​B.S. University of Virginia, 1980​M.E. University of Virginia, 1981​Ph.D. University of Virginia, 1986

William T. Scherer is an expert in systems engineering, stochastic control, and business analytics. Professor Scherer has served on the University of Virginia Systems Engineering Program faculty since 1986. He also consults with numerous organizations on the topics of systems thinking and business analytics applied to disparate organizations. He has authored and co-authored numerous publications (journal and conference papers, business cases, and book chapters) on intelligent decision support systems, transportation systems, stochastic control, and systems thinking. His current research focuses on systems engineering methodology, financial engineering and intelligent transportation systems. His co-authored book, How To Do Systems Analysis, was published by Wiley in 2007, and a follow-on book, How to Do Systems Analysis: Primer and Casebook, was also published by Wiley in 2016. He has strong interests in engineering education and has published papers on curriculum and pedagogy, and was awarded an Outstanding University of Virginia Faculty Award in 2007. He was also a Visiting Professor at the Darden Graduate School of Business in 2001-2002 and President of the IEEE Intelligent Transportation Systems (ITS) Society 2007-2008.


  • Outstanding Undergraduate Teaching Award in Systems Engineering, selected by students 2019 and 2020
  • TRB Best Paper Award - RYAN C. BOYER, WILLIAM T. SCHERER, and MICHAEL C. SMITH; Trends Over Two Decades of Transportation Research: A Machine Learning Approach 2017
  • Awarded the Jefferson Scholars Hartfield-Jefferson Teaching Award 2013
  • Awarded and All University Teaching Award from the University of Virginia in “recognition of excellent teaching and skill in motivating and inspiring students” 2006
  • Cited by Darden School of Business for Outstanding Performance in team teaching “Optimization models” 2002
  • Awarded the SEAS Rodman Scholars Teaching Award for 2001 for teaching excellence.
  • Awarded the Mac Wade Award for 1996/7 for outstanding service to School of Engineering and Applied Science.
  • Awarded the Lucien Carr Professorship of Engineering for 1995-1996 for outstanding contributions to undergraduate engineering education at the University.
  • Named the Distinguished Faculty at the University of Virginia in 1993 by the Student IMP Society.

Research Interests

  • Business Analytics and Decision Analysis
  • Computational Statistics and Simulation/Statistical Modeling
  • Stochastic Modeling
  • Optimization Models and Methods
  • Intelligent Transportation Systems
  • Sports Analytics

In the News

  • 3Cav Grant '21/'22: Applying Machine Learning and Artificial Intelligence to Personnel Selection and Staffing: Efficacy and Ethics

    Professors Yael Grushka-Cockayne [Darden], Jared Harris [Darden], and William Scherer [Systems Engineering]

    The goal of the study is to use machine learning/AI to quantify more accurate algorithms for scoring interviews, the goal is to develop predictive algorithms for scoring interviews for future success.


  • Fall '21 USEM: The Demon Haunted World- Critical Thinking for Science and Data in the Age of Information

    Professor William T Scherer

    Critical thinking requires the application of scientific principles to the evaluation of concepts such as conspiracy theories, paranormal beliefs, UFOs, mystics, etc., and disparate disciplines such as economics, urban planning, politics, medicine, and data science. This seminar explores the development of ‘new eyes’ - the ability to see the world in new ways and the development of rigor in reasoning about matters of fact in daily life.


    COVID Summer 2020 students helping UVa Health Scheduling - Clare Hammonds (BS SE 2021) and Soumya Chappidi (BS SE 2021)

  • President Jim Ryan drops in on Scherer and Bailey SYS 3034 Zoom Class

  • Honor the Future Panel "The Future of Finance: Cracking the Code to Healthy Financial Markets" 2019

    with Michael Gallmeyer [Commerce], Narges Tabari [Data Science], Michael Albert [Darden], William Scherer [SEAS], and moderator Alice Handy [Investure/UVIMCO]

  • 'Hooball 2018

    Should University of Virginia head football coach Bronco Mendenhall work his team harder in practice? Should he “go for it” more often on fourth downs, instead of punting? Where should Mendenhall and his staff focus their recruiting efforts?

    Some of the answers are coming from a place you wouldn’t expect: Academia. Specifically, UVA’s School of Engineering and Applied Science.

    For the past two years, UVA engineering students have been giving the coaching staff input derived from unique data analytics models they have created as part of yearlong capstone projects.

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  • Measuring Grit 2018

    To measure the grit of a football player requires at least two steps. First, you need to find the standard for what “grit” is made of. Then you can place a numerical value on what is basically an arbitrary word.

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  • Time to Rethink Professional Training 2018

    Traditional programs don’t provide the diversity of learning experiences that develop the kind of engineers society and employers actually need.

