A 12-Week Immersive Program for University Students and Early-Career Professionals
This advanced HealthTech Entrepreneurship program is designed for individuals seeking to accelerate their ability to innovate at the intersection of artificial intelligence and healthcare. Through a rigorous, hands-on curriculum, participants will progress from deep problem discovery to developing ethical AI-driven solutions ready for academic defense, publication, or startup advancement.
Curriculum Overview
This program is built on three powerful pillars: Research, AI, and Innovation, helping students move from curiosity to creation.
In the first half of the program, students learn how to spot meaningful, real-world health challenges, analyze their broader context, and apply interdisciplinary thinking to generate bold ideas. Alongside this, they will gain a foundational understanding of artificial intelligence (what it is, how it works, and how to build their own simple predictive model using a healthtech case study). For those ready to dive deeper, optional coding exercises using Python and Google Colab will be available.
In the second half, students transition from ideation to execution. They will learn to prototype their solution using no-code tools or basic Python scripts (based on their skill level) and practice how to communicate their vision with clarity and confidence. This includes learning how to pitch like a founder or explore publishing options.
The program culminates in a Demo Day, where students present their prototypes to peers, families, and invited guests. They will receive personalized feedback, graduate with a certificate of completion, and leave with a portfolio-ready project that reflects their skills, creativity, and ambition.
Note: The curriculum is customizable if the student already has a project idea and/or is familiar with AI. Please indicate in the application form. We will follow up with a discovery call to customize the curriculum accordingly.
Below is a week-by-week overview of the modules covered in the program.
Curriculum Modules (Click to expand)
Module 1: Deep Dive into Health Challenges & Data Ecosystems
This module explores the intricate landscape of healthcare challenges and the vast, complex data ecosystems that underpin them. Participants will learn to identify profound unmet needs through rigorous research, preparing them to embark on their journey as innovators.
Module 2: Research Design & Data Acquisition
Participants master the art of designing robust health research, from conducting comprehensive literature reviews to developing ethical data acquisition strategies. The module emphasizes embedding responsible AI principles directly into a solution’s foundation, ensuring fairness, privacy, and impact from the outset.
Module 3: AI Model Selection & Development
This module offers hands-on experience in AI development, focusing on selecting and training powerful machine learning models for healthcare data analysis. Participants will delve into feature engineering and begin constructing their Minimum Viable Product (MVP), prioritizing functions that deliver immediate clinical value.
Module 4: Advanced AI for Health & Explainability (XAI)
Participants will advance their understanding of AI by exploring deep learning techniques for medical imaging and natural language processing. Based on the cohort, the curriculum can be extended to introduce Explainable AI (XAI) to ensure solutions are transparent, trustworthy, and readily adopted by clinicians and patients.
Module 5: Prototyping & User Validation
This module guides participants in translating AI models into functional prototypes, emphasizing rapid iteration and in-depth user validation.
Module 6: Ethical, Legal, and Regulatory Considerations (ELR)
Navigating the complex ethical, legal, and regulatory landscape unique to healthtech is a central focus of this module. Participants will learn to ensure their innovations are not only technologically sound but also compliant with stringent healthcare standards set forth by regulating bodies, such as the FDA, etc., mitigating risks proactively.
Module 7: Scaling Innovation & Business Models
Moving beyond the prototype, this module focuses on strategizing for scalable impact. Participants will explore robust business models for healthtech, analyze market dynamics, and establish the groundwork for effectively deploying AI solutions within complex healthcare ecosystems.
Module 8: Intellectual Property & Investment
This module focuses on securing an innovation’s future by exploring intellectual property strategies tailored to AI and health technology. Participants will learn to craft a compelling, investment-ready pitch deck, preparing them to attract crucial funding and strategic partnerships.
Module 9: Adoption Strategies
The module covers strategies for driving adoption among clinicians and patients, as well as critical techniques for monitoring AI performance after deployment.
Module 10: Refining the Solution & Pitch Preparation
This module is dedicated to refining the prototype, meticulously documenting the technical process and impact. Participants will prepare a compelling portfolio and a polished pitch, transforming their work into a powerful showcase for academic defense or professional advancement.
Module 11: Final Polish & Comprehensive Rehearsal
Participants will continue to polish their prototypes or concepts, perfect their presentations, and engage in comprehensive pitch rehearsals, ensuring every detail is impactful and ready for showcase.
