Academic Director

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Diane Woodbridge is an assistant professor in the MS in Data Science program at the University of San Francisco. Her research interests include database management systems, data fusion and data mining in various domains including biomedical, geoscience and geospatial remote sensing. Prior to joining USF, Professor Woodbridge was with the scalable analysis and visualization department at Sandia National Laboratories.

Education:
  • PhD, Computer Science, University of California, Los Angeles
  • MS, Computer Science, University of California, Los Angeles
  • BS, Computer Science and Engineering, Sogang University, South Korea

Full-Time Faculty

Harney Science Center 440A

David is an assistant professor at the University of San Francisco. His research interests are natural language processing, machine learning, and databases — specifically on the personal and cultural/demographic information transmitted during speech and typing. This research may lead to more accurate speech recognition systems.

Prior to joining USF, David was a research assistant in the Speech Lab at Queens College and an instructor at Hunter College. He has previously worked for the City of...

Education:
  • PhD, Computer Science, CUNY Graduate Center (candidate)
  • MS Computer Science, San Francisco State University
  • BS Computer & Information Science, Brooklyn College
Expertise:
  • Speech Processing
  • Applications of Machine Learning

Cody Carroll is an assistant professor with joint appointments in the Department of Mathematics and Statistics and the Master's in Data Science program (MSDS). He holds a PhD and MS in Statistics from the University of California, Davis and a BS in mathematics from the University of Texas at Austin. His methodological research interests focus on functional and longitudinal data, particularly in the context of human growth and aging, and his interdisciplinary work has spanned a wide range of...

Education:
  • UC Davis, PhD in Statistics, 2021
  • UC Davis, MS in Statistics, 2017
  • UT Austin, BS in Mathematics, 2014
Expertise:
  • Time warping & curve registration
  • Multivariate functional data
  • Statistical consulting
  • Communication through statistics

Robert Clements is an assistant professor in the MS in Data Science program. His interests include making data science concepts more accessible to a general audience through visual methods, and combining data, code and models with art. Prior to joining USF he had a nearly ten-year career in industry, holding several positions throughout the San Francisco Bay Area as a data scientist and data science manager/director, working primarily in developing machine learning models in different domains...

Education:
  • UCLA, PhD in Statistics, 2011
  • UCLA, MS in Statistics, 2009
  • Humboldt State University, BA in Mathematics, 2006
Harney Science Center 122C

Stephen Devlin is a Professor in the Department of Mathematics and Statistics and the Master’s in Data Science program (MSDS). He has also served as department chair and director of the undergraduate data science program. Stephen has a bachelor’s degree from Manhattan College in New York, and a Ph.D. in mathematics from the University of Maryland. He was a C.L.E. Moore Instructor at MIT before moving to the University of San Francisco. His research interests include both pure and applied...

Education:
  • PhD, Mathematics, University of Maryland, 2001

Mustafa Hajij is an assistant professor at the MSDS program at University of San Francisco. He received his masters in Computer Science, PhD in Mathematics from Louisiana State University and postdoctoral training at the computer science departments at University of South Florida and Ohio State University. Before joining  MSDS program he was an assistant professor at the department of Mathematics and Computer Science at Santa Clara University. Prior to SCU, he spent a year as an AI research...

Education:
  • Louisiana State University, PhD in Mathematics.
  • Louisiana State University, MS in Computer Science.
  • Jordan University for Science and Technology, MS in Mathematics.
  • Damascus University, BS in...
Expertise:
  • Deep Learning
  • Algorithms
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As the Senior Director of the Data Institute, Jeff Hamrick is responsible for the Institute's vision and strategic planning process, as well as its various centers and initiatives. Professor Hamrick has been instrumental in developing the University of San Francisco’s Master of Science in Data Science (MSDS) program. He has previously taught in the Master of Science in Financial Analysis (MSFA) program at the School of Management, where he holds a joint appointment.

For the MSDS program, he...

Education:
  • PhD, Mathematics, Boston University, Massachusetts, 2009
  • Certificate in Computational Science, Boston University, Massachusetts, 2009
  • MA, Mathematics, Boston University, Massachusetts, 2004
  • B...
Expertise:
  • Higher education administration
  • Data science
  • Econometrics
  • Financial markets
  • Investment management
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Yannet is an associate professor in the Master’s in Data Science program, and her research interests lie in the application of machine learning and deep learning to medical data. She holds a PhD in applied mathematics from Cornell University and a BS in mathematics from the University of Havana, Cuba. After a postdoctoral fellowship at UC Berkeley, she worked for five years as a data scientist at Google. Yannet co-founded Akualab, a start-up that helped organizations develop data-driven products...

Education:
  • Cornell University, PhD in Applied Mathematics, 2006
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Terence is a professor of computer science and is the creator of the ANTLR parser generator. He herded programmers and implemented the large jGuru developers web site, during which time he developed and refined the StringTemplate engine. Terence has consulted for and held various technical positions at companies such as IBM, Lockheed Missiles and Space, NeXT, and Renault Automation. Terence was an expert witness for Google in the Oracle v Google Android lawsuit. His passion is writing software.
...

