Chad Bhatti

Chad Bhatti

Email Chad Bhatti

Currently teaching:
Supervised Learning Methods

Chad R. Bhatti is a Principal Data Scientist at Citizens Bank. He has worked in data science and modeling in both front-end (marketing) and back-end (risk) in the banking industry for over fifteen years. Prior to working in the banking industry he was a National Science Foundation VIGRE postdoctoral researcher in the Department of Mathematics at Tulane University. He has taught graduate and undergraduate courses in the traditional areas of statistics, e.g. mathematical statistics, linear regression, and generalized linear models, and in their applications, e.g. introductory and advanced modeling courses and topics courses like financial modeling. Dr. Bhatti is trained in applied mathematics and statistics and has a PhD in Computational Statistics from Rice University.


Anil Chaturvedi

Anil Chaturvedi

Email Anil Chaturvedi

Currently teaching:
Unsupervised Learning Methods

Anil Chaturvedi has over 25 years of professional experience at companies such as AT&T Bell Labs, Kraft Foods, Capital One, and Accenture. He has provided consulting services to Bank of America, Fannie Mae, Johnson & Johnson, and Proctor & Gamble. Chaturvedi's general research interests include the areas of multivariate analysis – multi-linear models, information mining, and business insights. He co-authored a book, Mathematical Tools for Applied Multivariate Analysis, with the late Professor Paul Green (University of Pennsylvania) and Professor J. Douglas Carroll (Rutgers University). Chaturvedi has patented and published analytical methods for direct marketing, information mining, market segmentation, new product development, product positioning, customer loyalty, consumer promotion mix optimization, and brand btrategy. He earned his PhD from Rutgers University and PGDM from IIM Ahmedabad, India.


Carrie Dugan

Carrie Dugan

Email Carrie Dugan

Currently teaching:
Math for Data Scientists

Carrie Dugan has held a variety of positions instructing and writing curriculum for all undergraduate levels of online mathematics courses. In addition to her teaching experience, she has numerous years of actuarial experience working with both defined benefit pension plans and self-funded health care plans. Some of her current research interests include character theory, graph theory, and game theory. She holds a PhD in pure mathematics from Kent State University and a BS in mathematics with a minor in computer science from Marshall University.


Lawrence Fulton

Lawrence Fulton

Email Lawrence Fulton

Currently teaching:
Applied Statistics with R

Lawrence Van Fulton is an associate professor at Texas State University. His research interests include the application of machine learning, simulation, optimization, statistics, and decision science to aeromedical evacuation, sustainability, and healthcare in general. Currently, he is applying machine learning techniques for classification of brain imagery. He has published in journals including Multivariate Behavioral Research, Pain, Interfaces, Simulation, IIE Transactions on Healthcare Systems Engineering, Journal of Healthcare Management, Journal of Nursing Administration, and many others. Dr. Fulton served a quarter of a century in the U.S. Army Medical Department, attaining the rank of colonel prior to his retirement. His earned PhD in management science is from the University of Texas at Austin, and he holds five separate masters degrees, including a master of science in statistics from UT Austin.


Philip Goldfeder

Philip Goldfeder

Email Philip Goldfeder

Currently teaching:
Math for Data Scientists

Philip Goldfeder has worked as a business consultant with Booz & Company (formerly Booz Allen and Hamilton) and as an educator for both traditional and online universities. He is currently a faculty member at several online universities. His consulting specialization is mergers and acquisitions, primarily in the spirits and automobile industries. He earned a PhD in applied mathematics from Northwestern’s Robert R. McCormick School of Engineering and Applied Science.


Alexander Kline

Alexander Kline

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Alexander Kline is a leader capable of thriving in stressful environments with experience in Operations Research as well as combat operations in the US Army. He has led analytical efforts supporting finance, manpower, national defense, military operations, and resource allocation. His expertise lies in the design, implementation, and analysis of algorithms to solve complex problems. Kline has given lectures on Missile Defense research, heuristic and metaheuristic algorithms, multivariate analysis, and queueing theory. He has published articles in peer-reviewed journals and in conference proceedings, and has several additional articles in some phase of the publication process. Kline believes in focused perseverance and he is committed to excellence in all that he does.


William Mickelson

William Mickelson

Email William Mickelson

Currently teaching:
Supervised Learning Methods

William T. Mickelson is an applied statistician with more than 25 years of statistical consulting, measurement, evaluation and survey research experience in both academia and industry. Mickelson was on the faculties of the University of Idaho, the University of Nebraska–Lincoln, and the University of Wisconsin–Whitewater. He has also worked with the RAND Corporation as a policy analyst and with Chamberlain Research Consultants of Madison, Wisconsin, as a senior consultant and division director. Mickelson has taught across the entire spectrum of research and statistical topics, including applied statistics, probability, modern robust and nonparametric methods, multivariate methods, regression, experimental design and ANOVA and mathematical and statistical modeling. His current research interests include the robustness of commonly used statistical tests and predictive models, the use of modern resampling and nonparametric statistical methods and the teaching and learning of statistical reasoning, thinking and literacy. Mickelson received his PhD in educational psychology in quantitative methods from the University of Wisconsin–Madison and a master’s degree in statistics from Michigan State University.


