360+ national & international awards
AIClub Research Institute
Turn ideas into research that stands out.
A high-touch research program for middle and high school students who want to build original AI projects, publish stronger work, and compete with depth.
1:1 mentorshipPublication-ready outcomesFlexible pacing
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Original researchStudent-led questions, mentor-guided rigor.
1:1 guidancePh.D. mentors and milestone-based support.
Research outcomes
Why AIClub Research Program?
100+ research publications(last 24 months)
10+ student patent filings
AIClub's research program empowers middle and high school students to design and execute personalized research projects on topics they care about, including science, healthcare, climate, sports, music, and more.
Why this program feels different
Built around originality, not templates.
Students work from their own interests, learn the research process step by step, and build toward a result that feels genuinely theirs.
Every Project is Unique
Every student creates a project tailored to their interests and goals. No two projects are the same, allowing students to explore their passions through meaningful, individualized work.
Gateway to Professional Publications
We guide students toward competitions and publication paths tailored to their project and academic level, including professional publications typically pursued by graduate students and professors.
No Prerequisites Required
Each program is designed around the student's current programming and AI knowledge, providing the foundations they need before moving into advanced research.
Flexible and Personalized Schedules
Start when it suits you. Session time, frequency, and duration are customized around each student's schedule and learning pace.
Mentor collective
Meet our leaders.
Students work with practitioners, founders, and researchers who bring deep academic and real-world AI experience to every project.
Dr. Nisha Talagala
Founder & AI Systems PioneerCEO and founder of AIClub, Nisha is a recognized operational ML leader with more than 20 years of experience in distributed systems, product leadership, and software development.
Dr. Sindhu Ghanta
Head of Machine Learning, Pyxeda.aiSindhu has research experience spanning histopathological imaging, monitoring production ML systems, and machine learning innovation.
Dr. Amit Gupta
Head of Products, Pyxeda.aiAmit brings more than 20 years of experience in large-scale distributed systems design and development, with extensive work in networking, systems, and security.
Swaminathan Sundararaman
CTO & Co-founder, Pyxeda.aiSwami is a leader in operational machine learning, edge computing, distributed systems, and storage systems.
Venkata Duvvuri
Director of Data Science, OracleVenkata is a data science leader and adjunct faculty member with broad experience in analytics, machine learning, and large-scale data.
Bharath Ramsundar
Founder & CEO, Deep Forest SciencesBharath is the lead maintainer of DeepChem and a Stanford-trained researcher focused on deep learning applications in drug discovery.
Dr. Smriti H. Bhandari
Researcher & EducatorSmriti is an accomplished researcher and educator with extensive experience in computer vision, machine learning, and database systems.
Dr. Vani Kandasamy
AI Research MentorVani specializes in machine learning research and has taught computer vision, natural language processing, social network analysis, and data privacy.
Originality and ethics
How student work stays authentic.
Strong outcomes come from a strong process. The program emphasizes research integrity, transparent experimentation, and responsible use of modern AI tools.
- Self-generated hypotheses. Students start from their own interests and questions.
- Citation and reproducibility. Mentors teach students to document sources and experiments.
- Responsible AI use. Originality, transparency, and authorship remain central.
- Integrity checks. Projects progress through iterative reviews and feedback loops.
Program flow
From curiosity to a polished final output.
The workflow blends idea development, foundational learning, experimentation, mentor review, and communication support.
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Project spotlight
A few directions students have explored.
Students tackle scientific, technical, and creative questions while learning how to justify choices and communicate results.
Climate AI
Wildfire Prediction
A computer-vision project for spotting wildfire smoke earlier from trail and field imagery.
Biotech AI
AI-driven Drug Discovery
Students explored machine-learning workflows that accelerate the search for promising drug candidates.
Creative AI
AI Ballet Instruction
An interdisciplinary project combining movement analysis and AI to make dance coaching more accessible.
Showcase and publication culture
Students do more than finish a project.
They practice presenting, revising, and packaging their work for a real audience.
Student Research Symposiums
Students present their work publicly and practice defending their findings with confidence.
Publication-ready papers
Projects can evolve into polished writeups with research framing, results, and professional presentation assets.
Annual institute momentum
Weekly mentorship builds toward larger milestones, showcases, and submission cycles.
FAQ
What families usually ask first.
Core questions about how the program starts, what students work toward, and how the pace is managed.
The opening sessions identify the student's interests, brainstorm viable research ideas, and assess the AI and coding support needed. Once a direction is feasible, the team creates a custom plan with concept learning, experimentation, and milestone-based mentoring.
Apply now
If the idea matters, the process should too.
Book a free consultation to talk through interests, research goals, and whether the institute is the right fit for your student.
Book a research consultation Limited openings are available for the current research cohort.