Emille D. Lawrence is a low-dimensional topologist. Her mathematical interests include braid groups, geometric group theory, and spatial graphs. She is also an advocate for broadening participation in the mathematical sciences through outreach and mentoring.
PhD, Mathematics, University of Georgia, 2007, BS, Mathematics, Spelman College, 2001
My general research area is logic and computability theory, in particular computable structure theory. I am also studying quantum computing & quantum logic. More information at http://cs.usfca.edu/~jcchubb
PhD, Mathematics, George Washington University, 2009, MS, Applied Mathematics, George Mason University, 2003, BS, Physics & Applied Mathematics, George Mason University, 1999
Stephen Devlin is a Professor in the Department of Mathematics and Statistics and is the director of 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...
PhD, Mathematics, University of Maryland, 2001
Renee Brunelle Hubert has been fascinated by mathematics since a very young age. After graduating magna cum laude from USF with a BS in mathematics in 1994, she attended UC San Diego on a Cota Robles Fellowship, earning an MA in mathematics in 1997 with emphases in complex analysis and abstract algebra. She currently specializes in making mathematics accessible and exciting to non-majors, and investigating ways to integrate technology into the learning experience.
MA, Mathematics, University of California, San Diego, 1997
Paul Intrevado is an Assistant Professor of Data Science in the Department of Mathematics & Statistics. Paul is a co-director of the Machine Learning, Artificial Intelligence, Gaming Intelligence and Computing at Scale (MAGICS) Lab. He previously served as the MS Data Science Practicum Director [2014-2017], and is the founding Associate Director of the Data Institute [2017]. Professor Intrevado’s research focuses on service operations, including healthcare, hospitality and sports. Most...
PhD, Operations Management, McGill University, MSc Industrial Engineering, Purdue University, BSc Industrial Engineering, Purdue University, Baccalaureate of Commerce, McGill University
Daniel Jerison studies probability theory. He is interested in the properties of random objects, such as random planar maps and abelian sandpiles, and in the convergence of Markov chain Monte Carlo algorithms.
Stanford University, PhD in Mathematics, 2016, Harvard University, BA in Mathematics, 2007
Tristan Needham (son of the distinguished social anthropologist Rodney Needham) grew up in Oxford, England, where he attended the Dragon School (with Stephen Wolfram and Hugh Laurie). He studied physics at Merton College, Oxford, before moving to the Mathematical Institute, where he enjoyed the great privilege of studying black holes under the supervision of Sir Roger Penrose. Tristan received his DPhil in 1987, and joined the faculty of the University of San Francisco in 1989. His current...
DPhil, Mathematics, Oxford University, 1987
Daniel's research interests are in large scale optimization modeling and algorithms. His postdoctoral research in the UCLA Department of Radiation Oncology focused on applications of optimization in radiation therapy, medical imaging, and machine learning.
PhD, Mathematics, UCLA
David Uminsky's research interests are in applied mathematics. He is interested in unsupervised machine learning, data clustering, algebraic signal processing, as well as pattern formation, dynamical systems and fluids. David was selected in 2015 by the National Academy of Sciences (NAS) as a Kavli Frontiers of Science Fellow. Each year, 100 researchers under the age of 45 are selected by the academy, and the 20% of the current NAS were previous Kavli Fellows. He is also the founding director...
PhD, Mathematics, Boston University, BS, Mathematics, Harvey Mudd College
Cornelia Van Cott is a geometric topologist, studying knots, surfaces, and the interplay between three and four-dimensional topology.
PhD, Mathematics, Indiana University, 2008
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.
PhD, Statistics, Purdue University, 2015, BS, Mathematics, Fudan University, 2009
James is an Assistant 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 (...
