Jim Simons: 1938–2024

Portrait

I am saddened to learn that Jim passed away and I would like to extend my condolences to his family and friends. Jim’s memory will be a blessing to all who knew him.

I met Jim in 2011 when I had the good fortune of receiving the Simons Chair in Mathematics and Statistics. I was impressed by his curiosity, sharpness, and generosity, yet simultaneously very charmed by his down to earth personality.

Perhaps people will appreciate these qualities even more if I relate a conversation we had during my very first meeting with him:

Jim: so, what are you doing?
Emmanuel: I work on statistical theory and methodology.
Jim: oh, that’s strange. In my view, statistics is an empirical science, so why do theory?
Emmanuel (with heart beating fast and searching for an answer): well, Jim, while what you say is true, there are theoretical aspects that are fascinating. For instance, do you know about Stein’s paradox?”
Jim: No. What is it?

I proceeded to give him a provocative example which may have been something like this:1 say you have a baseball player, soccer player, and football player, and you wish to estimate the true mean number of home runs, goals, and touchdowns each scores per year. If you have their last ten seasons worth of data for each, then the obvious thing to do, for each player, is to estimate the true yearly mean score for each player by their average yearly scores from the last ten years. (E.g., the baseball player hits an average of 20 home runs each year, so let’s estimate their true mean yearly home runs by 20). Stein’s Paradox says that you can actually do a lot better than this. Even crazier, you should use data about the football player and soccer player to make predictions about the baseball player and vice-versa. This is deeply unintuitive since the players aren’t related to each other at all. The phenomenon only holds with at least three players; it doesn’t work for two.

Jim: This does sound crazy. Should I believe you?
Emmanuel: This is a mathematical fact.
Jim: Do you have a proof?
Emmanuel: I think so.
Jim: I would like to see it.

At this point, we were having lunch at the Simons Foundation and he stood up and said: “show me!” We walked to a white board, he gave me a color marker and asked me to explain. We had fun at the board that day.

This is the person I got to know: curious, lively, sharp as a razor, and fun.

We saw each other frequently since then and I have always enjoyed our interactions and being around him. Most of all, I will remember his generosity. Jim’s financial generosity is known to all: but he was also generous with his time and spirit.

Despite a busy schedule, Jim kindly agreed to be a member of the Advisory Board I established to counsel the new Stanford Data Science Institute. The guidance from someone who built at least two extraordinary organizations (Renaissance Technologies and the Simons Foundation) has been invaluable. For instance, he was extremely helpful in connecting me with some of the technical leaders of the computing core at the Flatiron Institute, which ultimately influenced our vision and changed our mission a great deal.

The last time I saw Jim was in San Francisco where he was helping the IHES (Institut des Hautes Etudes Scientifiques) fundraise. He did not have to do this but he did because he always made the choice to be helpful in whatever capacity he could be, and always put real effort behind that choice.

Another thing which always impressed me is that Jim was always surrounded by extraordinarily smart people. All the people he picked to work with – whether at RenTech, the Simons Foundation, or the Flatiron Institute – were world class. He had an ability to build human capital like no one else.

It has been a privilege to get to know Jim. Someone with his level of accomplishment can be intimidating but Jim was the opposite: approachable, funny, humble. He always made you feel at ease. I learned a lot from him and I would like to think that we had a great time together – I know I did. I will miss him very much.

Emmanuel Candès


  1. I do not recall the precise example I gave so I will borrow from Naftali Harris. ↩︎