Artificial Intelligence
Research on the Core Technology of A.I.
STARC's research collaboration program matches motivated students and early-career researchers with leading professors and mentors across multiple disciplines. Each collaboration is designed around concrete research questions, with a clear structure that moves from background reading and skill-building through experiment design, implementation, and publication.
This is not about padding résumés or producing contest-style projects. Our goal is sustained work that generates real insight, meaningful impact, and, when appropriate, peer-reviewed publications. We prioritize merit over background, ensuring that talent, curiosity, and drive—not institutional access—determine who gets to participate in cutting-edge research.
Explore our active research streams across multiple disciplines. Each area connects students with mentors working on current research questions, offering pathways into serious academic work regardless of your starting point.
Click the following blocks to find more about a research topic
Research on the Core Technology of A.I.
Research on Applications of Data Science
Data Science Methods for Social Sciences
Research on the Frontier of Economics
Research on Education Methods
International Politics on Technologies
Data Science Methods for Psychology
Computational Methods for Biology
Data Science Methods to for Finance
Research on the Statistical Core of A.I.
Share your academic background, areas of interest, and any prior experience with research or independent projects. No need for polished credentials—just show us how you think.
Tell us what excites you about research and why you're ready to take on a real project. We look for clarity, curiosity, and commitment—not perfection.
Our team reviews your materials and matches you with a research direction and mentor aligned with your strengths and goals. Select applicants may also be invited for a short conversation with our advisors.
Once matched, you'll receive a formal invitation to join a live project led by a university researcher. This is not a training simulation—you'll be contributing to real work.
You'll join a structured research team, receive mentorship, collaborate on defined tasks, and grow as an independent thinker and contributor.