WiDS Cambridge
Datathon Workshop
Saturday, April 18, 2026
9:00 am - 5:00 pm EDT
with a one-hour lunch break
Microsoft New England NERD Center
One Memorial Drive, Cambridge MA 02142
for more details, click important information below or contact wids-cambridge@mit.edu
2026 Datathon Workshop
2026 WiDS Cambridge Datathon: As part of the global WiDS Conference Datathon, we are hosting a datathon workshop on Saturday, April 18. The WiDS Conference Datathon workshop consists of a data science/machine learning tutorial followed by a team-based practical session focused on a single data science task. Participants of the workshop will be participating in the Global WiDS Kaggle competition on a dataset/task focused on Predicting Wildfire Impact: From Infrastructure to Equity
Datathon 2026 Challenge Theme: Predicting Wildfire Impact: From Infrastructure to Equity
Overview: the dataset and challenges. As wildfires grow more frequent, intense, and disruptive they threaten critical infrastructure and communities. The 2026 WiDS Datathon challenges students and professionals alike to turn data into action. In collaboration with real-time wildfire data from Watch Duty, a nonprofit that is democratizing emergency information to protect lives and strengthen communities, this year’s challenges invite participants to forecast wildfire impacts and design equitable interventions. By combining geospatial modeling with human-centered design, participants will create tools that protect lives, strengthen infrastructure, and empower the communities most at risk.
Who can participate:
Designed for all data science enthusiasts who are discovering or building their data skills, the objective of this challenge is to build models to estimate, within 48 hours, the probability that an active wildfire will intersect high-value infrastructure, such as transmission lines, utilities, roads, and other critical corridors, in affected regions.
This challenge centers on delivering location-specific, early forecasts to help utility operators and emergency responders preemptive action. Proactive shut‑offs, targeted resource deployment, and prioritized infrastructure protection can minimize power outages, avoid cascading community impacts, and inform smarter mitigation planning.
The global challenge will run from beginning January – May 2026.
The 2026 WiDS Cambridge Datathon Workshop will be led by Sharut Gupta, 4th year Ph.D student in the Machine Learning Group at CSAIL under the Electrical Engineering and Computer Science (EECS) program at Massachusetts Institute of Technology (MIT). Sharut's research mainly focuses on building robust and generalizable machine learning systems with minimal supervision; Jenny Y. Huang, 3rd year PhD student studying machine learning at MIT, working in the department of Electrical Engineering and Computer Science with Professor Tamara Broderick. Jenny's work is supported by the Amazon AI Research Innovation Fellowship and has been supported by the MIT Presidential and Quad Fellowships.
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Our Mission
WiDS Cambridge is independently organized by MIT and Microsoft New England to be part of the mission to cultivate the next generation of Data Science and AI leaders by providing resources for upskilling, networking, mentorship, and growth opportunities, from students to professionals.
Our Vision
A future in which women are decision makers and share in the economic success in the field of Data Science and AI
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 one-day technical conference at Stanford in November 2015. Ten years later, WiDS is a global movement that includes a number of worldwide initiatives.
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