30 Data Science Professors to Watch

Last Updated By • March 11, 2023

Data science — the analysis and management of large quantities of data — is one of the fastest growing industries. Data scientists from all around the world are asking more and more questions, and pushing the envelope further and further for the answers. Perhaps not surprisingly, many of those responsible for expanding data science into “the best job in America” (according to a report by Glassdoor) are college professors.

To narrow down our list to only 30 data science professors to watch, we considered only those who are currently employed by a university, who have authored ten or more articles or chapters for an impactful publication, and who have held some sort of leadership role in an organization outside of their university. We also considered such accomplishments as awards won and fellowships held.

Dr. Peter Allen

Columbia University

Dr. Peter Allen is a professor of computer science at Columbia University, where he teaches courses on data structures, algorithms, humanoid robots, and computation aspects of robots. He has published a number of books and articles, and his many honors include the Rubinoff Award, the Army Research Office Fellowship, University of Pennsylvania’s CBS Foundation Fellowship, and the National Science Foundation’s Presidential Young Investigator award.

Dr. Rafael Alvarado

University of Virginia

A self-proclaimed humanist, Dr. Rafael Alvarado teaches courses on dataesthetics, the internet, and digital liberal arts at University of Virginia. There, he also researches myriad data science-related topics ranging from iconography to text datasets. His experience designing text, media, and image management systems spans nearly two decades, though he also has vast experience in data modeling and programming web applications.

Dr. Cecilia Aragon

University of Washington

Dr. Cecilia Aragon is a professor and researcher whose work focuses on the topics of data science and big data, emotion in informal text communication, and visual analytics. Besides teaching at University of Washington, Dr. Aragon has worked as a principal investigator for more than $27 million worth of projects for organizations such as the National Science Foundation. She also serves as a senior data science fellow at the eScience Institute and is the director of the Human-Centered Data Science Lab. In 2008, Dr. Aragon received the Presidential Early Career Award for Scientists and Engineers in recognition of her work in data science.

Dr. Shlomo Argamon

Illinois Institute of Technology

Not only does Dr. Shlomo Argamon teach classes on computer science at Illinois Institute of Technology, he also founded the Institute’s Master of Data Science program. He has worked on a number of applications having to do with everything from forensic linguistics to biomedical informatics, and has conducted research on many topics such as natural language style, individual reasoning, and social context, to name but a few. Dr. Argamon is also a fellow of the British Computer Society.

Dr. Magdalena Balazinska

University of Washington

Dr. Magdalena Balazinska has proven herself a leading force in improving science through big data. She is currently an associate professor in the Department of Computer Science and Engineering at University of Washington. She teaches courses relating to her specialties of big data management, sensor and scientific data management, and cloud computing. She has worked on projects for Myria, Nuage, and CQMS, and has also spoken at a number of conferences.

Dr. Guarav Bansal

University of Wisconsin, Green Bay

Once a quality assurance executive at General Motors India and Daewoo Motors India, Dr. Gaurav Bansal is today a professor of management information systems and statistics at University of Wisconsin, Green Bay. His main research interests include data mining, trust, and internet security. His research has been nominated for the Best Paper Award at the International Conference on Information Systems. In addition to teaching, he is an editorial board member of the Journal of the Midwest Association for Information Systems.

Dr. William Bosl

University of San Francisco

Those in the know may recognize Dr. William Bosl’s name from his many papers in publications such as BMC Medicine, the International Journal of Medical Research, and Epilepsy and Behavior. At the University of San Francisco, Dr. Bosl works as the director of the master of science in health informatics program, where he also conducts research on such topics as machine learning in healthcare, using nonlinear EEG analysis for early detection of neurodevelopmental disorders, and consciousness, among much more.

Dr. Tom Davenport

Babson College

Dr. Tom Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College. His research focuses on such topics as knowledge management, enterprise systems, business process reengineering, and analytics, among other areas. He has authored 18 books and more than 100 articles on topics related to data science, including the texts “Big Data @ Work” and “Keeping Up with the Quants.” Dr. Davenport was recently named one of the top three technology analysts in the world, and Fortune magazine named him as one of the 50 best business school professors.

Dr. David Donoho

Stanford University

As a professor in the Department of Statistics at Stanford University, Dr. David Donoho has conducted research on such topics as harmonic analysis, signal processing, and data visualization. His work and algorithms have greatly contributed to the overall understanding of maximum entropy principle, sparse data description, and robust procedures. He has been awarded a number of prestigious industry prizes, including both the Wiener Prize in Applied Mathematics (2010) and the Shaw Prize in Mathematical Sciences (2013).

