This page provides links to all of my co-authors and co-editors who have web pages (and a few who don't). If I have made any errors in any of my thumbnail sketches, let me know and I will fix them.
David Aldous contributes to all parts of probability, but he has a particular liking for intuitive ideas like the famous clumping heuristic. His site provides (1) access to his new Markov Chain book with Jim Fill, (2) an open problems page, and (3) the Top Ten Reasons to Become a Probabilist.
Alessandro Arlotto completed his Ph.D. in the OPIM department at Wharton in the summer of 2012. He is now Assistant Professor of Decision Sciences, Fuqua School of Business, Duke University. Look for him to rise quickly as leader in the area of Markov decision problems, sequential decision making --- and applied probablity in general.
David Avis is a professor of computer science at McGill who is best known for work in computational geometry. Remarkably, David is also fluent in Japanese, which he learned as an adult.
Jon Bentley is on anyone's list's of the greatest contributors to the world literature of programming. His books make real money. Our paper has been translated into Japanese.
David Boyd is a founder of what is now known as experimental mathematics. He is the man to ask if you have a question about Pissot-Vinnot numbers or Mahler's measure; for his work in this area he won the 2005 CRM-Fields Prize.
Shankar Bhamidi studied with David Aldous and he works mostly on branching processes and distributional functional equations. He is an Assistant Professor of Statistics at UNC. Our paper is one of the few in the Annals of Applied Probability that mentions Lady Gaga.
Sid Browne and I did work together when he was a professor at Columbia. He subsequently moved to Goldman, Sachs and he is now a Managing Director at Credit Suisse. He has not lost his widely admired capacity for humor.
Robert Chen works is an applied probabilist at the University of Miami who has worked on many selection problems and prophet problems.
Burgess Davis is a probabilist at Purdue. He is perhaps best known for the middle piece (in three senses!) of the widely used Burholder-Davis-Gundy inequality. He has also done much to show people how probablity theory can be used to prove theorems in complex analysis.
Andres del Junco does ergodic theory at the University of Toronto. He has coordinates but no web page.
Dick DeVeaux teaches statistics at Williams College, and, with Paul Velleman, he has written Intro Stats, which sells like hotcakes. Dick also has a worldwide reputation as a raconteur with a fine ear for dialect.
Persi Diaconis is as well-known as any statistician can be and one of the few with a picture in his Wikipedia profile. We've known each other since we were both assistant professors at Stanford. He's not here as a co-author but as a co-editor of that hard-to-find classic Discrete Probability and Algorithms.
Bill Eddy works in computational statistics and image processing at CMU. He is closely associated with a collection of image processing tools bravely named FIASCO, or Functional Image Analysis Software - Computational Olio.
Marty Ellis died before our second paper could be published. No one understood the disease at the time, but it seems clear now that Marty was an early casualty of what we now know call AIDS.
Andrey Feuerverger is at the University of Toronto, works in mathematical statistics and gained some notoriety for his paper on the so-called "lost tomb of Jesus" which appeared in the first volume of the Annals of Applied Statistics.
Jim Fill is a probabilist at Johns Hopkins known for his many works on Markov chains, including his eternally soon-to-be-finished book with David Aldous.
Moshe Fridman did his Ph.D. with me at Wharton, worked at UCLA for several years, then took up a career in bio-statistics and medical consultancy.
Noah Gans is the Joel S. Ehrenkranz Family Professor of OPIM at Wharton. Most of his work focuses on probability models and optimization applications in service operations manangement.
Jun Gao did his Ph.D. with me at Princeton in Applied and Computational Mathematics, though in his last year he was actually at Wharton. Gao has been working in the financial service sector for more than ten years now. Unfortunately, we have lost touch. If you know what Jun is doing now please let me know.
Nassif Ghoussoub has worked in many parts of non-linear analysis, optimization and partial differential equations, but when we were kids, we did ergodic theory together.
Joe Glaz is a statistician and probabilist at the University of Connecticut. He is a particularly involved with the investigation of scan statistics.
Floyd Hanson started out as a classical applied mathematician, doing fluids, asymptotics, and such. He then moved to less classical areas including parallel computation, computational finance, and scientific visualization. Floyd recently retired in order to devote his energy to writing books.
Dorit Hochbaum teaches both in Engineering and in the Haas School at Berkeley. Her research interests include algorithmic and probabilistic aspects of logistics, including supply chain management.
