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Advisory Committee

Advisory Committee Created

The mission of the School of Statistics Advisory Board is to share its expertise to help the School achieve its mission through assisting with strategic planning, strengthening external relations, and participating in mentoring opportunities.

The specific purposes of membership on the Advisory Board include:

  1. Develop an understanding of the goals and mission of the School.
  2. Assist in the development and evaluation of short and long term goals for the School to ensure that the School’s programs remain relevant.
  3. Assist in the promotion and recognition of the School, both locally and nationally.
  4. Assist in the identification of opportunities, such as internships, consulting, or research collaborations, for the School’s students and faculty.
  5. Identify and involve alumni, friends, and others who may have an interest in and desire to support the mission of the School.

Current Committee Members

Sthitie Bom

Sthitie Bom is a director of Data Analytics and Reporting Systems group for the wafer factories at Seagate Technology. She started at Seagate in 2003 and has been a critical leader in the evolution of systems that support business intelligence and analytics for manufacturing.  She architected a program of "Learning Cycles" in collaboration with the UMN Departments of Statistics and Computer Science whose primary mission is to engage students with Seagate software engineers and statisticians to solve real-world, deploy-able solutions for autonomous factory monitoring.  She did her Bsc. in Management Information Systems from Metropolitan State University and MSc. in Software Engineering from University of Minnesota.  She also serves on the board for the Friends of St Paul Public Library and manages the education fund that she established which supports the middle and high school education for the underprivileged in Nepal.

Stephen G. Eick

Stephen G. Eick is a thought leader in the study of visual analytics and visual business intelligence. As an entrepreneur, Dr. Eick also founded SSS-Research and Visual Insights. His leadership and innovation have resulted in numerous best-in-class product awards and a coveted Smithsonian Award for eBizInsights. Dr. Eick also served as Deputy Director, National Center for Data Mining at the University of Illinois in Chicago. He had an extensive career with Bell Laboratories and managed their Visualization Research Group. He holds 40+ patents focused on visualization and visual analytics. Dr. Eick earned a PhD in Statistics from the University of Minnesota, an MS degree in Mathematics from the University of Wisconsin and a BA in Mathematics from Kalamazoo College.

Nathan Hubbell

Nathan is a 2nd Vice President in the Personal Insurance Research & Development department at Travelers Insurance.  He has been with Travelers for 13 years in a variety of actuarial and statistical modeling positions.  Nathan is a Fellow of the Casualty Actuarial Society (FCAS), and a graduate of St. Olaf College, where he majored in Mathematics with a Statistics concentration and Molecular Biology.

Tom Keenan

Tom Keenan is currently a Sr. Engineering Program Manager of Manufacturing Data Analytics for the Neuromodulation Business Unit of Medtronic, PLC in Columbia Heights, MN.  He has more than 25 years of experience at Medtronic working as an industrial statistician and Lean Sigma Master Black Belt.  He completed a Bachelor of Statistics degree from the University of Minnesota Institute of Technology (now the College of Science & Engineering) in 1986 and an M.S. degree in Statistics from the University of Minnesota in 1990.  He is an adjunct instructor in the School of Engineering at the University of St. Thomas (St. Paul, MN).

Lynn Lin

Lynn Lin was raised in Taiwan in humble circumstances, but excelled in his studies. He moved to Minnesota and completed his PhD in the School of Statistics in 1975. Dr. Lin was always dedicated to statistical solutions for real-world problems, so after a brief spell on the faculty he joined Pillsbury and then Booz, Allen Hamilton. He left to form his consulting company in 2002. He is best-known for BASES, the new-product sales forecasting methodology he invented, and which now has an 85% market share. Dr. Lin is a regular speaker at educational events for quantitative professionals. The School has benefited from his subvention of the summer internships that have exposed so many of our graduate students to the uses and applications of statistics in the real world.

Shefali Mehta

Shefali Mehta focuses on improved decision-making, management and resource usage in the agricultural and environmental sectors. She received her PhD in Agricultural and Applied Economics from the University of Minnesota, her MPhil in Economics from Cambridge University and a BA in Economics from New York University. Dr. Mehta currently works in Syngenta’s R&D group where she leads a company-wide operations transformation across the global seeds business. Prior to that, she has worked in a range of roles across private, public and non-profit sectors including such organizations as McKinsey and Company, the MN Office of Higher Education, the Federal Reserve Bank of Minneapolis and the American Cancer Society. She also serves as a National Board member of the conservation organization Pheasants Forever.