Dr. John Elder

University of Virginia

Dr. John Elder is an adjunct professor of optimization and data mining at University of Virginia, as well as a data mining consultant at Elder Research Incorporated. Dr. Elder has authored many publications on topics that include image recognition, text mining, and credit scoring, among much more, and he is often asked to be the keynote speaker at data mining conferences around the world. Especially notable is the fact that Dr. Elder spent five years as part of a presidential-appointed panel that guided technology for National Security.

Dr. Michael J. Franklin

University of California, Berkeley

Michael J. Franklin, a professor of computer science at U.C. Berkeley, specializes in applications and large-scale data management infrastructure. He has presented at a number of conferences relating to data science, such as the 2013 IEEE BigData conference. He is currently working on a number of projects for AMPLab, CrowdDB, and MLbase.

Dr. Yoav Freund

University of California, San Diego

Dr. Yoav Freund is the faculty co-director of the data science and engineering program at U.C. San Diego, where he also teaches classes. His research on such topics as machine learning algorithms in bioinformatics, network routing, high-performance computing, and computer vision is known internationally. He has written a number of articles, and is the recipient of the Gödel Prize (2003) and the Kanellakis Prize (2004).

Dr. Hector Garcia-Molina

Stanford University

Dr. Hector Garcia-Molina is a professor in the departments of computer science and electrical engineering at Stanford University. His research specialties include distributed computing systems, database systems, and digital libraries, and he has been associated with the prestigious Stanford Digital Library Project. Dr. Garcia-Molina is the author of the texts “Database Systems: The Complete Book” and “Database System Implementation.”

Professor Ira Greenberg, MFA

Southern Methodist University

Professor Ira Greenberg teaches classes on creative coding and visualization of information at Southern Methodist University. Professor Greenberg published a widely read paper in 2007 entitled “Processing: Creative Coding and Computational Art,” and it is for this that he is currently best known. Interestingly, Professor Greenberg is also a highly accomplished painter, and his work has been displayed in such prestigious galleries as the Flywheel Gallery and the Bowery Gallery.

Dr. Carlos Guestrin

University of Washington

Dr. Carlos Guestrin specializes in machine learning, and has spoken at a number of conferences on the topic. He is the Amazon Professor of Machine Learning, an associate professor of computer science and engineering, and an adjunct professor of statistics at University of Washington.

Dr. Henry Kautz

University of Rochester

Dr. Henry Kautz teaches classes on pervasive computing, artificial intelligence, and data-enabled research, among other subjects at the University of Rochester. He is also the university’s Robin and Tim Wentworth Director of the Goergen Institute for Data Science. His work and research have received a number of awards thus far in his career, include the Ubicomp 10-Year Impact Award and the AAAI Classic Paper Award. Dr. Kautz has also been a fellow at the American Association for the Advancement of Science, the Association for Advancement of Artificial Intelligence, and the Association for Computing Machinery.

Dr. Ray Klump

Lewis University

Dr. Ray Klump is a professor at Lewis University in Romeoville, Illinois, where he serves as chair of the Department of Computer Sciences and Mathematics. His favored research topics include numerical methods, programming languages, and scientific visualization. He has also published a number of papers on these topics. In addition to teaching, Dr. Klump is the principal developer of Retriever at the software company PowerWorld.

Dr. David Leake

Indiana University, Bloomington

In addition to his role as executive dean of Indiana University, Bloomington, Dr. David Leake is a professor of computer science. He conducts research on a number of topics, including artificial intelligence, data science, and cognitive science, to name but a few. He has published three data science texts, and has served on the editorial boards of AI Magazine, the International Journal of Expert Systems Research and Applications, and the Journal of the Learning Sciences.

Dr. Hod Lipson

Cornell University

Dr. Hod Lipson is an associate professor of mechanical and aerospace engineering at Cornell University. Dr. Lipson specializes in a number of topics relating to artificial life, including evolutionary robotics, self-assembly, rapid prototyping, and design automation. He is the author of “Fabricated: The New World of 3D Printing,” and was recently named by Forbes as one of the World’s Most Powerful Data Scientists.

Dr. Deirdre Mulligan

University of California, Berkeley

As an associate professor at U.C. Berkeley’s School of Information, Dr. Deirdre Mulligan has instructed a number of courses on technology, information law and policy, and online privacy, to name but a few. Her main research interests include online privacy, the governance of technology, and cybersecurity, and she has more than a dozen published articles to her name. Dr. Mulligan is a member of the AI 100 Project committee, and a co-founder of the Global Network Initiative.

