Center for Applied Artificial Intelligence
A guided research lab working across multimodal AI, vision–language models, generative systems and the ethics that hold them accountable — built so that first-time researchers can publish real work.
01 — The Lab
CAAI is an experimental research lab for students entering artificial intelligence, machine learning, computer vision and cross-modal systems.
We provide a guided environment where beginners learn research methodology, implementation practice, paper writing and experimental design under structured mentorship — not by watching, but by running projects end to end. Members join a cohort, take a question, and carry it through to a preprint, a journal submission or a released dataset.
The lab supports students learning Korean and preparing for academic or professional transitions to Korea and elsewhere, while building research profiles for international higher education.
02 — Research Areas
Merging vision, text and audio into systems that read the world the way people do — visual question answering, captioning, and cross-modal alignment.
Fairness, accountability and transparency in machine learning — measuring where models fail people, and designing evaluations that catch it early.
Large language models and diffusion systems for generating text, images, audio and code, and the architectures that make them controllable.
Applying the same techniques to healthcare, education and environmental problems where better models translate into better outcomes.
03 — Current Work
Learning a mapping from visual input to musical output — encoding an image into a shared representation and decoding it into audio that carries the scene's structure, mood and rhythm.
Gurpreet Singh · Lamia Qamar
Turning written narrative into sequential visual storytelling — segmenting a script into beats, then generating panel layout, imagery and dialogue that stay consistent across the sequence.
Trina Banerjee · Mukhthikka · Gurpreet Singh
Bringing the lab's cross-modal methods to molecular biology — combining sequence data, imaging and published literature in a single representation to support target selection and outcome prediction in gene editing.
Sudipta Patil · Gurpreet Singh
A collaboration run across borders, pairing the lab's AI methods with research in international business, ESG and media — and testing how a distributed team actually sustains a shared research programme.
Ritika Kanojia · Alimpia Roy · Gurpreet Singh
04 — Dispatch
05 — Join Us
CAAI is accepting graduate research assistants and undergraduate research interns. We look for strong programming ability — Python, PyTorch or TensorFlow — and the patience research actually takes.