Module 12: Demo Day & Pitch Event!
The program culminates with the Demo Day. Innovators will present their breakthrough solutions to a panel of experts and peers, marking a significant milestone in their journey to disrupt healthcare and showcase their readiness for real-world impact.
Learning Goals
Translate knowledge into innovation.
Apply your academic learning to identify unmet needs in healthcare and design a real-world AI-powered solution moving from problem to prototype to pitch.
Advance your technical skills.
Deepen your understanding of machine learning and build a working predictive model using real-world health data, Python, and open-source AI tools.
Build research-to-product fluency.
Gain skills in applied research and learn how to transform your work into publishable insights or translational prototypes that are ready for publication or innovation challenges.
Learn from real-world innovators.
Receive mentorship from a biomedical AI expert and startup founder. Learn how real-world innovation differs from academic problem-solving and how to bridge both.
Program Outcomes
Portfolio-ready health-AI prototype.
Build and document an AI-powered solution to a real-world health problem. Ideal for internships, job applications, or future projects.
Career clarity in the AI + Health space.
Complete a guided career mapping exercise to explore pathways like biomedical data scientist, digital health researcher, med-tech founder, etc., besides the traditional career pathways.
Advanced AI & health applications.
Learn how to use Python, Google Colab, and other tools to build models, work with health datasets, and assess model performance.
Publication & research readiness.
Refine your project for potential publication or poster presentations. Learn how to write a research abstract, create figures, and frame a compelling problem-solution arc.
Innovation leadership skills.
Learn how to frame a compelling vision, present your project with clarity, lead discussions, and integrate feedback, which are all essential traits for future researchers, founders, or medical innovators.
Professional network & feedback.
Collaborate with peers from diverse backgrounds, get structured feedback from mentors, and gain exposure to what top research labs, accelerators, and employers seek.
Digital Certificate of Completion.
Earn a certificate that showcases your expertise in AI, health innovation, and applied research.
Know your mentor
The program is led by Dr. Vinitha Subbhuraam, a global leader in AI-driven innovation. With over 15 years of experience, she has developed breakthrough industry-first medtech AI-powered products and solutions, raised millions in funding, and authored over 100 peer-reviewed papers and two books.
Dr. Vinitha Subbhuraam was recently listed among the top 1% of computer science researchers worldwide in the 2025 Research.com Global Rankings. This recognition reflects her contributions to AI innovation, scientific research, and thought leadership at the intersection of technology and health.
Read about her product portfolio and professional experience here
Read about her research portfolio and publications here
The curriculum was developed in collaboration with world-renowned AI experts, including professors and researchers ranked among the top 1% globally from institutions such as Columbia Business School, Stanford University, and Nanyang Technological University, as well as accomplished entrepreneurs and senior industry leaders.
Our early access program offers a unique opportunity to work directly with Dr. Vinitha Subbhuraam in a small-group set-up.
🚨 Registration closed!
Please join the waitlist to enroll in our future programs
Success Stories
Hear from students who have transformed their academic journey through our mentorship.
“Thank you for being such a great mentor the past year and for teaching me so much. I truly don’t think I could have such an amazing opportunity for my future if it wasn’t for your help.”
— Aspiring Biomedical Engineer | Incoming Georgia Tech CS Freshman
“You have been a great and encouraging mentor and I don’t think I would have asked for a better first experience (in AI research). I’ve learned a lot from you and hope to get the opportunity to continue to learn.”
— Future Tech-savvy Physician | First-Year at St. George’s University
“Thank you so much. It really gives a vision of what courses I can take related to science.”
— Aspiring Innovator in Genetics|High School Junior, Chicago
“I’m so grateful for your mentorship throughout this journey. Your insights into AI frameworks and research methods made complex ideas click — and showed me how to think across disciplines with clarity and confidence.”
— Future Researcher in Applied AI, Final-Year at NYU CS
FAQ
1. Program Value
How does the program differ from existing ones?
This isn’t just another online bootcamp or technical workshop. It’s a live, high-impact, project-based fellowship designed and led by Dr. Vinitha, a biomedical data scientist and health innovation leader with 15+ years of experience translating AI research into real-world products.