Dr. Alex Pentland

Massachusetts Institute of Technology

Dr. Alex Pentland is one of the computer science field’s most cited authors. He has published a number of articles and books, including “Social Physics: How Good Ideas Spread.” He helped found the MIT Media Lab at the Massachusetts Institute of Technology where he currently holds the positions of Toshiba Professor of Media Arts and Sciences, Director of MIT Media Lab Entrepreneurship Program, and Director of Human Dynamics Lab. Dr. Pentland was recently named by Forbes as one of the world’s most powerful data scientists.

Dr. Chris Re

Stanford University

Dr. Chris Re is an assistant professor of computer science at Stanford University where he teaches courses relating to his specialty, theoretical and practical problems in data management. Currently, Dr. Re is working on developing several data science-related applications for the Hazy project.

Dr. Manjeet Rege

University of St. Thomas

Dr. Manjeet Rege has published dozens of papers in such prestigious journals as Data Mining & Knowledge Discovery and Transactions on Knowledge and Data Engineering. Additionally, Dr. Rege is part of the editorial review board for the Journal of Computer Information Systems. As a professor at the University of St. Thomas, he has taught both undergraduate and graduate students, and was nominated for the Rochester Institute of Technology’s Eisenhart Award for Teaching Excellence.

Dr. Elke Rundensteiner

Worcester Polytechnic Institute

Dr. Elke Rundensteiner is the director of the data science program at Worcester Polytechnic Institute in Massachusetts, where she also teaches classes related to computer science. She has received a number of awards throughout her career thus far, including the EPTS Innovative Principles Award (2011) and the Sigma Xi Outstanding Senior Faculty Researcher Award (2007). Her research focuses on the ways in which data and information can aid in achieving goals in health services, science, and business.

Dr. Xiaotong Shen

University of Minnesota

Dr. Xiaotong Shen is a professor at the University of Minnesota, where he teaches classes on statistical learning and data mining. Besides teaching, Dr. Shen has served as the co-chair for the Institute of Mathematical Statistics, as well as the American Statistical Association’s group on Statistical Learning and Data Mining. Dr. Shen was awarded a fellowship with the American Association for the Advancement of Science, and has also been the recipient of a number of awards in recognition of his teaching.

Dr. Claudio Silva

New York University

Dr. Claudio Silva teaches in the Tandon School of Engineering at New York University. He has taught classes on scientific visualization and urban informatics, though his current topics of focus include big data and urban systems, data analysis, sports analytics, and geometry processing. Dr. Silva has been awarded more than a dozen U.S. patents, has been published in more than 220 journals, and has more than 10,000 research citations listed on Google Scholar.

Dr. Padhraic Smyth

University of California, Irvine

Dr. Padhraic Smyth teaches courses in the department of computer science at U.C. Irvine. He also serves as director of the school’s Data Science Initiative and associate director of the Center for Machine Learning and Intelligent Systems. He is widely published, and recently his paper, “Content Coding of Psychotherapy Transcripts Using Labeled Topic Models” appeared in the IEEE Journal of Biomedical and Health Informatics.

Dr. James Spall

Johns Hopkins University

Dr. James Spall serves as chair of the Applied and Computational Mathematics program and co-chair of the data science program at Johns Hopkins University. Besides holding two U.S. patents for inventions in control systems, Dr. Spall is extensively published on topics relating to data science, including three books on systems and control. He teaches classes on system identification, likelihood methods, stochastic search and optimization, and Monte Carlo methods, among other subjects.

Dr. Sebastian Thrun

Stanford University

Dr. Sebastian Thrun has a lengthy and impressive resume that includes such roles as Google fellow, co-founder of Udacity, and research professor at Stanford University. Dr. Thrun specializes in artificial intelligence and robotics, and he has participated in such prestigious projects as Google Glass and Google’s Self-Driving Car. He speaks at a number of conferences each year, and is the author of two books on robots.

Dr. Bin Yu

University of California, Berkeley

Bin Yu is yet another data science professor from the powerhouse that is U.C. Berkeley. She is a current Chancellor’s Professor in the Departments of Statistics, and Electrical Engineering & Computer Science. Her special areas of focus include statistical modeling and analysis of data structures, high-dimensional data problems, and machine learning. She has spoken at conferences on these topics.

 

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