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Selected Publications

  • Extending the Markowitz model with dimensionality reduction: Forecasting efficient frontiers. 2021 Systems and Information Engineering Design Symposium (SIEDS). IEEE, 2021. ABS Alexander, Nolan, William Scherer, and Matt Burket
  • Portfolio design and management through state-based analytics: A probabilistic approach. Cogent Economics & Finance 8.1 (2020): 1854948. ABS Burkett, Matthew W., William T. Scherer, and Andrew Todd.
  • Exploring cognitive states: Temporal methods for detecting and characterizing physiological fingerprints. AIAA Scitech 2020 Forum. 2020. ABS Nicholas J Napoli, Mudit Paliwal, Stephen Adams, William T Scherer, Angela R Harrivel, Kellie D Kennedy, Chad L Stephens
  • A Fundamental Misunderstanding of Risk: The Bias Associated with the Annualized Calculation of Standard Deviation. Cogent Economics & Finance 8.1 (2020): 1857005. ABS Burkett, Matthew W., and William T. Scherer.
  • The Danger of Using Ratio Performance Metrics in System Evaluations. Systems Engineering in Context. Springer, Cham, 2019. 313-321. ABS Scherer, William T., and Stephen Adams.
  • "TIME TO RETHINK PROFESSIONAL TRAINING." ASEE Prism (2018) 27-6. ABS William Scherer, Michael Smith
  • "Generating Synthetic Bitcoin Transactions and Predicting Market Price Movement Via Inverse Reinforcement Learning and Agent-Based Modeling." Journal of Artificial Societies and Social Simulation (2018) 21-3. ABS K Lee, S Ulkuatam, P Beling, W Scherer
  • "On the Practical Art of State Definitions for Markov Decision Process Construction." IEEE Access (2018) 6. ABS William T Scherer, Stephen Adams, Peter A Beling
  • "Data, Insights, Models and Decision Making: Machine Learning in Context." [in Intuition, Trust, and Analytics, CRC Press] (2018) Adams, Stephen, Scherer, William, and Beling, Peter.
  • "Trends Over Two Decades of Transportation Research: A Machine Learning Approach." Transportation Research, Record (2017) 2614. ABS Boyer, Ryan C., William T. Scherer, and Michael C. Smith.
  • "A Human–Machine Methodology for Investigating Systems Thinking in a Complex Corpus." IEEE Systems Journal (2017) 7-24. ABS Ryan C Boyer, William T Scherer, Cody H Fleming, Casey D Connors, N Peter Whitehead
  • "Dynamic Scheduling for Veterans Health Administration Patients using Geospatial Dynamic Overbooking." Journal of Medical Systems (2017) 41-182. ABS N. Peter Whitehead Stephen Adams, William T. Scherer, K. Preston White Jr., Jason Payne, Oved Hernandez, Mathew S. Gerber
  • "Stepping back from the trees to see the forest: a network approach to valuing intelligence." Social Network Analysis and Mining 6.1 (2016) 72. ABS Smith, Christopher M., William T. Scherer, and Andrew Todd.
  • "Visual analysis to support regulators in electronic order book markets." Environment Systems and Decisions 36.2 (2016) 167-182. ABS Paddrik, Mark E., R. Hayes, A. Todd, and W Scherer
  • “Crossed and Locked Quotes in a Multi-market Simulation,” PLOS ONE (2016) ABS Todd, Andrew, Beling, P., and Scherer, W.T.
  • Systems Analysis Primer and Casebook, Wiley, 2016. Gibson, J.E., Scherer, W.T., Gibson, W.F., and MC Smith

Courses Taught

  • SYS 6001: Introduction to Systems Engineering
  • SYS 3034: Systems Performance Evaluation
  • SYS 4053/4054: Systems Engineering Capstone Course

Featured Grants & Projects

  • NSF Center for Visula and Decision Dynamics (CVDI)

    The Center for Visual and Decision Informatics (CVDI) conducts multidisciplinary, cross-institutional research to develop the visual and decision support tools and techniques that allow leaders to improve the way their organization's data are organized and interpreted. CVDI develops visualization and data analytics techniques for sectors including government, health care, sustainability, transportation, commerce, and finance. As part of its efforts, CVDI recognizes the importance of research related to ethics, accountability, and transparency, when data analytics has to function in increasingly complex and emerging contexts such as augmented intelligence and cybersecurity.

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  • NSF - Northrop Grumman

    IUCRC Center for Visual and Decision Informatics (CVDI): Model-Free Signal State-Space Detection


    Using geolocating to improve the service to veterans at VA Hospitals.

  • US Army Training and Doctrine Command

    Using systems thinking and machine learning to mine intelligence reports