and software systems released to the public domain. My research work, widely cited, has been supported by government agencies including NSF, NIH, DOE, FDA, and DARPA, and by industry including HP, IBM, Verizon Labs, GTE, NEC, AMADEUS, Charles River Analytics, and by labs such as Army Research Labs, MIT Lincoln Labs, and MITRE Corporation. I've enjoyed holding leadership positions in the big data field, including having served as Associate Editor of prestigious journals including IEEE Transactions on Data and Knowledge Engineering and VLDB Journal, area chair on premiere professional big data conferences, including ACM KDD, ACM SIGMOD, VLDB, IEEE ICDE, and program committee lead for countless conferences. 

My research focuses on how to make use of data and information effectively, towards achieving goals in business, scientific discovery, and digital health. With interconnectivityvity of the internet, the availability of computing power, and digital data everywhere, access to the right piece of information at the right moment, possibly fused together from numerous information sources, remains one of the most critical capabilities that can set you apart from others. Together with undergraduates, graduate students, post-docs, and other faculty, I strive to develop intelligent systems solutions leveraging AI, machine learning, big data, and data visualization technologies to discover and explore important nuggets and patterns in massive data sets in near real-time in applications from fraud detection, digital health, emergency management, business intelligence, to event analytics.

I love every moment of working with students and colleagues at WPI and in industry on cutting-edge data science research and project activities. At the undergraduate level, I work with students on MQP,  IQP projects, and REU research projects focused on computer science and data science research challenges often in collaboration with companies and other organizations.