Abhijeet Bhattacharya

Graduate Student Researcher at Smart Health Lab, Oakland University

Email: bhattacharya399@gmail.com, bhattacharya@oakland.edu

Areas of Interests

Classical Computer Vision algorithms employed in conjunction with Deep Learning, Video Understanding, Vision Language Models, and also Explainable AI.

About me

Hi! Welcome to my webpage. I am Abhijeet Bhattacharya a Computer Science Engineering graduate student at School of Engineering and Computer Science, Oakland University under Dr Tianle Ma. I do my research at the Smart Health Lab in the field of applying Machine learning to medical data to predict the mutation of the cancer cell. In my free time I like to conduct my own research in the field of Computer Vision and Video Understanding. Before coming to Oakland University I was a Data scientist and a Product Engineer at a start up called Coding Blocks in India. I completed my Bachelor's of Technology in Electrical and Electronics Engineering from Guru Gobind Singh Indraprastha University, New Delhi, India.

I have 3 years of work experience in the field of Deep Learning, Computer Vision, and a bit of Autonomous Vehicles. As of December 2024 I am working on Video understanding and Action quality assessment and understanding videos with explainable AI. Visit the publication tab for an up-to-date list of my publications.

For collaborations, please get in touch.

What's New:

Jan, 2025: Started as a Graduate Research Assistant under Dr Tianle Ma.
Sept, 2024: Served as a Teaching Assistant at the Probability and Statistics course.
Sept, 2024: Started my time at Oakland University as a Graduate student (MS in CS).
June, 2024: Got 100% scholarship for my Masters at Oakland University. (Fully funded MS)
April, 2024: (Publication): Abhijeet Bhattacharya, C Mollan, S Gupta, V Pandey. “Combining Triz and NLP to identify promising problem-sloving approaches for emerging Technologies: A Prelimnary study.” IDETC, 2024.
Dec, 2023: Started as a Research Intern under Dr Vijitashwa Pandey.
March, 2023 - Dec, 2023 - Took time off (Personal Health issues)
Jan, 2023: Reviewer for Scientific Reports Journal. (Nature journal).
Oct, 2022: Started my position as Data Scientist and Product Engineer at Coding Blocks.
Oct, 2022: (Undergraduate Thesis): Bhattacharya, A. (2022). "Automatic Seizure Prediction using CNN and LSTM." arXiv. https://doi.org/10.48550/arXiv.2211.02679
Oct, 2022: Reviewer for Springer Nature Journal. (Artificial Intelligence Review)
Oct, 2022: (Publication): A. Bhattacharya, Makarand Tapaswi "Which actions did the gymnast perform? Predicting Sub-actions for Action Quality Assessment in Gymnastics" accepted in Indian Conference on Computer Vision, Graphics and Image Processing, 2022. (Retrieved)
June, 2022: (Publication) M. S. Pillai, A. Bhattacharya, T. Baweja, R. Gupta and M. Shah, "DeepSAR: Vessel Detection in SAR Imagery with Noisy Labels," 2022 IEEE International Conference on Image Processing (ICIP), 2022, pp. 2526-2530, doi: 10.1109/ICIP46576.2022.9898020.
Dec, 2021: Started as a Research Assistant under Dr Makarand Tapaswi.
Sept, 2021: (Publication) "Epileptic seizure prediction using deep transformer model" accepted in International Journal of Neural Systems.
Sept, 2021: Started as a Research Intern under Dr Mubarak Shah.