About

Viraj Bagal is a highly skilled Machine Learning Intern currently working at IIIT Hyderabad. He has made significant contributions to two research projects focused on improving healthcare through the implementation of Computer Vision and NLP. In his first project, he proposed an interpretable visual question answering (VQA) system that outperformed previous state-of-the-art models on two medical VQA datasets, resulting in a 5% increase in accuracy and bleu score. Additionally, his model was 66% more efficient than the previous best models. In his second project, he proposed an interpretable state-of-the-art conditional generative network for molecule generation with desirable physicochemical properties. Here as well, his model outperformed previous models in terms of the generation when tested on two benchmark molecule datasets while being 94% smaller than GPT1. Viraj has a strong background in Physics, having completed his BS-MS degree from the Indian Institute of Science Education and Research (IISER), Pune in 2021. He is experienced in Python for ML/DL, and has a strong working knowledge of various models like CNNs, RNNs, LSTMs, Transformers, VAEs, GANs, etc. He is well-versed with the entire research pipeline, having worked on literature survey, ideation, code and model implementation, and paper writing. In addition to his technical skills, Viraj has excellent communication skills, which he has honed through frequent presentations. His tech stack includes ML, Computer Vision, Deep Learning, NLP, Python, Research Scientist, LLM, OpenCV, Scikit, and Pytorch. With 2.20 years of relevant experience, Viraj is a highly motivated and skilled individual who is committed to making a positive impact in the field of healthcare through his research.