Kelley School of Business, Indiana University
Frank Acito is Professor of Marketing and the Max Barney Distinguished Teaching Fellow in the Kelley School of Business at Indiana University. His current teaching is focused on predictive analytics and data mining tools in courses for graduate students and corporate professionals. He is the co-founder and former director of the Institute of Business Analytics at the Kelley School. His research interests are in marketing research methods and tools, the application of research methods to management decisions, and marketing strategy. His publications on these topics have appeared in the Journal of Marketing Research, Journal of Marketing, Journal of Consumer Research, Multivariate Behavioral Research, Decision Sciences, the Academy of Management Journal, Industrial Marketing Management, and other professional journals. Acito has served as Associate Dean for Academics and Associate Dean for Technology in the Kelley School. He also served as chair of the Marketing Department at the Kelley School for more than 11 years. During that time, he established the Center for Education and Research in Retailing with a substantial grant from Sears, Roebuck & Company. He then served as chair of the Kelley School’s Doctoral Programs for four years. He received the Distinguished Teaching Award from the Doctoral Student Association in 2002 and again in 2005. Acito developed and taught in executive programs at Infosys, Allegiant, Abbott Nutrition, Eli Lilly and Company, IBM, Rolls-Royce Allison, 3M Company, and Ingersoll Rand. He has consulted with Chrysler, IBM, Lilly, Kocolene Oil, and Walker Research. Acito holds a Bachelor of Electrical Engineering from Cornell University and an MBA and PhD from the University at Buffalo.
B. Michael Adams
Retired, The University of Alabama
Mike Adams served as Professor of Applied Statistics at The University of Alabama, where he was a faculty member for over 25 years. His primary interests are in the areas of business analytics, statistical quality control and statistical education. His research appears in such journals as Technometrics, Journal of Quality Technology, Journal of Statistical Computation and Simulation, and Quality Engineering, and he has contributed to reference texts such as the Handbook of Statistical Methods for Engineers and Scientists, The Encyclopedia of Quality and Reliability and The Encyclopedia of Science and Technology. In addition to publishing research, Adams collaborates on corporate projects. He has had the pleasure of working with organizations such as NASA, Mercedes-Benz USA, U.S. Pipe and Steel, U.S. Veterans Administration, Wal-Mart and AT&T, among others. He is involved with statistical education initiatives, including the Alabama Quantitative Literacy Program (activity-based statistics lessons for K-12 teachers), the development of distance learning courses, and study abroad programs in China. In 2013, two student teams under his direction received honors at the SAS Analytics Shootout national data mining competition. One team took first place and the other received an honorable mention (top 6 team). Adams has a PhD in statistics from the University of Louisiana – Lafayette, a Master of Science in mathematics from the University of Arkansas, and a Bachelor of Science in mathematics from the University of Louisiana – Monroe.
Dan Beitzel is the Analytics Manager at First Solar, the largest thin-film solar module manufacturer in the world, leading a team of statisticians and engineers who provide innovative analytics via JMP and SAS. His JMP experience began with version 6, which he used for the automation of data extraction, analysis and visualization. He was instrumental in JMP adoption at First Solar, having developed several JMP applications for key processes throughout the company. Beitzel is an ASQ certified Six Sigma Black Belt and an instructor for a variety of in-house courses in statistical analysis, DOE and JMP scripting.
Nathan Clark is a Senior Systems Scientist with 14 years of experience in research and development of veterinary diagnostic products. Starting with JMP 5, Clark has grown with the software and is now responsible for mining data in several locations and developing innovative analysis methods to decipher the story contained in the data. His main focus is on the functional breakdowns of biological and engineering systems and merging that data together for a complete system understanding. In his current position, Clark guides R&D teams for optimized visual analytics and uses JSL to create software tools for streamlining analyses. He holds a BA in marine biology and a BS in environmental science with a minor in chemistry from the University of Maine, Machias.
