Biographical sketch
In 2016, I accepted a position as Chair of Uncertainty in the University of Liverpool School of Engineering. Previously, I was a senior scientist at Applied Biomathematics, a research firm in New York specializing in methods for environmental and engineering risk analysis, and also taught risk analysis and environmental systems modeling at Stony Brook University in the Department of Technology and Society within the College of Engineering and Applied Sciences. My research focuses on developing reliable mathematical and statistical tools for risk assessments and on methods for uncertainty analysis when empirical information is very sparse. I have a Ph.D. in ecology and evolution from the State University of New York, and am author of several books and around 200 other scholarly publications, including several software packages, in risk analysis and uncertainty propagation. I have served on many governmental and industry advisory panels, and on editorial boards for several scientific journals.
See biosketches for summary descriptions of various lengths written in the third person.
Research interests
My interests have to do with poor or sparse data and what we can do with it, including
assured or automatically verified calculations,
imprecise calculations, robust Bayes analysis, and distribution-free methods of uncertainty analysis,
dependency modeling and backcalculation strategies,
protecting privacy of patients, clients, and consumers during data release events,
statistical inference, the theory of measurement error, and the foundations of statistics,
detecting clusters in very small data sets,
image and shape analysis, and
risk communication.
These topics may seem disparate and unconnected, but they will each become crucial as the internet of things is realized and data collection becomes pervasive and intrusive. This change will produce data that are abundant with huge sample sizes but with limited precision. In the case of personalized medicine and individually targeted marketing, it will produce data sets of extremely small sample sizes. The methods developed to address these topics find applications throughout science and engineering. Most of my work has been with applications in
engineering reliability,
public health research and epidemiology,
population dynamics and conservation biology, and
environmental risk analysis.
If you are interested in any of these topics or these domains of applications, I'd love to hear from you. You can email me at sandp8(at)gmail(dot)com. If I don't respond, you may try following up by phone at +44 (0) l 5 l 795 8039. From a land line in the United States and Canada, this would be 0 l l-44-l 5 l-795-8039.
Recent papers
Gray, A., S. Ferson. V. Kreinovich, and E. Patelli. 2022. Distribution-free risk analysis. International Journal of Approximate Reasoning 146: 133-156.
Ferson, S., and M. De Angelis. 2021. Computing with confidence [editorial]. International Journal of Approximate Reasoning 137 (2021) 67–68.
Le Carrer, N., and S. Ferson. Beyond probabilities: A possibilistic framework to interpret ensemble predictions and fuse imperfect sources of information. Quarterly Journal of the Royal Meteorological Society 147: 3410-3433 https://doi.org/10.1002/qj.4135
Gray, N., D. Calleja, A. Wimbush, E. Miralles-Dolz, A. Gray, M. De Angelis, E. Derrer-Merk, B.U. Oparaji, V. Stepanov, L. Clearkin, S. Ferson. 2020. Is no test is better than a bad test? Impact of diagnostic uncertainty in mass testing on the spread of COVID-19. PLOS One 15: e0240775. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0240775.
Balch, M.S., R. Martin, and S. Ferson. 2019. Satellite conjunction analysis and the false confidence theorem. Proceedings of the Royal Society A 475. https://royalsocietypublishing.org/doi/10.1098/rspa.2018.0565
Gray, N., S. Ferson, M. De Angelis, D. Calleja. 2019. A problem in the Bayesian analysis of data without gold standards. Proceedings of the 29th European Safety and Reliability Conference (ESREL), 10.3850/978-981-11-2724-3_0458-cd. https://bit.ly/2WltrQc
Le Carrer, N., S. Ferson, and P.L. Green. 2019. Optimising cargo loading and ship scheduling in tidal areas. European Journal of Operational Research 280: 1082–1094. https://doi.org/10.1016/j.ejor.2019.08.002
Ferson, S. 2017. Estimating rare-event probabilities without data. Proceedings of the 12th International Conference on Structural Safety & Reliability (ICOSSAR), 6-10 August 2017, Wien, Austria.
Ferson, S. and K. Sentz 2016. Epistemic uncertainty in agent-based modeling. Proceedings of the 7th International Workshop of Reliable Engineering Computing: Computing with Polymorphic Uncertain Data, 15-17 June 2016, Ruhr Universität, Bochum, Germany.
Ferson, S., J. O'Rawe, A. Antonenko, J. Siegrist, J. Mickley, C. Luhmann, K. Sentz, A. Finkel. 2015. Natural language of uncertainty: numeric hedge words. International Journal of Approximate Reasoning 57: 19-39. http://www.ramas.com/health/hedges.pdf
O'Rawe, J.A., S. Ferson and G.J. Lyon. 2015. Accounting for uncertainty in DNA sequencing data. Trends in Genetics 31: 61-66. DOI:http://dx.doi.org/10.1016/j.tig.2014.12.002).
