Appointment of Four New Data Science Faculty Fellows at Boston University
From Dr. Jean Morrison, University Provost and Chief Academic Officer
I am delighted to announce the appointment of four new Data Science Faculty Fellows through BU’s Data Science Initiative (DSI).
Launched in 2017, the Data Science Faculty Fellows program brings together uniquely talented faculty whose scholarship advances and leverages data science methodologies to enable fundamental advances across the entire academic landscape. Those chosen for this distinction are expected to play a leading role in steering the DSI, based out of the Rafik B. Hariri Institute for Computing and Computational Science & Engineering, and in helping to build on BU’s vision for research and education in this strategically important area.
Since the launch of this program, we have appointed 13 Data Science Faculty Fellows from across four schools and colleges, whose distinctive research areas have sparked cross-disciplinary collaborations in fields as varied as public health, law, cybersecurity, bioinformatics, and machine learning. As with our previous appointees, this year’s Fellows emerged from a rigorous selection process and represent a host of diverse disciplines. All have been cited for exceptional contributions to their areas of study and for the versatility, multidisciplinary scope, and tremendous potential of their research to yield new innovations and breakthroughs.
This year’s Data Science Faculty Fellows are:
Professor of Computer Science, College of Arts & Sciences
A member of BU’s Computer Science faculty since 1994 and past department chair, Mark Crovella works to improve the understanding, design, and performance of parallel and networked computer systems – mainly through the application of data mining, statistics, and performance evaluation. His recent work has focused on the analysis of social and biological networks with applications to recommender systems, public opinion analytics, and computational biology. He is an elected fellow of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE), holds 10 patents derived from his research, and has published a book and more than 200 widely-cited papers on networking and computer systems. He holds a doctorate from the University of Rochester, a master’s degree from the State University of New York at Buffalo, and a bachelor’s degree from Cornell University.
Jonathan Huggins (arriving January 2020)
Assistant Professor of Mathematics & Statistics, College of Arts & Sciences
Jonathan Huggins will formally join the Mathematics & Statistics faculty in January 2020 from Harvard University, where he has been a postdoctoral fellow in biostatistics. Jonathan’s research centers on the development of fast, trustworthy machine learning and AI methods that balance the need for computational efficiency and the desire for statistical optimality with the inherent imperfections that come from real-world problems, large datasets, and complex models. In addition to affiliations with Dana-Farber Cancer Institute and the Broad Institute of MIT and Harvard, he has published over a dozen papers in leading statistics and machine learning journals and conference proceedings. He received his doctorate and master’s degree in computer science from MIT and his bachelor’s degree in mathematics from Columbia University.
Associate Professor of Computer Science, College of Arts & Sciences
Kate Saenko has been a member of the Computer Science faculty since 2016 and is director of BU’s Computer Vision and Learning Group, where she specializes in machine learning, concentrating on the development of new systems to enhance vision and language understanding. The recipient of several active federal grants supporting her research into artificial intelligence, she has published extensively in leading computer science journals, serves as program chair for the 2020 Conference on Computer Vision and Pattern Recognition, and in 2017 received the Most Innovative Solution award, alongside her students, in the IEEE Large-Scale Activity Recognition Challenge. She holds a doctorate and master’s degree in electrical engineering and computer science from MIT and a bachelor’s degree in computer science from University of British Columbia.
Professor of Electrical & Computer Engineering and Systems Engineering, College of Engineering
Venkatesh Saligrama joined the Department of Electrical & Computer Engineering in 2001, where he explores problems arising in machine learning, statistical signal processing, and control and information theory. His recent research has focused on machine learning under budget constraints, identifying racial and gender bias in AI systems, and developing new tools for video analytics in highly cluttered and urban scenarios. An elected fellow of the IEEE, he is a past recipient of the Presidential Early Career Award, NSF CAREER Award, and Office of Naval Research Young Investigator Award. He has edited a book, published dozens of widely-cited articles and papers in leading journals and conference proceedings, and is incoming chair of the Big Data Special Interest Group of the IEEE Signal Processing Society. He received his doctorate and master’s degree from MIT and his bachelor’s degree from Indian Institute of Technology in Madras.
Professors Crovella, Saenko, and Saligrama began their appointments this fall as Data Science Faculty Fellows, and Professor Huggins will begin his in January 2020. All bring enormous talent and potential through their unique interdisciplinary portfolios to advance BU’s data science capabilities, and we are excited for what the future holds for them and their research. We look forward to their contributions in the years ahead.
Thank you for your assistance identifying and nominating the talented candidates we considered for these fellowships. Thanks are also due to DSI Chair, Hariri Institute Director, and William Fairfield Warren Professor Azer Bestavros for his continued leadership on this important initiative.