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I am a final year BS-MS student at the Indian Institute of Science Education and Research (IISER), Pune, India. Currently, I am a Research Fellow at the International Institute of Information Technology (IIIT), Hyderabad advised by Professor CV Jawahar and Dr. U. Deva Priyakumar. I am a part of Healthcare with AI (HAI) team at IIIT.

I am interested in building systems that can understand and generate multimodal data like image+text, video+audio, etc. For integration of such systems in the real world, it is also important that the systems are interpretable and robust. This motivates me to work on interpretability and robustness of multimodal AI systems. My current research focuses on buliding interpretable multimodal systems for application in healthcare and drug generation & discovery.

Updates


Email | GitHub | Twitter | Resume | NLP Resume | CV Resume | LinkedIn


Achievements

Publications

LigGPT-Model

LigGPT: Molecular Generation using a Transfomer-Decoder Model
Viraj Bagal, Rishal Agarwal and U. Deva Priyakumar Under review
Paper | AAAI_Paper_Version | Code | Slides | Video Presentation

MMBERT

MMBERT: Multimodal BERT for Improved Medical VQA
Yash Khare*, Viraj Bagal*, Minesh Mathew, Adithi Devi, U. Deva Priyakumar and CV Jawahar International Symposium on Biomedical Imaging (ISBI), 2021
Paper | Code | Slides | Video Presentation

Personal Projects

GNN

Keyword Spotting from Speech Data
Code | Model Comparisons

GNN

Text Classification using Graph Neural Networks
Notebook | Model Comparisons

obj

Semi-supervised Ecommerce Product Matching
Code

obj

Wheat Head Object Detection
Code

obj

CycleGAN: From Photos to Monet paintings and viceversa
Code

FMix

Re-implementation of Ethan Harris et al. FMix: Enhancing Mixed Sample Data Augmentation
Article | Code

Chestxray

Re-implementation of Ekagra et al. Jointly Learning Convolutional Representations to Compress Radiological Images and Classify Thoracic Diseases in the Compressed Domain. ICVGIP 2018
Report | Code

PANDA

Prostate cANcer graDe Assessment (PANDA) Challenge, Kaggle
Leaderboard: Stood 16th. Top 2%.