Education:
  • PhD in Computer Engineering, Purdue University '93
Expertise:
  • Software engineering
  • Programming language design and implementation
  • How programmers communicate with machines to build new software

Michael Ruddy is an assistant professor in the Master in Data Science program. His research interests are in deep learning in image processing and applications of geometry to image science, data science, and statistics. He is passionate about creating a respectful and inclusive environment in his courses, in which students feel comfortable collaborating, taking risks, and making mistakes.

Professor Ruddy received a PhD in mathematics from North Carolina State University in 2019 (with advisers...

Education:
  • North Carolina State University, PhD in Mathematics, 2019
  • University of Tennessee at Martin, BS in Mathematics, 2014

Shan is an assistant professor at the University of San Francisco and currently teaching full time for USF's Data Science programs. Her research interests are nonparametric estimation, prediction models, and applied statistics. Shan also works closely with experts from different fields. She has experiences in NIH and NSF grants in cancer research and GIS. She holds a PhD in statistics from Purdue University (IUPUI campus) and a BS in mathematics from Fudan University in China.

Education:
  • PhD, Statistics, Purdue University, 2015
  • BS, Mathematics, Fudan University, 2009
Harney Science Center 107B

James is an Associate Professor of Statistics and Co-Director of the BS in Data Science program at the University of San Francisco. He has joint appointments in the Department of Mathematics and Statistics and the MS in Data Science program, where he has developed and taught courses in Bayesian statistics, machine learning, data science, and network analysis.

In research, James develops new statistical and computational techniques to model, analyze, and explore high-dimensional and relational...

Education:
  • PhD, Statistics and Operations Research, University of North Carolina, 2015
  • MS, Mathematical Sciences, Clemson University, 2010
  • BS, Mathematics, Campbell University, 2008
  • BS, Chemistry...

Part-Time Faculty

Michael Brzustowicz is a physicist turned data scientist. After a PhD from Indiana University, Michael spent his post doctoral years at Stanford University where he shot high powered X-rays at tiny molecules. Jumping ship from academia, he worked at many startups (including his own) and has been pioneering big data techniques all the way. Michael specializes in building distributed data systems and extracting knowledge from massive data. He spends most of his time writing customized, multi...

Education:
  • PhD, Indiana University
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Sundar Dorai-Raj has been a data scientist at Google since 2009. He has spent most of his career working on Ads products, from YouTube Ads, where he helped launch YouTube's first skippable ad format, to Brand Lift and Google Analytics. He currently manages a team of data scientists who focus on privacy-centric analytics, quantifying the effectiveness of YouTube advertising, and Bayesian methods for online experiments. His expertise includes A/B testing, statistical modeling, machine learning...

Education:
  • Virginia Tech, PhD in Statistics, 2001
  • Virginia Tech, MS in Statistics, 1999
  • University of Alabama, MA in Applied Math, 1997
  • University of Alabama, BS in Applied Math, 1995
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Nicholas Ross received his PhD from UCLA's Anderson School of Management in 2012. His research interests revolve around how asymmetric information affects decision making and using data to understand those effects. Most recently he has worked on a number of cloud-based systems which use machine learning and other data science techniques to extract information from complex data sources.

Prior to receiving his PhD, Nick worked as a litigation consultant at Bates White in Washington DC and San...

Education:
  • Ph.D., Anderson School of Business, University of California, Los Angeles, California, 2012
  • M.A., Economics, University of California, Davis, California, 2007
  • B.A., Applied Mathematics, Honors...

Jason has a deep background in data science. He currently works as SVP of Data Science at Aki Technologies and previously served as Head of Data Science and Analytics for FinTech data solutions provider Womply. He spent twelve years at The Boeing Company in engineering, operations research, strategy, and business development. Jason previously served as an Advisory Board Member to the Data Institute.

Education:
  • MBA, Georgetown University
  • MS, Analytics, University of San Francisco
  • MS, Systems Engineering, USC
  • BS, Mechanical Engineering, University of Illinois
Harney Science Center 122A

Nathaniel is interested in using data to make decisions, solve problems, and improve processes. Specifically, his research interests lie in methodological development at the intersection of data science and industrial statistics; his publications span topics including experimental design and A/B testing, social network modeling and monitoring, survival and reliability analysis, measurement system analysis, and the development of estimation-based alternatives to traditional hypothesis testing...

Education:
  • PhD, Statistics, University of Waterloo, 2015
  • MMATH, Statistics, University of Waterloo, 2011
  • BMATH, Statistics, University of Waterloo, 2010
  • Minor, Pure Math and Psychology, University of...

Instructor

Jeremy Howard is an entrepreneur, business strategist, developer, and educator. He is a founding researcher at fast.ai, a research institute dedicated to making deep learning more accessible. He is also a Distinguished Research Scientist at the University of San Francisco, a faculty member at Singularity University, and a Young Global Leader with the World Economic Forum.

Jeremy’s most recent startup, Enlitic, was the first company to apply deep learning to medicine, and has been selected one...