Galit Shmueli

Galit Shmueli is Distinguished Professor at the Institute of Service Science, National Tsing Hua University, Taiwan. She is co-author of the best-selling textbook Data Mining for Business Analytics, among other books and numerous publications in top journals. She has designed and instructed courses on forecasting, data mining, statistics and other data analytics topics at University of Maryland’s Smith School of Business, the Indian School of Business, National Tsing Hua University and online at

Peter C. Bruce

Peter Bruce is the creator and president of The Institute for Statistics Education at, the leading provider of online education in statistics; he also develops and markets statistical software. Previously he taught statistics at the University of Maryland, and served in the US Foreign Service.

Nitin R. Patel

Nitin Patel has been a member of the faculty at MIT's Sloan School and the Operations Research Center since 1995. Previously, he was a Professor at the Indian Institute of Management, Ahmedabad, and held visiting positions at Harvard, the University of Michigan, the University of Montreal and the University of Pittsburgh. Dr. Patel is a fellow of the American Statistical Association.

Mia Stephens

Mia Stephens is an Advisory Product Manager for JMP Statistical Discovery LLC. Prior to joining JMP, she was an adjunct professor of statistics at the University of New Hampshire and a founding member, statistical trainer and consultant with the North Haven Group. Mia has taught and consulted within a variety of industries, and is a co-author of four books, including Building Better Models, Visual Six Sigma, and JMP Start Statistics. She is also the instructor of the free online course, Statistical Thinking for Industrial Problem Solving.


Inbal Yahav

Inbal Yahav is a faculty member at Tel Aviv University's Coller School of Business, Israel. Her interests lie on the interface between data mining and operations research, with applications in healthcare.

Kenneth C. Lichtendahl Jr.

Kenneth C. Lichtendahl Jr. is an Associate Professor of Business Administration at the University of Virginia’s Darden School of Business. He specializes in teaching data science to MBA students with R. He was recognized by The Case Centre as its 2015 Outstanding Case Teacher for his course Data Science in Business. His research focuses broadly on making, evaluating, and combining forecasts and has been published in leading academic journals such as Management Science.

Peter Gedeck

Peter Gedeck is is at the forefront of the use of data science in drug discovery. He is a Senior Data Scientist at Collaborative Drug Discovery, which offers the pharmaceutical industry cloud-based software to manage the huge amount of data involved in the drug discovery process. Drug discovery involves the exploration and testing of huge numbers of molecule combinations, and much of that testing takes place analytically, hence the need for robust software to handle the data and provide a framework for analyzing it. Peter’s specialty is the development of machine learning algorithms to predict biological and physicochemical properties of drug candidates. Prior to this, he worked for twenty years as a computational chemist in drug discovery at Novartis in the United Kingdom, Switzerland, and Singapore. His research interests include the application of statistical and machine learning methods to problems in drug discovery, clinical research and meta-analysis.

Amit V. Deokar

Amit V. Deokar, PhD, is Chair of the Operations & Information Systems Department and an Associate Professor of Management Information Systems at the Manning School of Business at University of Massachusetts Lowell. Since 2006, he has developed and taught courses in business analytics, with expertise in using the RapidMiner platform. He is an Association for Information Systems Distinguished Member Cum Laude.

Kuber Deokar

Mr. Kuber Deokar is Data Science Lead at UpThink EduTech Services Pvt. Ltd. (Pune, India). He holds a Masters degree in Statistics from the University of Pune, India, where he also taught undergraduate statistics. He has earned two PASS certifications in Analytics for Data Science and Programing from (an Elder Research company). Kuber handles and is responsible for the coordination of online courses and ensures seamless interactions between the management teams, course creators, course instructors, teaching assistants, and students. He has over 14 years of experience in course designing, development and delivery. He teaches Predictive Analytics and Statistical Modeling courses at The Institute for Statistics Education at Kuber has a special interest in Machine Learning, Statistical Modeling, SQL, R, Python and software development ideation to execution.

Muralidhara Anandamurthy

Muralidhara is an Academic Ambassador with JMP, a division of SAS. He is a technical advocate of JMP for Indian academic markets and is responsible for seeking and supporting new customers.

He has served more than 20 years in Analytics and Data Science Industry and worked for Genpact, Target and Danske.