2020 Conference

06 March 2020

08:00 am - 5:00 pm

For the fourth year, Harvard, MIT, and Microsoft Research New England are proud to collaborate with Stanford University to bring the Women in Data Science (WiDS) conference to Cambridge, Massachusetts.

This one-day technical conference will feature an all-female line up of speakers from academia and industry to talk about the latest data science-related research in a number of domains, to learn how leading-edge companies are leveraging data science for success, and to connect with potential mentors, collaborators, and others in the field.

WiDS Cambridge Advisory Committee: Tamara Broderick, MIT; Yael Grushka-Cockayne, HBS; Stefanie Jegelka, MIT; Rachel Nethery, Harvard T.H. Chan School of Public Health; and Caroline Uhler, MIT

The 2020 WiDS Cambridge Datathon meetup will take place from

9:00 - 5:00 on Saturday, February 15th at the Microsoft NERD Center.

Datathon Workshop Website

About WiDS

The Women in Data Science (WiDS) initiative aims to inspire and educate data scientists worldwide, regardless of gender, and to support women in the field.

WiDS started as a conference at Stanford in November 2015. Now, WiDS includes a global conference, with approximately 150+ regional events worldwide; a datathon, encouraging participants to hone their skills using a social impact challenge; and a podcast, featuring leaders in the field talking about their work, their journeys, and lessons learned.

2020 SPEAKERS

X. Shirley Liu

Professor, Dana Farber Cancer Institute and Harvard T.H. Chan School of Public Health

Asu Ozdaglar

Distinguished Professor of Engineering

MIT, EECS

2020 PANEL

"DATA WEAPONIZED, DATA SCRUTINIZED: A WAR ON INFORMATION"

Fake news, misinformation, disinformation… these all became buzzwords in 2016 during the US presidential election. Four years later, have we made sense of them? As inaccurate information is spread at an unprecedented scale and speed online, we rediscover a very old truth: information can be manipulated. What is the data needed to prevent truth from manipulation?