Colorado Department of Public Health and Environment
Elaine Daniloff is an epidemiologist at the Colorado Department of Public Health and Environment where she uses JMP daily to measure and track the AIDS epidemic. She uses JMP for infectious disease surveillance, incidence estimates, statistical analysis and visualization of results. Daniloff discovered JMP in 1992 while working as a research assistant at National Jewish Health’s Division of Environmental and Occupational Health Sciences. She is currently starting up the first Denver (CO) JMP Users Group. She studied economics at Beloit College and received her Bachelor of Science in applied sociology from Purdue University and a master’s degree in public health from the University of Colorado.
Brad Foulkes is a Principal Engineer of Lifing Analytics in the Power Services division of GE Power, where he works on predictive and prescriptive analytics for power plant equipment. He has worked in several businesses across General Electric, including aircraft engines, circuit breakers, motors and gas turbines, and has held several roles, including design engineer, DFSS Black Belt and reliability engineer. Foulkes has bachelor’s and master’s degrees in mechanical engineering from WPI. He is a daily user of JMP and JMP Pro, regularly employing the Reliability platform and several other modeling platforms, as well as using JSL to develop tools that help his team. In 2016, he was a founding member of the Upstate JMP Users Group in South Carolina.
Rachel Knoll is a Financial Analysis Manager at Cummins, a global power leader in diesel and alternative fuel engines, generator sets, and related components and technology. She was one of the first adopters of JMP at Cummins in 2006, and has since grown the user base through the development of scripts and add-ins that significantly increase efficiency. Knoll and her team regularly use JMP for data extraction, cleansing, and transformation, as well as predictive analytics and visualization. Knoll has a bachelor’s degree in statistics from Purdue University and is currently pursuing a master’s degree in finance from Indiana University.
Rob Lievense leads a group that supports the consumer health care research and development department at Perrigo with statistical analysis, data visualization, advanced modeling, data-driven Quality by Design for product development, and structured experimental design planning. He has more than 20 years of manufacturing experience in the automotive industry and more than eight years of experience in the pharmaceutical industry. Lievense has presented at major conferences including Discovery Summit and the annual conference of the American Association of Pharmaceutical Scientists. He is currently the Principal Statistician for CHC Research and Development at Perrigo, as well as an active professor of statistics at Grand Valley State University located in Allendale, Michigan.
Andrew Parker is a Data Science and Analytics Manager at Boeing, the world’s largest aerospace and defense company. He manages a team of data scientists supporting Commercial Airplanes’ Commercial Aviation Services (CAS) division. His team uses a variety of analytical techniques to provide business solutions to several CAS organizations. Parker has also worked in Supplier Management Finance as a data scientist, supported Airplane Development Estimating, and worked in 787 Program Estimating. He has been using JMP since 2011 and established it as the gold standard of analytics software for the predictive modeling team in Supplier Management, where it is used for its modeling platform, dynamic visualization capacity, and customization through scripting. He studied mathematics and economics at University of Puget Sound and received his master’s in applied statistics from Colorado State University.
Philip J. Ramsey
North Haven Group
Philip J. Ramsey is the owner of the North Haven Group, a firm offering full-service statistical training and consulting in all levels of Six Sigma, as well as comprehensive training in design of experiments and predictive analytics. Ramsey is also a Principal Lecturer in the Department of Mathematics and Statistics at the University of New Hampshire (UNH). He has held the following relevant industrial positions: Senior Engineer for Materials and Processes Development, McDonnell Douglas, St. Louis, MO; Staff Scientist/Statistician, Alcoa Technical Center, Pittsburgh, PA; and Statistician/Senior Engineer, Rohm & Haas Electronic Materials (now Dow), Marlboro, MA. Ramsey has a PhD in statistics from Virginia Tech. He lives with his family and assorted pets in Brookline, New Hampshire.
