Publications

Published/Accepted

Sagar D., Jasko, A., Fourouzesh, N. (2024, November). Enhancing Drug Discovery via Physics-Guided Deep Generative Models. Computational Structural Bioinformatics Workshop 2024, Boston, MA.

Chatterjee R., Sagar D., Pourhomayoun M., Kaur M., & Amini N. (2024, June). Detection of Large Vessel Occlusion in Ischemic Stroke Patients using Deep Residual Distilled Convolutional Networks. International Journal of Semantic Computing.

Sagar, D., Dwivedi, T., Gupta, A., Aggarwal, P., Bhatnagar, S., Mohan, A., Kaur, P. & Bhatnagar Sr, S. (2024). Clinical Features Predicting COVID-19 Severity Risk at the Time of Hospitalization. Cureus, 16(3). [ https://pubmed.ncbi.nlm.nih.gov/38690475/ | Impact Factor: 1.2]

Chatterjee R., Sagar D., Pourhomayoun M., Kaur M., & Amini N. (2023, February). Deep Residual Distilled Convolutional Learning For Detection of Large Vessel Occlusion in Ischemic Stroke Patients. In 1st IEEE‬‭ International‬‭ Conference‬‭ on‬‭ Artificial‬‭ Intelligence,‬‭ Medicine,‬‭ Health‬‭ and‬‭ Care‬‭ (AIMHC‬‭ 2024),‬‭ Laguna‬ Hills, California, Feb. 2024. [https://ieeexplore.ieee.org/abstract/document/10504351 | 28.33% Acceptance Rate ]

Sagar, D., Mohammadi F., Pourhomayoun M., Joen J., & Amini N. (2023 October). Deep Learning Based GABA Edited-MRS Signal Reconstruction. In 18th International Symposium on Visual Computing (ISVC 2023), Lake Tahoe, NV, Oct. 2023. [https://link.springer.com/chapter/10.1007/978-3-031-47969-4_2 | 30% Acceptance Rate ]

Sagar, D., Risheh A., Sheikh N. & Forouzesh N. (2023, September). Physics-Guided Deep Generative Model for New Ligand Discovery. In 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB 2023), Houston, TX, Sept. 2023. [ ⭐️ Best paper finalist award ⭐️ | https://dl.acm.org/doi/10.1145/3584371.3613067 | 29% Acceptance Rate ]

Sagar, D., Aggarwal, P., Farswan, A., Gupta, R., & Gupta, A. (2022). GCRS: A hybrid graph convolutional network for risk stratification in multiple myeloma cancer patients. Computers in Biology and Medicine, 149, 106048.
[ https://pubmed.ncbi.nlm.nih.gov/36113255/ | Impact Factor: 7.7]

Sagar, D., Garg, J., Kansal, P., Bhalla, S., Shah, R. R., & Yu, Y. (2020, September). PAI-BPR: Personalized outfit recommendation scheme with attribute-wise interpretability. In 2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM 2020) (pp. 221-230). IEEE Virtual Conference. [ https://ieeexplore.ieee.org/abstract/document/9232589 | 19.5% Acceptance Rate]

Theses

Deep Reconstruction Model for Exposing Low Concentration Metabolites in Edited-MRS Brain Scans.

Multiple Myeloma Cancer Cell Instance Segmentation. A tool to detect and segment MM cancer cells from bone marrow aspirate slides using Deep Learning. [ Published as B.Tech Thesis in IIIT Delhi Thesis Archive 2021. | https://arxiv.org/abs/2110.04275 ]