Hi, I am a Master's student in Graduate School of AI at Korea Advanced Institute of Science and Technology (KAIST). I am fortunate to have Prof. Edward Choi as my advisor. I am interested in Artificial Intelligence at the intersection of Computer Vision, Machine Learning & Healthcare. I am currently working on out-of-distribution detection in deep learning.
We define a new task, natural attributebased shift (NAS) detection, to detect the samples shifted from the training distribution by some natural attribute such as age of subjects or brightness of images.
We also introduce benchmark datasets in vision, language, and medical for NAS detection.
Conducting research in Vision and Language applications and introduced a new task, ViQAR: Visual on
Answering and Reasoning, which focuses on automatic generation of the answer, and of a rationale,
given a visual query.
Developed a temporal forecasting solution based on the historical data reported by Central Pollution
Control board to predict the real-time and fine-grained air quality information in five locations of Delhi.
We introduced a new task, ViQAR, in which the model generates the complete answer and rationale. We also proposed an end-to-end, attention-based
encoder-decoder architecture to solve this task, and showed that our model generates strong answers and rationales through qualitative and quantitative evaluation, as well as human Turing Test.
As a part of the Celestini Project, sponsored by Google and Marconi Society and mentored by Dr. Aakanksha Chowdhery, we developed Clair: Air pollution forecasting in Delhi, a temporal forecasting solution based on the historical data reported by Central Pollution
Control board to predict the real-time and fine-grained air quality information in five locations of Delhi. We were awarded Second Prize for our novel solution and also had the opportunity of presenting our work at GlobalSIP 2019.