Save the Dates • April 10–11, 2026

Transform Precision Medicine with AI

Real datasets. Real challenges. Real impact on health — aligned with BU’s North Star priority on artificial intelligence, data science, and computing. Join Boston University's two-day medical AI hackathon tackling biomedical problems with machine learning.

April 10–11, 2026 Fri 3–6 PM, Sat 9 AM–6 PM

Boston University Center for Computing & Data Sciences

$10,000 in Prizes Plus GPU access & mentorship

About the Hackathon

What is MedAI Hack?

A two-day sprint bringing the entire BU community together to tackle real biomedical problems using AI/ML on de-identified clinical datasets — imaging, EHR, genomics, and more.

Friday evening features challenge reveals, rapid onboarding, and team formation with optional primers. Saturday is a full hack day with mentorship and judging.

Every challenge comes from active BU research labs — directly supporting BU’s convergent research priorities, including artificial intelligence, data science, and computing as well as health across the lifespan. Your work can inform publications, grants, and clinical insights.

4-5

Faculty-Sourced Challenges

$10K

Total Cash Prizes

GPU

HPC Compute Provided

1:1

Expert Mentorship

Event Schedule

Two Days of Innovation

Friday is all about preparation — team formation, training, and getting set up. Saturday is dedicated to building and winning.

Friday, April 10

Kickoff, Training & Teams

3:00 PM Check-in, Badges, Light Snacks

3:15 PM Welcome + Challenge Overviews

3:45 PM Data Access & Compliance Briefing

4:00 PM Team Formation & Mentor Office Hours

5:00 PM Tooling Setup: Repos, HPC/GPU Check

5:50 PM Day 1 Wrap + Saturday Reminders

Saturday, April 11

Hack Day, Demos & Awards

9:00 AM Breakfast + Final Q&A

9:15 AM Hacking Begins (mentors on-call)

12:00 PM Lunch

3:00 PM Mid-Day Check-In with Mentors

4:30 PM Submissions Due (code + brief)

5:00 PM Presentations & Judging

5:30 PM Awards & Networking Reception

2026 Challenges

Real Problems, Real Impact

Every challenge comes from active BU research labs, advancing BU’s North Star vision of convergent research where AI, data science, and computing intersect with health and biomedical innovation. Final challenge list will be announced in March 2026 — here's a preview of what to expect.

Sample Challenge

Early-stage lung cancer phenotyping

Data Whole-slide images and clinical variables

Goal Predict microscopic vascular invasion in lung resected tissues and pre-surgical biopsies on digitized images

Description Lung adenocarcinoma (LUAD), the most common type of lung cancer and a leading cause of cancer deaths in the US, varies widely in appearance under the microscope and has unpredictable chances of returning after treatment. This makes it hard for doctors to predict outcomes using standard methods alone. In this challenge, you'll build AI models to analyze high-resolution H&E-stained whole-slide images from surgically removed lung tissue and predict two key features: (1) microscopic vascular invasion (tiny cancer cells in blood vessels, a subtle sign of higher spread risk), and (2) solid-predominant growth pattern (the most aggressive subtype among LUAD's six patterns, linked to the worst prognosis). Using about 562 massive digital slides from 197 patients, your models must handle differences within the same tumor and use simple patient-level labels (present/absent for each feature). Strong results could help analyze smaller biopsy samples in the future and, if successful, be tested on larger Boston Medical Center data, potentially leading to published research that improves patient care.

All challenges are sourced from BU research groups and align with the university's emphasis on interdisciplinary convergence to solve major challenges in health and beyond. Your work can contribute to publications, grants, and clinical insights.

Prizes & Recognition

$10,000 in Total Prizes

Top teams will be awarded cash prizes and recognized for their contributions to biomedical AI research.

1st Place $1,000

2nd Place $500

3rd Place $250

* Prize amounts are per challenge track and represent the total reward for the winning team (shared among members). Additional categories or prizes may be announced.

Our Sponsors

Supported By

Proudly backed by leading BU centers and departments advancing biomedical AI and health data science.

Who Can Participate

Join the Hackathon

Eligibility

Open to the entire BU community across all disciplines. No prior AI/ML experience required. We welcome diverse perspectives!

Teams

Form teams of 3–5 members. Coming solo? No problem. We'll match you with a team during Friday's team formation session. Teams can tackle multiple challenges (we recommend focusing on 1–2).

What's Included

Friday training & onboarding
Faculty & industry mentorship
GPU/HPC compute access
Meals, snacks & swag
Project templates & starter repos
Networking with researchers

The Team

Organized By

Vijaya B. Kolachalama, PhD

Medicine, Computer Science, CDS

Jennifer Beane-Ebel, PhD

Medicine

Katia Bulekova

Research Computing Services

Charles Jahnke

Research Computing Services

Lingyi Xu

Computing & Data Sciences

Varuna Jasodanand

Graduate Medical Sciences

Shreyas Puducheri

School of Medicine

Rishi Shah

School of Medicine

Karim Elzokm

Electrical & Electronics Engineering

Samyuktha Kathirvel

Computer Science

Questions & Answers

Frequently Asked Questions

The MedAI Hack is open to the entire BU community across all disciplines. You don't need to be in a technical field — we encourage diverse teams with varied backgrounds in medicine, biology, data science, and more.

No prior coding or ML experience is required! Mixed-experience teams are encouraged. We provide lightning primers on Friday to get everyone up to speed, and mentors will be available throughout the event to help with technical challenges.

Teams consist of 3–5 members. You can register with a pre-formed team or come solo — we'll help match individual participants with teams during Friday evening's team formation session. Teams can tackle as many challenges as they want, though we recommend focusing on no more than 2.

You can use Python, R, PyTorch, TensorFlow, scikit-learn, JAX, and TerrierGPT. BU-supported stacks are preferred. GPU/HPC compute access will be provided, and we'll help you get set up with credentials and repo templates on Friday.

All datasets are de-identified and IRB-compliant. Data is accessed through secure BU systems only — you won't be able to download or remove data from the environment. Access credentials will be provisioned during Friday's onboarding session.

Friday attendance is strongly recommended. This is when challenge details are revealed, compliance training is completed, teams are formed, and compute access is provisioned. Without Friday, you may not be able to access the data or participate fully on Saturday.

We're awarding $10,000 in total prizes: $1,000 for 1st place, $500 for 2nd place, and $250 for 3rd place per challenge track. Additional prizes and categories may be announced closer to the event.

Ready to Make an Impact?

Join 100+ BU students, postdocs, and researchers contributing to BU’s convergent research priorities in artificial intelligence, data science, computing, and health — tackling real biomedical challenges with AI.

Plan to attend Friday for team formation and access setup