Resources for Pre-Health & Pre-Med Advisors
Helping Pre-Med Students Build a Real AI Project — Not Just Another Extracurricular
STEAM in AI works with pre-health advisors (WAAHP, NAAHP member institutions) to give premed and med-school-bound students a portfolio-ready AI project — built or researched 1:1 with an industry mentor, grounded in ethics-first design, and mapped to what admissions committees actually look for.
Two Tracks, Two Kinds of Value
Matching the Track to the Student's Story
AI Build — The Differentiator
Most premed applicants already have clinical volunteering and a standard research stint. Very few have built a working AI health tool. This track signals initiative and innovation precisely because it's rare in the applicant pool — a strong fit for students telling a "future physician-innovator" or digital-health story.
AI Research — Counts as Research Experience
Computational/AI research produces a poster, abstract, or paper — something advisors and admissions committees can place directly into the "research experience" bucket. It also doesn't require lab bench access, so it's a path to a real research credential for students without a nearby lab or PI connection.
We help you match the track to the student's story — not every premed student needs the same project.
AI Build
Student Project Examples
Examples shown, outcomes vary.
Final projects depend on readiness, interests, and mentor guidance.
MRI Knee Image Classification
JuliaBuilt an AI classification model for MRI knee images, evaluating accuracy and clinical limitations.
Accepted to Duke — Statistical Science / Data Science + CS
SkinSense — AI Skincare Analysis Tool
RaianBuilt an AI tool that analyzes skin health and conditions from images, with careful attention to accuracy limits and responsible use of visual health data.
Portfolio-ready AI health tool
AI Research — Forward-Looking Directions
Where Students Can Take AI Research in Health
These are proposed research directions — scoped and ready for a mentored student — not past student outcomes.
Health Equity Audit of a Diagnostic AI Model
Evaluate a public dermatology or radiology model's accuracy across different skin tones or demographic groups; document bias findings and clinical implications.
Disease Trend Forecasting Model
Build a predictive model using public health datasets (CDC, WHO, or similar open data) to forecast spread or risk of a chronic or infectious condition.
NLP Analysis of Patient Experience
Text-mine patient forums, clinical notes, or medical literature to surface unmet needs, treatment barriers, or communication gaps in a specific condition community.
Each direction pairs a real public dataset with mentor guidance, and is scoped to produce a submittable poster, abstract, or paper.
Ethics-First by Default
Why This Fits an Ethics-First Framework
Every project — Build or Research — includes bias, safety, and human-oversight evaluation as part of the process, not as an add-on.
For health specifically, this maps directly to how medical AI is actually scrutinized in practice — clinical validation, equity of diagnostic accuracy across populations, and appropriate human oversight in decision-making.
For Advisors
How This Works
STEAM in AI works alongside pre-health advisors the same way we work alongside independent educational consultants — we don't replace your advising relationship with the student.
We provide the specialized AI mentorship layer: project design, 1:1 industry mentorship, and a portfolio-ready outcome your student can speak to in interviews and applications.
Why Work With Us
Meet Your AI Research Partner
Your Partner for Personalized AI Projects in AI Build or AI Research
We work with you to help pre-health students stand out through a personalized AI project based on their skills, interests, activities, and college & career path — built on our 5-Step STEAM in AI Framework.
Shilpi Agarwal
Chief AI Architect & Principal Investigator · Former Stanford AI Adjunct Faculty · Co-Chair, IECA STEM & Arts Committee
Shilpi Agarwal is the Principal Investigator on every Research Track paper — she shapes each research question and co-authors submissions. She brings academic research rigor as a Regeneron ISEF Grand Award Judge, NeurIPS presenter, MIT mentor, and Former Stanford AI Adjunct Faculty, complementing the advising you already provide.
She is also an IEC and Co-Chair of the IECA STEM & Arts Committee — but for your students, her value is as the AI research expert, not another counselor. She gives pre-health students a genuine AI research project with real academic supervision.
Every student works with two mentors: Shilpi Agarwal as Chief AI Architect & PI who personally co-authors every research paper, plus a dedicated 1:1 Industry Mentor — an AI researcher or engineer from companies like NVIDIA, Genentech, and Roblox, matched to the student's research area.
The 5-Step STEAM in AI Framework
Personalized to Every Student's Path
Every student's project follows our 5-Step STEAM in AI Framework — personalized to their unique path.
01
Discover
Identify the student's skills, interests, and goals.
02
Design
Architect a personalized AI research project aligned to their pre-health/pre-med path.
03
Research
Execute the project with dual-mentor guidance (Chief AI Architect & PI + 1:1 Industry Mentor).
04
Document
Build research portfolio, document outcomes, strengthen medical school & college applications.
05
Present
Opportunity to present and compete (path to conferences, competitions, publications).
The Two-Mentor Structure
Every Student Works With Two Mentors
Chief AI Architect & PI
Shilpi Agarwal
Co-authors every research paper, shapes the research question, and ensures academic rigor.
1:1 Industry Mentor
Dedicated per student
A dedicated AI researcher or engineer matched to the student's research area (e.g., Genentech for biotech/pre-med, NVIDIA for computational).
Research Mentors From
YC Startup Founders
a16z AI Startup Founders
Stanford
Santa Clara University
MIT
Where Our Students Have Been Accepted
Students from our program have been accepted to:
Examples shown. Outcomes vary based on student background, effort, and overall application.
Path to Research Publications & Competitions
Students who continue beyond the Intensive have a path to submit research to competitions, present at conferences, and pursue publication — differentiating their pre-med applications with genuine AI research experience.
ISEF
Neural Information Processing Systems
MIT RSI
Proud Member & Business Partner
Questions? Reach out to Shilpi at shilpi@steaminai.org
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