In this issue, you will find articles about LIDS alum and Stanford Universiy professor David Tse, recent graduate Christina Lee, graduate student Ian Schneider, Principal Research Scientist Kalyan Veeramachaneni, Assistant Professor Caroline Uhler, and new staff member Jin "Gracie" Gao. Each of these articles showcases the accomplishments of an extraordinary individual shaped in part by their experiences at LIDS.

A Message from the Director

It is a privilege to introduce the latest edition of LIDS|All. I began my tenure as LIDS Director in April 2017...

Practical Lessons

Ask David Tse what his greatest failure is, and he gives a surprising answer: his PhD thesis.

Discovering Insights in Data

Most people don’t give much thought to the ways in which an e-commerce platform like Amazon generates its recommendations for users. Christina Lee considers this topic often

Engineering a Brighter Future

Ian Schneider has spent much of his academic career thinking about renewable energy and where it sits in the larger picture of social and financial infrastructures. His interest began during his undergraduate days at Dartmouth College...

Data to AI

Principal research scientist Kalyan Veeramachaneni has been working in data science for over a decade.

The Explorer

Imagine a cell. A liver cell or a lung cell, say: a little porous packet of fluid with a tightly packed nucleus, like a baseball’s rubber core.

Soundbites: Jin "Gracie" Gao

After finishing my degree, I came to Boston to get married. I had a data-collecting job at a research institute before coming to MIT...

LIDS Welcomes Ali Jadbabaie

Ali is the JR East Professor of Engineering in the department of Civil and Environmental Engineering, the Associate Director of the Institute for Data, Systems and Society, and the Director of the Sociotechnical Systems Research Center at MIT.

LIDS Welcomes Philippe Rigollet

Philippe works at the intersection of statistics, machine learning, and optimization, focusing primarily on the design and analysis of statistical methods for high-dimensional problems.