Summary
Vijay Sadashivaiah is a Senior Scientist in Machine Learning with a decade of experience applying deep learning and multimodal representation learning to healthcare, autonomous systems, and drug discovery. Currently at Merck, he explores pre-training and fine-tuning large foundation models for drug discovery, building on a PhD-level research trajectory at RPI where he developed explainable medical-image classifiers and methods to suppress semantic concepts for privacy. His work spans industry and academic labs—Bosch, IBM Research, Lieber Institute, Johns Hopkins and MIT—where he engineered practical pipelines (including a 700k-image instruction dataset for VLMs) and achieved measurable performance gains across VLMs, radar/LiDAR encoders, and transfer learning. He co-led a $400k collaborative grant, publishes in interdisciplinary venues, and combines strong systems engineering with a knack for aligning latent representations to background knowledge—an uncommon focus that improves interpretability and fine-tuning outcomes.
10 years of coding experience
11 years of employment as a software developer
Bachelor of Engineering - BE Electrical Engineering, Bachelor of Engineering - BE Electrical Engineering at PES University
Johns Hopkins University
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Rensselaer Polytechnic Institute