Bret Musser

Bret Musser is currently a Director at Merck Research Laboratories, in the department of Quantitative Pharmacology and Pharmacometrics.  Since joining Merck in 1998, Bret has driven the application of statistical principles across clinical development.  He has experience spanning from preclinical studies through large outcomes trials.  Bret currently works on the development and application of advanced mathematical models in drug discovery and development, and leads a group responsible for developing new methodology used to address critical questions in drug development.  Bret’s current research interests focus on clinical trial simulation and decision theory. Bret is active in the ASA, including the newly formed Pharmacometrics SIG.

Rich Scamehorn

Rich Scamehorn uses his 20 years of Research and Insights experience to lead InContext Solutions' Insights function in designing primary market research studies utilizing virtual store simulation techniques to address clients’ business issues. Prior to co-founding InContext Solutions in 2009, Rich led Virtual Store and In-Store Testing at General Mills for the Fortune 200 company. He also managed their Advanced Analytics primary market research group during his 8 years with General Mills. Rich has a B.A. in Mathematics from Macalester College and a M.S. in Statistics from the University of Minnesota.

Lawrence Thibodeau

Lawrence A. Thibodeau PhD, is President and owner of Strategic Advocacy Inc., a company he founded in 2004 upon retirement from pwc. While at pwc, Dr. Thibodeau was partner-in-charge of the Financial Advisory Services Global and Americas Pharmaceutical practice, and the Economics and Statistics Group. Dr. Thibodeau holds a PhD in Statistics from the University of Minnesota, 1977, was on the Harvard Biostatistics Faculty (1977-1980), was a Visiting Research Scientist at ETS in Princeton (1980- 1981), taught at George Washington University as Adjunct Faculty (1988-1991), and served as a US Army officer in Vietnam (1966-1973).

Stephen Tich

Stephen Tich currently serves as COO of Ygrene Energy Fund and is responsible for leading the construction of operating platforms to introduce new products, expand market territory, develop strategic partnerships, and support growth. Stephen possesses extensive executive leadership experience in numerous financial services industries including insurance, mortgages, payments, and specialty finance that included 6 years based in Hong Kong. He most recently served as COO, Global Insurance at HSBC, leading insurance operations and IT across fifteen countries in Asia, LatAm, and Europe.  His HSBC tenure totaled 15 years of progressive senior-level operating roles with P&L accountability and he achieved $12B in mortgage originations and over $2B in added insurance revenue. Prior to HSBC, Stephen spent 9 years at GE where he worked on its Corporate Audit Staff and was heavily engaged in its six sigma initiative. 

Throughout his career, Stephen excelled at translating strategy into operational design and is known for his ability to grow businesses and meet financial objectives by integrating digital and data capabilities to simplify operations and improve the customer journey. Stephen possesses an open and collaborative leadership style and builds diverse teams to accomplish challenging goals.

Stephen received his M.B.A. from Georgetown University and a B.A. degree in Statistics from the University of Minnesota.

Pat Whitcomb

Pat is the founding principal and president of Stat-Ease, Inc. Before starting his own business, he worked as a chemical engineer, quality assurance manager, and plant manager. Pat co- authored Design-Expert® software, an easy-to-use program for design and analysis of factorial, response surface, mixture, and combined experiments. He's provided training and consulting on the application of design of experiments (DOE) and other statistical methods for several decades. In addition, Pat is co-author of the books, DOE Simplified: Practical Tools for Effective Experimentation and RSM Simplified: Optimizing Processes Using Response Surface Methods for Design of Experiments, and has published many articles on DOE.

Emeritus Committee Members

David Olive

David Olive is a Mathematics professor at Southern Illinois University who received his Ph.D. in Statistics from the University of Minnesota in 1998. His research has developed practical methods for analyzing data, including robust statistics, methods for visualizing data, extending least squares variable selection and inference methods to a large class of regression models, and large sample prediction regions. Applying the prediction region to a bootstrap sample of the statistic results in a large sample confidence region (the percentile confidence interval is also a prediction interval for a future bootstrap statistic value). This result may lead to inference for complicated models such as variable selection models.