PhD, Statistics and Operations Research, University of North Carolina, 2015, MS, Mathematical Sciences, Clemson University, 2010, BS, Mathematics, Campbell University, 2008, BS, Chemistry, Campbell University, 2008
Dynamical systems theory including coupled oscillators, Josephson junction arrays, injection lasers, sigma-delta data converters, and algorithmic analysis of microarray data
PhD, Mathematics, Cornell University, 1999
For Professor Damon, teaching math is a second career; before teaching she worked in the finance industry as a bond fund manager. In her spare time she likes working math problems, jogging, hiking, reading, and baking sourdough bread.
San Francisco State University, MA in Mathematics, 2011, UC Berkeley, BA in Applied Mathematics, 1983, UC Berkeley, BA in Economics, 1983
Tahir Issa is a data science postdoctoral fellow at the USF Data Institute. His research is in applied mathematics, mathematical biology, statistical learning, and applied deep learning.
Auburn University, PhD in Mathematics, Auburn University, MS in Probability and Statistics
Dmitriy is an adjunct math professor at the University of San Francisco.
UC Berkeley, BS in Math (with High Honors), 2003, Stanford University, PhD in Math, 2010
Although Professor Elizabeth Mickaily-Huber's degrees are in chemical engineering, her specialty is in computational fluid dynamics (CFD). Over the years, besides using CFD to solve real-world problems, she has taught engineering and mathematics at the University of San Francisco, San Francisco State University, the Swiss Federal Institute of Technology at Lausanne (Switzerland), and CSU Los Angeles.
University of California, San Diego, PhD in Chemical Engineering, University of California, San Diego, MS in Chemical Engineering, University of California, Berkeley, BS in Chemical Engineering
Van Tran has been a dedicated instructor at USF for more than 10 years.
UCLA, MA in Mathematics, UC Davis, BS in Mathematics, UC Davis, BA in Economics
Michael Valdez completed his BS in honors mathematics at USF in 2006. He obtained his MS in mathematics from UCI in 2008. His studies have primarily focused on numerical and applied mathematics. Valdez has been teaching in the California community college system for the last 13 years. In between his teaching career, he took a short detour testing his religious vocation with the Anglican Franciscans at the Society of St. Francis, working with the poor in San Francisco and giving spiritual...
UC Irvine, MS in Mathematics, 2008, University of San Francisco, BS in Honors Mathematics, 2006
Applied & Numerical Mathematics
Millianne Lehmann received her M.A. in Mathematics from San Francisco State University in 1963 and joined the USF faculty 1965. Her areas of interest include mathematics education and technology-assisted instruction in mathematics. She was project director for the USF Middle School Math Institute (an NSF-funded program from 1984–1986. She has co-authored four books, the latest of which, Quantitative Methods for Business, a Conceptual, Excel-Based Approach (co-authored with Paul Zeitz) will be...
Professor Pacheco's main research interest is parallel computing. He's been involved in the development of the MPI Standard for message-passing. His book Parallel Programming with MPI is an elementary introduction to programming parallel systems that use the MPI 1 library of extensions to C and Fortran. His book An Introduction to Parallel Programming is designed to teach inexperienced programmers how to program both shared- and distributed-memory parallel systems.
PhD, Mathematics, Florida State University, 1983
Parallel computing
John Stillwell was born in Melbourne, Australia, and taught at Monash University from 1970 until 2001, before moving to USF in 2002. He was an invited speaker at the International Congress of Mathematicians in 1994, and his mathematical writing has been honored with the Chauvenet Prize of the Mathematical Association of America in 2005 and the book award of the Association of Jesuit Colleges and Universities in 2009. Among his best-known books are Mathematics and Its History (3rd edition,...
PhD, MIT, 1970
Originally trained as an ergodic theorist (PhD University of California, Berkeley, 1992), today Paul Zeitz's overriding interest is mathematical problem solving and the promulgation of an Eastern European-inspired problem-solving culture to American audiences. Towards this end, he wrote The Art and Craft of Problem Solving in 1998, co-founded the Bay Area Mathematical Olympiad in 1999, and co-founded the San Francisco Math Circle in 2005. In 2009 he produced a series of video lectures for The...
PhD, University of California, Berkeley, 1992
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