Jacqueline Johnson is a principal analytical training consultant in Global Academic Programs at SAS Institute. In her role at SAS, she conducts SAS software trainings at academic campuses around the country and works with faculty to support efforts to develop the future analytics workforce. She holds a DrPH in Biostatistics from UNC Chapel Hill. Prior to coming to SAS, Dr. Johnson’s career has focused on statistical analyses of clinical trials data and includes working as a biostatistics faculty in at the UNC Chapel Hill School of Medicine and as a biostatistician in industry at Novartis Pharmaceuticals and Rho, Inc. She has been teaching with SAS in commercial and academic settings since 2009 and joined the SAS Global Academic Programs instructional team full-time in 2019. 

Justin serves as a Senior Data Scientist responsible for applying innovative human-like artificial intelligence to financial crimes. Insights from reverse-engineering humans have enabled patents and algorithms that perform cutting-edge AI explainability, one-shot learning, graph search, and small data analytics while remaining human-interpretable. His efforts enable the processing of problems such as elder abuse, fraud, and human trafficking where complex behaviors are captured only by sparse data.

Amy Chang is a Senior Analyst in Enterprise Analytics at Blue Cross Blue Shield of Massachusetts who specializes in analyzing complex data and communicating analytic insights for actionable business outputs. Her work at Blue Cross MA has led to the creation of COVID-19 vulnerability indices that led to outreach and support of over 8,000 members during the pandemic, removal of $100,000 in COVID-related cost share for members, and the development of new digitally engaging BlueFit HMO and PPO Health Plans and the BlueCare360 buy-up program. Prior to Blue Cross, Amy’s work at public-private partnership Health Data Consortium with the US Department of Health and Human Services was instrumental in liberating federal governmental data to advance availability of analytics enhanced with public big data. Her strategy work also led the successful presentation of the Telling Health Stories with Interactive Storymaps session at SXSW Interactive 2016.

She received her Masters of Public Health in Biostatistics and Epidemiology from Boston University.

Gunce E. Walton is a manager of a development team at SAS. She researches, implements, and oversees econometric techniques in SAS Econometrics procedures and action sets for cross-sectional and panel data analysis. She also plays a critical role in promoting SAS Econometrics products. Her recent research focus has been on implementation of machine learning techniques for causal analysis in policy research. Prior to working at SAS, Gunce was an assistant professor at Instituto Tecnologico Autonomo de Mexico, Mexico City. She taught graduate and undergraduate level empirical micro-econometrics classes. She has many published articles in the areas of instrumental variable estimation, instrument selection methods, and dynamic panel data model estimation. Gunce has a Ph.D. in Economics from North Carolina State University.

Frederico Batista Pereira (Fred Batista) is an Assistant Professor of Political Science and Public Administration at the University of North Carolina at Charlotte (UNCC). He is also a member of the Latin American Studies Program and the School of Data Science at UNCC. His research focuses on public opinion and misinformation in Brazil and Latin America.

Dr. Jun Xu is an Assistant Professor in the Department of Mechanical Engineering & Engineering Science at the University of North Carolina at Charlotte. He is the director of Vehicle Energy & Safety Laboratory. Dr. Xu obtained his Ph.D. from Columbia University major in environmental engineering/engineering mechanics and returned to China in 2014. In 2018, Dr. Xu moved his research group to UNC Charlotte and established a new lab there. Dr. Xu’s research area includes multiphysics modeling of lithium-ion battery safety issues and the design of advanced materials and structures under dynamic mechanical loadings. Dr. Jun Xu now serves as the Chair of Energy Conversion & Storage Committee and Chair of Multifunctional Materials Committee, ASME. He has so far published more than 110 peer-reviewed papers with more than 3700 citations and H-index=33.

Michael Korvink is a Principal Data Scientist for Premier’s ITS Data Science division and active Advisory Board member in The University of North Carolina at Charlotte’s School of Data Science (SDS). In current role, he develops machine learning and statistical models to aid in the solution of complex business problems. At Premier, he has also served as a Lead Technical Developer and Systems Analyst where he contributed to enterprise development efforts and large-scale system architecture.

Michael is a former Lecturer of Computer Science at the University of North Carolina at Charlotte where he taught courses in machine learning and data mining. He is proficient in R, Java/Spring, SQL, and Bash/Linux. Michael holds a Master of Arts from The University of North Carolina at Charlotte where he focused on Linguistic Decipherment Methods.

Jingfen Zhu is an executive and practitioner in Data Science with over 18 years of cross-industry experience in Life Science, Healthcare, Finance and CPG. Throughout her career with AT&T, Experian and Dow Jones and currently Genpact, she has developed numerous state-of-the-art analytical solutions which have been productionized and generated tremendous financial outcome. Her responsibilities include thought leadership advisory, innovation guidance, as well as mentoring and lecturing. The team she coached participated in the 2018 Data Hackathon held by KeyBank and ranks top 3 in Client Centricity solutions among 72 competing teams and 300 contestants. The first-phase deployment of personalized customer retention strategy from this hackathon solution resulted in a signed-off savings
of $38 million. She received Ph.D. in Applied Statistics and M.S. in Management Science from The Pennsylvania State University – University Park.

Pankaj Telang is a Principal Staff Scientist in the Computer Vision team at SAS. He has over 20 years of experience in the areas of artificial intelligence, machine learning, computer vision, cybersecurity and software development. He enjoys research and development in the areas of computer vision and deep learning. He received a Ph.D. degree in Computer Science from the NC State University.

Dr. Weidong Tian is currently a professor of finance and a distinguished professor of risk management and insurance. Prior to coming to UNC Charlotte, Dr. Tian served as a faculty member at the University of Waterloo and a visiting scholar at the Sloan School of Management at MIT, Shanghai Advanced Institute of Finance, University of Cambridge, and a visiting Research Fellow of SAMSI. His primary research interests are asset pricing, quantitative finance, and risk management. He has been more interested in the data-driving asset allocation strategies, model-free application for asset pricing, long-term investment (retirement portfolio and pension funds), and nonparametric derivative pricing. Dr. Tian has published in many top academic journals, including Review of Financial Studies, Management Science, Finance and Stochastics, Mathematical Finance, Journal of Risk and Insurance, and professional journals, including Journal of Fixed Income, Journal of Investing, and Journal of Investment Strategy. His editorial book entitled “Commercial Banking Risk Management: Regulation in the Wake of the 2008 Financial Crisis” has been published by Palgrave Macmillan. He also held various positions in financial institutions before joining UNC Charlotte and the University of Waterloo, and extensive consulting experiences in fund industries and financial institutions.