Ferson, S., J. O’Rawe and M. Balch. 2014. Computing with confidence: imprecise posteriors and predictive distributions. Proceedings of the International Conference on Vulnerability and Risk Analysis and Management and International Symposium on Uncertainty Modeling and Analyis. http://www.ramas.com/health/icvram2014.pdf
Ferson, S. 2014. Model uncertainty in risk analysis. Proceedings of the 6th International Workshop of Reliable Engineering Computing: Reliability and Computations of Infrastructures, 25–28 May 2014, IIT, Chicago, Illinois, pages 27–43. http://rec2014.iit.edu/papers/Paper_Ferson.pdf
Xiang, G., J. O’Rawe, V. Krienovich, J. Hajagos, and S. Ferson. 2014. Protecting patient privacy while preserving medical information for research. Proceedings of the 6th International Workshop of Reliable Engineering Computing, 25–28 May 2014, IIT, Chicago, Illinois, pages 281–293. http://rec2014.iit.edu/papers/Paper_Xiang.pdf
Ferson, S., M. Balch, K. Sentz, and J. Siegrist. 2013. Computing with confidence. Proceedings of the 8th International Symposium on Imprecise Probability: Theories and Applications, edited by F. Cozman, T. Denoeux, S. Destercke and T. Seidenfeld. SIPTA, Compiègne, France. http://www.ramas.com/health/cboxes.pdf
Beer, M., S. Ferson, and V. Kreinovich. 2013. Imprecise probabilities in engineering analyses. Mechanical Systems and Signal Processing 37: 429. http://www.ramas.com/health/ip.pdf
Ferson, S., and J. Siegrist. 2012. Verified computation with probabilities. Pages 95-122 in Uncertainty Quantification in Scientific Computing, edited by A. Dienstfrey and R.F. Boisvert, Springer, New York. http://www.ramas.com/health/verifiedprob.pdf
Akçakaya, H.R., S. Ferson, M.A. Burgman, D.A. Keith, G.M. Mace, and C.R. Todd. 2012. Commentary: IUCN classifications under uncertainty. Environmental Modelling & Software 38: 119–121.
Ferson, S., and J. Siegrist. 2011. Statistical inference under two structurally different approaches to interval data. Pages 29-37 in Vulnerability, Uncertainty, and Risk: Analysis, Modeling, and Management, edited by B.M. Ayyub. ASCE, Reston, VA. http://www.ramas.com/health/two.pdf
Sentz, K., and S. Ferson. 2011. Probabilistic bounding analysis in the quantification of margins and uncertainties. Reliability and Engineering System Safety 96: 1126–1136.
Siegrist, J., S. Ferson, J. Goode, and R. Grimson. 2011. Statistically detecting clustering for rare events. Proceedings of the International Conference on Vulnerability and Risk Analysis and Management with the Fifth International Symposium on Uncertainty Modeling and Analysis , Hyattsville, Maryland, American Society of Civil Engineers.
Beer, M., and S. Ferson. 2011. Fuzzy probability in engineering analyses. Proceedings of the International Conference on Vulnerability and Risk Analysis and Management with the Fifth International Symposium on Uncertainty Modeling and Analysis, Hyattsville, Maryland, American Society of Civil Engineers.
Ferson, S., and J. Mickley. 2011. Uncertainty arithmetic on Excel spreadsheets: add-in for intervals, probability distributions and probability boxes. Proceedings of the International Conference on Vulnerability and Risk Analysis and Management with the Fifth International Symposium on Uncertainty Modeling and Analysis, Hyattsville, Maryland, American Society of Civil Engineers.
Enszer, J.A., Y. Lin, S. Ferson, G.F. Corliss, and M.A. Stadtherr. 2011. Probability bounds analysis for nonlinear dynamic process models. AIChE [American Institute of Chemical Engineers] Journal 57: 404–422.
Other publications about p-boxes and probability bounds analysis
Research funding organizations
Hearty thanks are owed for research support from the UK Research and Innovation (including the Engineering and Physical Science Research Council, the Economic and Social Research Council, and the Medical Research Council), National Institutes of Health (including the National Library of Medicine, the National Center for Advancing Translational Sciences, the National Institute of Allergy and Infectious Diseases, the National Institute of Nursing Research, the National Institute of Environmental Health Sciences, and the National Institute of General Medical Sciences), the National Aeronautics and Space Administration (NASA), Sandia National Laboratories, the Electric Power Research Institute, the U.S. Army Corps of Engineers, the National Science Foundation. Of course none of these generous funders is responsible for my craziness.
Other Fersons
There is another Scott Ferson who is a blogger and a politically active attorney in Massachusetts at Liberty Square Group.
Susan Ferson, sometimes S. Ferson or S.S. Ferson, is a medical researcher at Children’s Hospital of Pittsburgh.
Wayne Ferson is a professor of finance in the Marshall School of Business at the University of Southern California.
David Ferson is a physician at the University of Texas MD Anderson Cancer Center and publishes on brain tumors.
(Owing to an unnoticed typographical error, Scott A. Ferson and S.A. Ferson seem to refer to me.)
