Robert E. (Rob) Kass received his Ph.D. in Statistics from the
University of Chicago in 1980. His early work formed the basis for his
book *Geometrical Foundations of Asymptotic Inference*,
co-authored with Paul Vos. His subsequent research has been in
Bayesian inference and, beginning in 2000, in the application of
statistics to neuroscience. Kass is known not only for his
methodological contributions, but also for several major review
articles, including one with Adrian Raftery on Bayes factors (*Journal of
American Statistical Association*, 1995) one with Larry Wasserman on
prior distributions (*Journal of American Statistical Association*, 1996),
a pair with Emery Brown on statistics in neuroscience (*Nature Neuroscience*, 2004,
also with Partha Mitra; *Journal of Neurophysiology*, 2005, also with
Valerie Ventura), and, with 24 others, an overview of computational neuroscience
emphasizing essential mathematical and statistical ideas (*Annual Reviews of
Statistics and its Applications*, 2018). His book *Analysis of Neural Data*, with
Emery Brown and Uri Eden, was published in 2014.

Kass has served as Chair of the Section for Bayesian Statistical
Science of the American Statistical Association, Chair of the
Statistics Section of the American Association for the Advancement of
Science, founding Editor-in-Chief of the journal
*Bayesian Analysis*, and Executive Editor (editor-in-chief) of the international review journal * Statistical Science*.
He is an elected Fellow of the American
Statistical Association, the Institute of Mathematical Statistics, and
the American Association for the Advancement of Science. He has been
recognized by the Institute for Scientific Information as one of the
10 most highly cited researchers, 1995-2005, in the category of
mathematics (ranked #4). In 2013 he received the Outstanding Statistical
Application Award from the American Statistical Association for his
2011 paper in the *Annals of Applied Statistics* with Ryan Kelly
and Wei-Liem Loh. With various co-authors, Kass has also written on statistics education and the use of statistics, including the short article * Ten Simple Rules for Effective Statistical Practice, * which received more than 100,000 views during the first 10 weeks after it was published. In 1991 he began the series of eight international workshops *Case Studies in Bayesian Statistics*, which were held every two years at Carnegie Mellon, and was co-editor of the six
proceedings volumes that were published by Springer. He also founded
and co-organized the eight international workshops * Statistical Analysis of Neuronal Data*, from 2002 to 2017.
The ninth iteration (with new organizers) took place in the Spring of 2019.

Kass received the 2017 R.A. Fisher Award and Lectureship from the Committee of Presidents of Statistical Societies. The lecture may be found here (starting at 25:15 in the video)
and a shorter version, edited to remove most of the technical material, may be found here with the corresponding CMU press release summary here.
A 2017 interview of Kass in * Statistical Science * (published in 2019) may be found here.

Kass has been been on the
faculty of the Department of Statistics at Carnegie Mellon since 1981; he joined the Center
for the Neural Basis of Cognition (CNBC, run jointly by CMU and the University of Pittsburgh) in 1997,
and the Machine Learning
Department (in the School of Computer Science) in 2007.
He served as Department Head of Statistics from 1995 to 2004 and Interim Co-Director of the CNBC (CMU-side director) 2015-2018.
He became the Maurice Falk Professor of Statistics and Computational Neuroscience in 2016
(see announcement here).

Kass has provided a brief summary of his work in 5 sentences and 4 questions.
Some additional detail on Kass's research may be obtained from his
NIH bio.

More than 80% of Kass's neuroscience publications have involved spike trains. That work is summarized here.

- A Conversation with Robert E. Kass, interviewed by Sam Behseta for
*Statistical Science*journal, Vol. 34, Number 2 (2019), pp 334-348. - Other interviews
- 2018 online interview
- 2016 radio interview (12 minutes)

In the spring of 1972 (my second year in college) I worked in the Department de Pathologie at the University of Geneva, Switzerland. There I learned a variety of lab techniques (I had previously worked in a different lab, doing various jobs, at Harvard Medical School), including tissue culture and time-lapse photographic microscopy.

The director of the lab, Guido Majno (a close personal friend of my father's), had become interested in the phenomenon that wounds heal much more slowly when circular than when straight, or rectangular. He called this the "turtle" effect because he imagined a circle of turtles walking toward each other and getting stuck when their shells collided, leaving a circular gap (analagous to slow healing).

I decided to run an experiment on this by growing fibroblasts in culture, and creating small wounds in the cultured layer, then creating a movie of them as they grew in. (I did this surreptitiously, after hours, because I knew I would not have been given permission to do this on my own.) The results were astonishing: in time-lapse we could see the cells slowly moving toward each other, then one would "extend an arm" (cytoplasm) toward another, they would wrap each other and pull, and then suddenly hundreds of cells would pile on top of each other. In other words, we could see mechanistic aspects of wound healing in vitro. My report on the turtle experiments may be found here. Guido raised his eyebrow when I told him about what I had done (right at the end of my stay in his lab), but when he watched the movie he also thought it was amazing. He promised to follow up, repeat, and publish the results. This never happened. My impression is that this was about the time that people were starting to work out mechanisms of fibroblast locomotion (e.g., Theriot, JA and Mitchison, TJ (1992) J. Cell Biol., 118: 367-377, and refs therein).

In my earlier jobs (especially in high school and just after) I had learned electron microscopy. I saved an electron micrograph of an
alveolar macrophage, because I had done all the work, from harvesting the cells from the animal, to embedding the tissue in epoxy,
to slicing with a diamond knife, to running the microscope, and finally developing and printing the picture. It is the top one here: