I’m from Sri Lanka, living in Tokyo, Japan for the last ten years. I work as a Research Engineer at the AI4Science Team at SB Intuitions. With a background in healthcare and drug discovery from my time at the University of Tokyo, Lily MedTech, and Preferred Networks (PFN), I build machine learning models to tackle real-world challenges. I earned my PhD in Computer Science (AI) from the Tokyo Institute of Technology.
Outside of work, I’m a casual runner and a coffee lover walking around Tokyo to find the best cafes. You can track my running progress on Strava or check out the cafes I’ve enjoyed visiting.
Yiming Zhang, Jun Jin Choong, Kaushalya Madhawa, Keisuke Ozawa, “AutoLead: An LLM-Guided Bayesian Optimization Framework for Multi-Objective Lead Optimization”, bioRxiv preprint 2025
Nuwan Bandara, Dasun Premathilaka, Sachini Chandanayake, Sahan Hettiarachchi, Vithurshan Varenthirarajah, Aravinda Munasinghe, Kaushalya Madhawa, Subodha Charles, “Deep geometric framework to predict antibody–antigen binding affinity”, Journal of Structural Biology 2025 [bioRxiv]
Kaushalya Madhawa and Tsuyoshi Murata, “MetAL: Active Semi-Supervised Learning on Graphs via Meta Learning”, Asian Conference on Machine Learning (ACML), 2020 [Arxiv]
Kaushalya Madhawa, Katushiko Ishiguro, Kosuke Nakago, and Motoki Abe, “GraphNVP: An Invertible Flow Model for Generating Molecular Graphs”, Arxiv preprint, 2019 [Arxiv]
Kaushalya Madhawa, Choong Jun Jin, Arie Wahyu Wijayanto, and Tsuyoshi Murata, “Robustness of Compressed Convolutional Neural Networks”, Workshop on Big Data for CyberSecurity (BigCyber-2018), IEEE International Conference on Big Data, Seattle, Washington, 2018