[Population Modeling] Introduction

[Jeff Shrager]

Hi, Jacob encouraged me to introduce myself, so here goes.

My name is Jeff Shrager [-1]. I am director of research of the non-profit Cancer Commons [0], and also an adjunct professor in the Symbolic System dept. at Stanford [1].

My background is rather complex. I started out in CS (operating systems and GOFAI [2]), and then went to CMU psych where I got interested in scientific reasoning [3]. Of course, the “Club of Simon & Newell” saw everything as individual search and problem solving, and my primary work there (primarily with David Klahr) was on how individual reasoners change their models by a process that I called “view application” (and which is these days called conceptual blending [4]), which (to be very gross about it) works sort of like an OO MixIn. After graduation I went to Xerox PARC for a decade where I did a bunch of random stuff, including some simulation work (primarily with Tad Hogg and Bernardo Huberman), on learning and search, mostly from a multi-agent point of view [5]. As a result, my own thinking about how science works morphed toward the multi-agent search and problem solving point of view. After PARC, I became deeply involved in biomedical science, co-founding two successful companies in the drug discovery and cancer spaces, and spending ten years in an actual molecular biology lab (yes, growing cells, pipetting, DNA manipulation, and All That Jazz! [6] All That Jazz didn’t afford much time for simulation work, but I did get to deeply understand how biomedical science works (and I did published a couple of little simulation experiment on biomedical science as a multi-agent search problem, esp. focused on the question of pre-v.-post publication peer review [7]). During that time I did a whole lot of other stuff that wouldn’t be relevant here; but one thing that is slightly relevant is that I lead a team that created what was among the earliest, and almost certainly the most advanced, through-the-web programmable biocomputing engines (what they now call Software as a Service) [8].

I’m now actually focused on creating (and simulating) a new kind of clinical trial, called Global Cumulative Treatment Analysis (GCTA) [9], which amounts to operating an Air Traffic Control system over the whole biomedical system [10]. The GCTA method uses Bayesian methods to adaptively (and so, theoretically, very efficiently) search the hugely combinatoric [omic x treatment] space, while treating each patient with the best validated knowledge to that moment. I’m very interested in talking to folks who are interested in scientific (esp. biomedical) modeling, esp. If you have an interest in biomedical discovery. (In fact, I may be looking to hire a modeler in this space!)

[-1] http://jeffshrager.org
[0] https://www.cancercommons.org/
[1] https://symsys.stanford.edu/
[2] http://jeffshrager.org/vita/pubs/1982AAAIWizard.pdf
[3] https://www.amazon.com/dp/1558601317
[4] https://en.wikipedia.org/wiki/Conceptual_blending
[5] http://jeffshrager.org/vita/pubs/1987SpreadAct.pdf
[6] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC326643/
[7] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2877080/
[8] http://jeffshrager.org/vita/pubs/2007SHPSBioBikeTZ.pdf
[9] https://arxiv.org/abs/1308.1066
[10] http://jeffshrager.org/vita/pubs/201609ShragerScienceLetterPrecision.pdf

(Ps. Fun Fact (apropos of nothing): My first published work was a BASIC version of Eliza that appeared in Creative Computing (now defunct) in the July/August issue of 1977. (I actually wrote the program in 1973!) Of course, the original Eliza was written by Joseph Weizenbaum in the mid '60s in Lisp. (Technically it was written in SLIP by JW and translated to Lisp by Bernie Cossell of BBN.) Although I saw a copy of the Lisp code much later, my translation was done without that benefit, and was, to put it gently, "conceptual", and pretty awful. Regardless, 1977 was the dawning of "The Age of The Personal Computer", and few folks had (or knew) Lisp, but everyone had (and knew!) Basic. So my version of Eliza was hugely influential -- probably the most influential thing I've ever done. Hundreds of knock-offs appeared, some as late as 2015 (!), and it was translated into many other programming languages. In fact, my version has even been translated back into Lisp! Some AI researchers and engineers to this day credit this version of Eliza and their introduction to the "magic" of AI. For fun I run a site dedicated to the history of Eliza called The Eliza Genealogy Project [n].)

[n] http://elizagen.org/