Principal data scientist at Nanigans. Previously worked as a senior software engineer at Google and Microsoft working on large scale machine learning. Presented a workshop on Machine learning for profit: Computational advertising landscape and Data Science at the Command Line.

Computational and Applied Mathematics department at Rice University. His research focuses on scientific computation, including scalable algorithms and parallel computing, numerical analysis, software development, and computational geophysics and biology. Presented on How Should We Write Simulation Software? and The Portable Extensible Toolkit for Scientific Computation.

University of Chicago. Presented on Scalable Marketing.

Title: A genetic algorithm approach for building parmacokinetic model

Dr. Bies is an Associate Professor of Pharmaceutical Sciences at the School of Pharmacy and Pharmaceutical Sciences as well as a member of the Center for Data Sciences and Engineering at the State University of New York at Buffalo. 

Title: Time-variation in market efficiency: The code behind the chart

Dominik Roesch is an Assistant Professor of Finance at the State University of New York at Buffalo. He obtained a Ph.D. from the Rotterdam School of Management, Erasmus University and Master degrees in Mathematics from the University of Bonn and in Finance from the University of London. 

Title: Uncertainty quantification for multiscale transport equation

Dr. Li Wang is an Assistant Professor in the Department of Mathematics at the University of Buffalo starting Jan. 2016. She is also a core faculty member of the Computational and Data-Enabled Science and Engineering program.

Title: Transitioning to data-driven careers in industry

Greg Antell from Insight Data Science. Greg Antell is a Program Director for Insight Health Data Science in Boston, Massachusetts and a former fellow of the program from the Winter 2016 cohort.

Title: Adjoint Methods for Uncertainty Quantificaiton

Varis Carey  - University of Colorado-Denver

Title: Optimization Methods for Machine Learning

Haimonti Dutta is an Assistant Professor in the Department of Management Science and Systems (MSS), School of Management, University at Buffalo, New York. Prior to her current appointment she served as an Associate Research Scientist at the Center for Computational Learning Systems (CCLS) at Columbia University, NY where she headed the Scalable Analytics Research Group.

Title: Industry 4.0 with the Digital Manufacturing Commons

Ken English, SMART CoE, University at Buffalo
Chi Zhou, Industrial and Systems Engineering, University at Buffalo

Title: Pharmacometrics as interdisciplinary science aiding drug development

Title: R for High-Throughput (Genomic) Analysis

Dr. Martin Morgan has been working with R for the last 10 years or so; he currently leads the successful and widely used open-source R / Bioconductor project for the analysis and comprehension of high throughput genomic data.

Title: Network Visualization

Dr. Sarah Feldt Muldoon joined the University at Buffalo in 2015 as an Assistant Professor in the Mathematics Department, core faculty in the Computational and Data-Enabled Sciences and Engineering Program, and member of the Neuroscience Program. 

Title: Big Data with Apache Accumulo

Dr. Dennis Patrone is a member of the senior professional staff at The Johns Hopkins University Applied Physics Laboratory (JHU/APL) in Laurel, MD.  During his 17 year-tenure at JHU/APL, Dr. Patrone has worked on a wide range of projects that have been used on submarines, in space applications, and everywhere in between. 

Title: Python and Jupyter for Programmers

John Ringland is an Associate Professor of Mathematics at UB. His research interests are in dynamical systems, both abstract and applied.

Title: Making Decisions in a Curious World: What Do We Know and How Do We Know We Know It

Anthony Scriffignano in an internationally recognized data scientist with experience spanning over 35 years, in multiple industries and enterprise domains. Dr. Scriffignano has extensive background in linguistics and advanced algorithms, leveraging that background as primary inventor on multiple patents worldwide.

Title: '2017 UB Symposium on Job and Career Perspectives for Students in the Computational Sciences'