Melvin Ott is owner and president of Melvin Ott & Associates, LLC, a statistical and economic consulting firm. He has made presentations for private companies on predictive modeling in healthcare, banking, and market research. Ott has worked with predictive models for more than thirty years. His consulting practice focuses on applications in healthcare payment methodologies and expert witness testimony plus adjunct teaching at several universities in statistics, mathematics, and market research. Previously, Ott was director of research and database for Ingenix, Inc., director for data management at a large medical center (responsible for SAS online access to the medical center data and performed the survival analysis for the kidney transplant program) and was a director for reimbursement for a Blue Shield plan. He is a SAS programmer and Visual Basic programmer with online logistic regression and simulation applications. He holds a PhD in statistics from Oregon State University and a master's degree in mathematics from Utah State University.


Jamie Riggs

Email Jamie Riggs

Currently teaching:
Applied Statistics with R

Jamie Riggs works with the Statistics for Physical and Engineering Science Institute and specializes in statistical methods used in astronomy, physics, and engineering. She has worked with researchers from the Adler Planetarium, the American Association of Variable Star Observers, the Laboratory for Atmospheric and Space Physics, and the National Radio Astronomy Observatory on numerous projects. Riggs was with Sun Microsystems as a senior staff statistician, where she was co-issued three patents, each involving statistical methodologies. She worked on warranty cost estimating using general mixed models, tape library reliability and survivability, spare parts logistics time and location forecasting, and a number of designed experiments. Riggs worked as a mathematical scientist at The Boeing Company, having worked with W. Edwards Deming and his associates. Riggs worked with the Forecast Systems Laboratory of the National Oceanic and Atmospheric Administration on meteorological forecasting. Riggs earned her PhD in applied statistics and research methods from the University of Northern Colorado and MS degrees in applied mathematics and statistics and physics from Wichita State University.


Syamala Srinivasan

Syamala Srinivasan

Email Syamala Srinivasan

Currently teaching:
Applied Statistics with R

Syamala Srinivasan has over 30 years of industrial and academic experience in analytics applied to solve business problems. Currently, Syamala is leading the business analytics practice at CGN Global, Inc. She also teaches at National Louis University in the department of mathematics. Prior to CGN, she worked at Caterpillar Inc., at various technical and management positions for 22 years. She started and developed the Department of Analytics and was the director of analytics before retiring from Caterpillar, focusing on developing and deploying analytical solutions to complex business problems in the entire value chain of product development, manufacturing, supply chain, marketing, and sales. She developed innovative techniques when solving complex business problems and received two U.S. patents. One of those patents was used to spin off a new startup company. Her prior academic appointments include Bradley University, Chicago State University, Northern Illinois University, and Colorado State University. Srinivasan has a PhD in statistics and a MS in statistics from Colorado State University. She has several management and leadership certificates from Wharton & Kellogg’s school of business.


Irene Tsapara

Email Irene Tsapara

Currently teaching:
Applied Statistics with R

Irene Tsapara has worked in the financial industry for 5 years as a financial engineer, building financial algorithms for trading systems at Goldman Sachs/Hull Trading and Hedge Fund Research company. She has taught for over 20 years in universities across the US and Europe and speaks English and Greek fluently and she has a good knowledge of French and Spanish. Tsapara earned her PhD in mathematical computer science from University of Illinois with a focus in computational learning theory and universal algebra. She holds a masters in computer science from University of Illinois and a bachelors in mathematics from University of Patras.


Donald Wedding

Donald Wedding

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Donald Wedding has over twenty years of experience in the field of Data Science. He has worked in a variety of industries including Banking, Insurance, and Telecom. He has also spent time as a freelance consultant and spent over 10 years working at the SAS Institute. He currently works as a Customer Facing Data Scientist for Data Robot. Dr. Wedding joined the faculty of Northwestern in 2013 and has developed and taught a variety of courses. He is a frequent presenter on analytic topics at conferences, user groups and industry meetings. He is particularly interested in segmentation and cluster analysis and machine learning algorithms. He received his PhD in Engineering Systems from the University of Toledo, where he specialized in machine learning and expert systems. He has an MS in Engineering from the University of Toledo, an MS in Management from the University of Akron and an MS in Data Mining from Central Connecticut State University. He is also a graduate of the Stonier Graduate School of Banking.


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