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| Larry Shepp | |
|---|---|
| Name | Larry Shepp |
| Birth date | 1936 |
| Birth place | Newark, New Jersey |
| Death date | 2013 |
| Death place | Scottsdale, Arizona |
| Fields | Statistics, Applied Mathematics, Computerized Tomography |
| Workplaces | Bell Telephone Laboratories, Columbia University, Rutgers University |
| Alma mater | Princeton University, Columbia University |
| Doctoral advisor | William Feller |
Larry Shepp was an American statistician and mathematician known for foundational work in probability, statistical decision theory, and computerized tomography. He made influential contributions to the theory of stochastic processes, optimal stopping, and image reconstruction algorithms that linked theoretical statistics with applied problems in medical imaging and signal processing. His career spanned industry research at Bell Laboratories and academic appointments at Columbia University and Rutgers University, where he supervised doctoral students and collaborated widely across mathematics, physics, and engineering.
Born in Newark, New Jersey, Shepp completed undergraduate studies at Princeton University and pursued graduate work at Columbia University where he earned a Ph.D. under the supervision of William Feller. During this formative period he was exposed to the probabilistic traditions associated with Princeton University and Columbia University faculties, interacting with scholars connected to Andrey Kolmogorov’s school, the legacy of Norbert Wiener, and the statistical communities tied to Harvard University and University of California, Berkeley. His doctoral work situated him among contemporaries influenced by research at Bell Laboratories, Institute for Advanced Study, and collaborations reaching researchers at Stanford University.
Shepp began his professional career at Bell Telephone Laboratories, joining a research environment that included figures from Claude Shannon’s information theory lineage and experimental ties to AT&T. He later moved to academia, holding professorships at Columbia University and Rutgers University, where he taught courses connected to departments that interacted with New York University and Princeton University. His roles involved collaborations with researchers affiliated with Massachusetts Institute of Technology, Carnegie Mellon University, and the University of Pennsylvania. He served on editorial boards of journals associated with American Statistical Association and engaged with conferences organized by Institute of Mathematical Statistics and Society for Industrial and Applied Mathematics.
Shepp’s research encompassed probability theory, stochastic processes, sequential analysis, and the mathematics of image reconstruction. In probability he worked on problems related to the work of William Feller, Paul Lévy, and Joseph Doob, contributing to optimal stopping theory connected to Dynkin-style formulations and to sequential hypothesis testing in the spirit of Abraham Wald. In stochastic modeling he addressed questions related to random walks and Brownian motion that interfaced with results by Kiyoshi Itô and Andrey Kolmogorov.
In the realm of computerized tomography he collaborated with engineers and physicians to develop algorithms influenced by the Radon transform as studied by Johann Radon and computational techniques paralleling work at Los Alamos National Laboratory and Lawrence Livermore National Laboratory. He contributed to filtered back-projection methods, expectation-maximization algorithms related to Dempster–Laird–Rubin EM theory, and statistical models for Poisson data used in emission tomography reflecting practices emerging from Mayo Clinic imaging research and the National Institutes of Health. His work connected to algorithmic advances at Bell Labs, and mathematical frameworks from Courant Institute and California Institute of Technology researchers. Shepp coauthored interdisciplinary studies involving colleagues affiliated with Columbia-Presbyterian Medical Center and international centers such as Karolinska Institute.
He also advanced applied probability techniques relevant to actuarial contexts associated with Prudential Financial and telecommunications problems echoing themes from Shannon’s information theory. His collaborations crossed borders to include statisticians linked to University of Oxford, University of Cambridge, ETH Zurich, and Université Paris-Saclay.
Shepp received recognition from organizations that included the Institute of Mathematical Statistics and the American Statistical Association. He was invited to speak at meetings sponsored by the National Academy of Sciences and awarded fellowships connected to research bodies such as the National Science Foundation and institutes like the Institute for Advanced Study. He held visiting appointments at institutions including Massachusetts Institute of Technology, Stanford University, and University of California, Berkeley, and was cited in retrospectives alongside figures like Jerzy Neyman, Ronald Fisher, and John Tukey.
- Articles on stochastic processes and optimal stopping published in journals affiliated with the Institute of Mathematical Statistics and the American Statistical Association, often cited alongside work by Joseph Doob, William Feller, and Abraham Wald. - Papers on computational tomography and image reconstruction that interfaced with literature by Johann Radon, Dempster–Laird–Rubin, and contributors from Bell Laboratories and Courant Institute. - Collaborative works addressing EM algorithms, Poisson models for emission tomography, and implementations used in clinical contexts at institutions such as the Mayo Clinic and Johns Hopkins University.
Shepp’s personal life intersected with academic networks in the New York metropolitan area, fostering mentorship ties with students who later joined faculties at places like Rutgers University, Columbia University, and Princeton University. His legacy persists in curricula at departments connected to Courant Institute, Columbia University, and in applied programs at medical physics centers including Memorial Sloan Kettering Cancer Center and Massachusetts General Hospital. Posthumous recognition appears in memorial sessions at meetings sponsored by the Institute of Mathematical Statistics and in citations appearing across literature from University of Oxford to ETH Zurich.
Category:American statisticians Category:1936 births Category:2013 deaths