Multimodal AI
Vision, text and audio in one system — captioning, visual question answering, cross-modal alignment.
About
Fostering the next generation of researchers.
CAAI is an experimental research lab for students entering artificial intelligence — a place to learn the craft by running real projects, not by reading about them.
01 — Mission
Teaching research by doing research.
CAAI Lab supports students entering the field of artificial intelligence, machine learning, computer vision and cross-modal systems. We provide a guided research environment where beginners learn research methodologies, implementation practices, paper writing and experimentation under structured mentorship.
Members take a question and carry it end to end — literature, method, implementation, evaluation, write-up. The work that comes out is theirs, and it goes out under their names.
02 — Organization
Under The Korean Academy.
CAAI Lab operates under The Korean Academy, a registered organization in India. The lab supports students learning Korean and preparing for academic or professional transitions to Korea or other countries, while building research profiles for international higher education opportunities.
- Founded
- 2022
- Operating under
- The Korean Academy
- Registered in
- India
- Researchers & alumni
- 54
03 — How the lab works
Structured mentorship, real deliverables.
- Guided projects. Every member joins an active project with a defined scope, a timeline and a mentor — currently image-to-music generation, text-to-comic generation, multimodal AI in gene editing, and an international research collaboration.
- Research methodology. Reading papers properly, framing a question, designing an experiment and reporting results honestly.
- Implementation practice. Python with PyTorch or TensorFlow, working through the gap between a paper's method section and code that runs.
- Writing and submission. Drafting, revising and submitting to preprint servers, journals and conferences — twelve papers and datasets so far.
04 — What we work on
Four pillars.
AI Ethics & Bias
Fairness, accountability and transparency — measuring where models fail people.
Generative Models
Language and diffusion models for text, image, audio and code generation.
AI for Social Good
Healthcare, education and environmental problems where better models matter.
Join us
Come and do the work.
The lab takes graduate research assistants and undergraduate research interns each term. If you can program and you're willing to be patient with an experiment, we want to hear from you.