Dick Karp has contributed to many parts of discrete mathematics and the theory of algorithms. In particular he was among the first to realize the importance of NP-completeness and related notions of computational complexity. If there were Nobel prizes in computer science, he would have a couple.
Martin Kulldorff is a statistician at the Harvard Medical School who worked with Joe Glaz and Vladimir Pozdnyakov on scan statistics. As sometimes happens when a paper has multiple co-authors, I met Martin for the first time in 2009 more than a year after the publication of our paper.
Tom Leighton and I each have 20% ownership of a group paper organized by Jon Bentley. Tom is perhaps more famous as the co-founder of Akamai. He is my only billionaire co-author, though I hope there are many more.
Margaret Lepley is a computer scientist at Mitre Corporation who now mainly works in data compression for images.
Vladimir Pozdnyakov did his first Ph.d. in St. Petersburg and then came to Penn to do a second Ph.d. He works in limit theory, mathematical finance, and other areas of applied probability, including scan statistics. He is now a Professor at UConn.
Zhihua Qiao is currently a research associate at J. P. Morgan. He did a Ph.d. in statistics at Wharton and liked it so much he decided to do a scond Ph.d program in finance at MIT.
Dan Rudolph and I were students together at Stanford, and he is the co-author I have known the longest. Dan died of ALS in February 2010; he was 61.
Steve Samuels worked in applied probability and was Professor of Statistics at Purdue for many years. He passed away in 2012.
Larry Shepp is best known for his work in tomography, but hid footprints are found all over applied mathematics. Larry had a terrible fall in January of 2013 and passed away a few months later.
Timothy Snyder did his Ph.D. with me at Princeton in Applied and Computational Mathematics. We wrote several papers together while he was at Georgetown University, where he became a very young Associate Dean. He is now the 16th President of Loyola Marymont University in Los Angeles, a Catholic institution with more than 9,000 students.
Diane Souvaine is a computational geometer who also did her duty as the chair of computer science at Tufts.
Joel Spencer can be aptly called "Mr. Probabilistic Method." Like Persi, he is here as a co-editor of our IMA volume Discrete Probability and Algorithms.
Donald Stanat started out in physics and mathematics, but he headed to computer science almost in time to be there for the creation. He retired from UNC a few years back.
Bill Steiger is a professor of computer science at Rutgers who sometimes teaches statistics at Princeton and who is always interested in problems of computational geometry.
Frank Stenger is now Professor Emeritus at the University of Utah. He is best known for work on approximation theory and the sinc function.
Bob Stine has a preference for statistical problems that require a computationally intensive approach, and has worked with Dean Foster on a wide range of problems that leverage a computational point of view.
Luke Tierney is an R super-guru and one of the creators of MCMC. Luke teaches at the University of Iowa.
V.V. Nguyen is currently a Ph.d. student at the Fuqua School, Duke University. He works in operations research and applied probability. Vinh seems not to have a web page, but you can follow his Google Scholar page.
Andy Yao is a professor of computer science at Princeton. He works in several areas, perhaps most notably in the theories of algorithm efficiency and quantum cryptography.
Yu Zhang is a probabilist at the University of Colorado in Colorado Springs who works in many parts of percolation theory.
Tauhid Zaman is Assistant Professor of Decision Science at the Sloan School, MIT. We did our first work on Twitter and the "Retweet Graph" during his 2011-2012 post-doc at Wharton. He's working on owning the brand "probablity plus social media."
Jim Zidek was UBC's first Professor of Statistics, and he has recently become UBC's first Emeritus Professor of Statistics. You can read about Jim's career in English or in French.
Almost anyone in the mathematical sciences is likely to be amused by the Mathematics Genealogy Project . Here I learned to my surprise that I am a scholarly descendant of C. F. Gauss (by two paths):
I also recently checked my Erdös number, which I knew had to be two even without knowing by what path. Anyway, I found that David Avis has Erdös number one, so the paper Avis-Davis-Steele (1988) confirms that my Erdös number is in fact two.
Erdös and I had two pieces of work together, yet out of my laziness or foolishness they did not turn into publications. In one of these, Marty Ellis and I developed an idea which was in my thesis and for which Erdös had been the supplier of both the motivation and the key ideas. This is all duly acknowledged in the thesis, but it would have been infinitely better (and much more appropriate) to have had Ellis-Steele (1979) be Erdös-Ellis-Steele (1979). I sorely wish that it could be made so retrospectively.