Philippe Barbe

As a business person, I do one thing: innovation. There two broad categories of innovations in which I specialize:

1. help organizations to define their vision and strategy. As a mathematician, I approach these in a very analytical way, with a lot of rigor, using both inductive and deductive methods, and imagination when it comes to vision (yes, mathematicians, like other scientists, have imagination, for it is needed to imagine solutions to difficult problems).

2. data science, analytic, machine learning, applied math, operation research, whatever math, particularly for very difficult problems that require highly customized solutions. As a loose indication, the problems I tackle range from organizing work and leading teams, to designing complex decision supporting systems, to designing new algorithms, to inventing new conceptual frameworks for solving your problem.

If your problem can be solved with standard methods, I am happy to tell you how to do it, but do not ask me to spend a lot of time on it. I am always seeking difficult problems.

If you would like to contact me, please reach out on LinkedIn.

Philippe Barbe is a leader, expert and trusted advisor in data science, AI, and mathematics, with a wide range of experiences in business, industry, government and research and a very substantial international experience.

After some noted work on the cost of unemployment in France, he worked for 21 years as mathematician at the prestigious Centre National de la Recherche Scientifique in France. He collaborated with teams from very diverse backgrounds on multiple continents. He was invited professor in numerous universities worldwide, including Yale and Georgia Tech. He is the author of 5 books, many scientific papers, and gave conferences to audiences ranging from a few to over 1,000.

As a consultant he helps corporations with their vision and strategy, and any problem related to information, data, algorithms and mathematics at large.

Since 2014, he is based in the US, working in health care, IoT, and media. He lead high performing data science teams. He was the head of Data Science at Videa, a Cox Enterprise company, from 2015 to 2020. He is currently Senior Vice President of Content Data Science at Parmount Global, and is responsible for data science modeling to inform content exploitation decisions across Paramount businesses

Philippe Barbe holds a degree in economics and government affairs from ENSAE, a master in statistics, and a PhD in mathematics from the Université Pierre et Marie Curie in Paris, France.

My avatar is a collage of book covers which tells you a fair amount on myself.

The books are:

• Strategor: probably the best book ever written on strategy for business persons. It covers business strategy, corporate strategy, and change management. It is in French and is the standard textbook in top MBA programs.

• The Elements of Statistical Learning by J. Friedman, R. Tibshirani, and T. Hastie. This illustrates my original training as well as the change of semantic that I have witnessed. The content of the book used to be part of standard statistics, and got rebranded as machine learning.

• Shape and Shape Theory by D. G. Kendall, D. Barden, T. K. Carne, H. Le. Shape theory is one of these fields that any data scientist dealing with image should know, and most ignore. It illustrates my interest in geometric matter, and how I like data science: when it intersects many fields, as here, statistics, differenial geometry, algebraic topology, and computing.

• Probabilité by myself and M. Ledoux. Writing is an important part of my life, in particular writing books, and so is teaching. Michel Ledoux has influenced many French probabilists. Among many things, he taught me to strive for simplicity.

• Three Dimensional Geometry and Topology by W. Thurston. Not only the topic is interesting, but it is the most beautifully typset mathematical book I know. This represents my interests in pure mathematics, as well as the years I studied typography and book composition. It is also attached to David Pollard who made me interested in typesetting and typography, as well as some wonderful time in Blacksburg with Bill Floyd who was involved in the making of this book; and by association, his colleagues in the math department, Marty Day, Peter Haskell, Leslie Kay, John Rossi and others.

• Deep Learning by I. Goodfellow, Y. Bengio, A. Courville, is in the same spirit as Friedman, Tibshirani and Hastie’s book. It is also my marketing side: I wanted something about the topic of deep learning, and this is one of the few books available on the topic. I encountered neural networks first in 1993. So I have some historical perspective on that matter, and appreciate the field and its evolution.

• Commentaire is a journal founded by Raymond Aron. The journal is very much a miror of his founder, dominated by realism and pragmatism, with a bend toward liberalism and social democracy. The authors tend to be practionners more than academics. It reflects my interest in the broad range of topics that it covers, albeit from a French perspective.

• Political Science Quarterly is about political science, but more broadly, discusses domestic and international affairs, somewhat like Commentaire, but more from an american perspective. It is more scholarly than Commentaire and this reflects my taste for in depth analyses, as well as my American side.

• Beethoven’s sonata because classical music is an important part of my life, both as a listener and as a (very amateur) musician who plays the piano.

This makes it a decent overview of who I am, and tells you more about myself than a picture.

I try to remain educated, meaning reading some books, newspapers, articles and so on. My interests have been changing over the years, depending on where I live, who I hang out with, and geo-political events. Some constants have been international, domestic and military affaires. I also read a fair amount on architecture, design, and sustainability.

Writing is an important part of my life. I wrote and write both scientific papers and general articles.

In my spare time I played the clarinet and the organ for some years, but piano has been my main instrument. I wrote some music, stopped for several decades, and went back to it in 2020.

My intellectual self is balanced by a life long interest in manual work. I can probably build a house from scratch though I never tried. I also had periods of elaborate cooking, though now I am mostly baking my own bread every day – French baguettes straight from the oven are irresistible! I owe this bread making interest to our friend Joseph who is an accomplished musician, baker, writer, and photographer.

Throughout my life I have been practicing sports, but I am no superman. I have no interest in watching sports. I went to a school where 6 hours of sport each week was mandatory (3 times 2 hours). It also required students to learn a new sport every semester, under the direction of particularly knowledgeable instructors. I have practiced various ball sports (soccer, rubgy, handball, basketball, water polo, tennis, babmington), running (100m, 500m, relay, hurdling, long distance), throwing (hammer, javelin, disk, weight), jumping (high jump, long jump, pole vault), swiming (crawl, butterfly, breaststroke, diving), gymanstic (horizontal bar, parallel bar, rings, rope climbing), combat sports (fencing, judo, and even shooting, which is rare in France), winter sports (downhill and cross-country skiing, ice skating), sports on wheels (bicycle, roller skating). I was an avid fencer (all weapons) for several years.

This tremendous training gave me an appreciation for all sports, and tons of fun memory!

I still do some physical activity to keep in shape, and remain an avid downhill skier.

I also sail, which at time qualifies as physical activity.

If you want to laugh at my expense: I jumped far lower at the pole vault then at the high jump! The only way I can jump as high is to throw away the pole before jumping!