Susan Roweton is a Research Manager in Medtronic’s Minimally Invasive Therapies Group. As a member of the Tissue Effect Research team within Surgical Innovations, she is responsible for continuous improvement of testing and data analysis methods. Roweton uses JMP for visualizing, mining and modeling critical performance data for energy-based vessel sealing devices, and she has facilitated the use of JMP by all Tissue Effect Research scientists and engineers for comprehensive analysis of data for regulatory submissions. Prior to her current role at Medtronic, Roweton was Manager of the Technology Development at Covidien Respiratory and Monitoring Solutions. She has 18 years of industrial experience in medical device research and development and, before joining Covidien, held roles of increasing responsibility in research and development at Ethicon, Inc. (Johnson and Johnson). Roweton holds a PhD in polymer science from the University of Connecticut, an MS in bioengineering from Clemson University and a BS in biomedical engineering from The Johns Hopkins University.
John Sall is a co-founder and Executive Vice President of SAS, leader in business analytics software and largest independent vendor in the business intelligence market. He also leads the JMP business division, which creates interactive and highly visual data analysis software for the desktop.
Sall joined Jim Goodnight and two others in 1976 to establish SAS. He designed, developed and documented many of the earliest analytical procedures for Base SAS® software and was the initial author of SAS/ETS® and SAS/IML® software. He also led the R&D effort that produced SAS/OR® software, SAS/QC® software and Version 6 of Base SAS.
In the late 1980s, Sall saw a niche that SAS software was not filling. Researchers and engineers – whose jobs didn’t revolve solely around statistical analysis – needed an easy-to-use and affordable stats program. A new software product, today known as JMP, was launched in 1989 to dynamically link statistical analysis with the graphical capabilities of Macintosh computers. Now running on Windows and Macintosh, JMP continues to play an important role in modeling processes across industries as a desktop data visualization tool. It also provides a visual interface to SAS in an expanding line of solutions.
Sall was elected a Fellow of the American Statistical Association and the American Association for the Advancement of Science. He serves on the board of World Wildlife Fund and was a member of the board of The Nature Conservancy from 2002 to 2011, reflecting his strong interest in international conservation and environmental issues. He also serves on the advisory board of the Smithsonian National Museum of Natural History. He is a former member of the North Carolina State University (NCSU) Board of Trustees. In 1997, Sall and his wife, Ginger, contributed to the founding of Cary Academy, an independent college preparatory day school for students in grades 6 through 12.
He received a bachelor’s degree in history from Beloit College in Beloit, WI, and a master’s degree in economics from Northern Illinois University in DeKalb, IL. He studied graduate-level statistics at NCSU, which awarded him an honorary doctorate in 2003.
Ledi Trutna joined SAS in 2012 after 13 years as a consultant teaching statistics. She has been using JMP since version 3 and loves teaching with the software. Prior to consulting, she worked at AMD and Texas Instruments. While at Texas Instruments, she developed the catapult as a tool for teaching design of experiments and Statistical Process Control. She then shared that knowledge with others so that it could be adopted in many types of classes. She has a bachelor’s degree in biomedical engineering from Duke University.
Daniel Valente is a product manager for JMP, a business unit of SAS that specializes in data visualization software. In his current role, Valente defines product requirements and helps communicate product information to prospects and users. Before joining SAS, he completed an NIH post-doctoral fellowship at the Boys Town National Research Hospital. Valente holds a PhD in architectural sciences from Rensselaer Polytechnic Institute and has been a longtime JMP user.
Kevin White is the Applied Statistics Group Leader at Eastman, a global advanced materials and specialty additives company that produces a broad range of products found in items people use every day. Relying heavily on JMP Pro, he leads a team of statisticians who provide experimental design and other statistical modeling solutions in support of top company growth programs. White is an ASQ Certified Quality Engineer and a past chair of the ASQ Chemical and Process Industries Division. His JMP experience began with a student version over 25 years ago at the University of Tennessee, where he received his bachelor’s and master’s degrees in statistics.