Neural Collective Matrix Factorization for integrated analysis of heterogeneous biomedical data. - Ragunathan Mariappan; Aishwarya Jayagopal; Ho Zong Sien; Vaibhav Rajan (Bioinform., 2022)

Multimodal Representation Learning With Text and Images. - Aishwarya Jayagopal; Ankireddy Monica Aiswarya; Ankita Garg; Srinivasan Kolumam Nandakumar (CoRR, 2022)

WISER: Weak Supervision and Supervised Representation Learning to Improve Drug Response Prediction in Cancer. - Kumar Shubham; Aishwarya Jayagopal; Syed Mohammed Danish; Prathosh A. P.; Vaibhav Rajan (ICML, 2024)

Personalised Drug Identifier for Cancer Treatment with Transformers using Auxiliary Information. - Aishwarya Jayagopal; Hansheng Xue; Ziyang He; Robert J. Walsh; Krishna Kumar Hariprasannan; David Shao Peng Tan; Tuan Zea Tan; Jason J. Pitt; Anand D. Jeyasekharan; Vaibhav Rajan (KDD, 2024)

ASTER: A Method to Predict Clinically Relevant Synthetic Lethal Genetic Interactions. - Herty Liany; Aishwarya Jayagopal; Dachuan Huang; Jing Quan Lim; Nur Izzah NBH; Anand Jeyasekharan; Choon Kiat Ong; Vaibhav Rajan (IEEE J. Biomed. Health Informatics, 2024)

GANDALF: Generative AttentioN based Data Augmentation and predictive modeLing Framework for personalized cancer treatment. - Aishwarya Jayagopal; Yanrong Zhang; Robert John Walsh; Tuan Zea Tan; Anand D. Jeyasekharan; Vaibhav Rajan (ICLR, 2025)

Farm-Level, In-Season Crop Identification for India. - Ishan Deshpande; Amandeep Kaur Reehal; Chandan Nath; Renu Singh; Aayush Patel; Aishwarya Jayagopal; Gaurav Singh; Gaurav Aggarwal; Amit Agarwal; Prathmesh Bele; Sridhar Reddy; Tanya Warrier; et al. (CoRR, 2025)