While other programs may teach you to build an app or run an AI model, this 12-week experience helps you go deeper:
✅ Identify an unmet health need grounded in research
✅ Design and test an AI-powered solution using a structured CONNECT-IL framework
✅ Build a functional prototype
✅ Communicate your work through a compelling innovation brief and pitch presentation
The curriculum integrates research methodology, applied AI, and innovation thinking for health innovation, preparing students for outcomes that matter in graduate admissions, startup pitches, or industry placements.
You won’t just learn how AI works. You will also understand how to apply it ethically and effectively in a health context, build with purpose, and articulate the real-world value of your work under the guidance of a mentor who’s done it in both academic and startup settings.
Whether you are preparing for medical school, graduate programs in engineering, jobs in life sciences and engineering, or a future in digital health entrepreneurship, this program helps you create something that sets you apart. It provides you with a portfolio-worthy innovation project that showcases initiative, interdisciplinary thinking, and your ability to lead from idea to implementation.
By the end, you will be well-prepared to continue through the IMPACT Labs 1:1 Mentorship Program for deeper exploration and support, if you choose to do so.
How is this program different from the college curriculum?
Most school systems don’t teach students how to apply their knowledge to real-world innovation. Here’s what’s missing—and what we bring:
- 🚫 From theory to translation: Traditional coursework teaches concepts like machine learning, public health, or biomedical devices, but in isolation.
☑️ This program helps students integrate their academic learning across courses to design AI-powered solutions for real-world health problems. You will apply what you know to a challenge that matters. - 🔄 Bridging siloed knowledge: Courses are often designed to master knowledge within a single field. Rarely do students have the opportunity to combine research, coding, human-centered design, and ethics into a single, integrated project.
☑️ This program guides students to work across disciplines, just as real healthtech and research teams do, by applying knowledge from various disciplines to solve meaningful problems. - 🛠️ Beyond class assignments: Most student projects conclude with a paper or lab report and remain confined to the classroom.
☑️ This program guides students from problem identification to prototype development to pitch presentation, enabling them to produce a portfolio-ready project that can be utilized for job interviews, research positions, or graduate school applications. - 👀 Real-world innovation lens: Academic labs may not always reflect the pace and mindset of startups or product innovation.
☑️ This program utilizes a real-world innovation framework (CONNECT-IL), grounded in experience from the startup, research, and healthtech industries, helping students think like founders, builders, and translational scientists.
This program doesn’t replace your coursework. It multiplies its value by helping you connect, apply, and extend what you have learned into the real world.
2. Application, Pre-requisites, Pricing
Is this course open to beginners?
Yes.
Should I know coding?
Basic familiarity with research methodologies or coding is appreciated. You will be introduced to Python AI/ML coding during the program. If you know coding and want to build a tech product, we can offer the required guidance so you get the maximum value out of the program.
What happens once I submit my application?
Your application will be reviewed within 48 hours. If admitted, you will receive an email with tuition details and a secure payment link. Once payment is received and your admission is confirmed, you will receive onboarding instructions via email. If you are not admitted, you will also receive an email notification.
I do not reside in the U.S. Can I still participate?
You may be able to. Please apply still and we will reach out to you with additional information.
Is there an Info session?
Please email contact@impactlabsacademy.com expressing your interest in an information session.
3. Program Details
What is included in my tuition?
- Weekly 2-hour live sessions
- Project-based learning using real-world health challenges
- Guided AI exploration
- Weekly study materials and assignments
- Work on prototyping a solution for one selected real-world problem in life sciences
- Individualized project feedback
- Access to a small, curated peer group
At the end of the program, students will also participate in a Demo Day where they will pitch their prototype. They will also receive a Certificate of Completion.
What if I miss a live session?
Recordings of all live sessions will be available to students in the course portal for on-demand access until the end of the course duration.
4. Post-program Details
Are course materials accessible after the program?
Yes, students will have lifetime access to any PDFs and reading materials provided via Google Drive, allowing them to refer to them at any time after the program.
Are there any follow-up programs for those who completed this program?
Yes, if students wish to continue building their AI portfolio independently or work on challenging new projects in-depth and require mentorship, they can enroll in the IMPACT Labs 1:1 Mentorship program. For more details and to express interest, please email contact@impactlabsacademy.com.
Will I receive a letter of recommendation after this program?
Please note that this program does not include a college recommendation letter. However, students who continue into the IMPACT Labs 1:1 Mentorship program may be eligible for a letter of recommendation upon completion, at the mentor’s discretion and based on demonstrated merit and commitment.
IMPACT Labs Academy 