About
Rajesh Ramaswamy is building the next generation of intelligent systems that transform how we understand, predict, and engineer complex systems across health, finance, and the physical world. His work focuses on turning traditionally empirical disciplines into continuously learning, AI-driven systems. Across startups, growth-stage companies, and global enterprises, he has led the development and deployment of AI systems that deliver measurable scientific, operational, and commercial impact.
He is currently Head of AI at Precede Biosciences, where he leads the strategy, development, and deployment of foundational AI systems for diagnostics and data products. His work is focused on transforming blood into a continuously updated representation of human biology, enabling earlier and more precise interventions, and ultimately a shift from reactive to adaptive healthcare. By combining multimodal data, machine learning, and scalable AI infrastructure, he is helping build systems capable of decoding complex diseases from wide variety of signals, including genomic and immune signals, in blood at population scale.
Previously, Rajesh was Senior Vice President and Founding Head of AI at Sail Biomedicines, where he led the design and deployment of the company’s AI system for generating a novel class of programmable medicines. His work advanced a shift in drug creation from a process driven by chance to one grounded in engineering, where outcomes can be systematically improved and accelerated. The AI platform he helped pioneer contributed to multiple programs, including an in vivo CAR-T program.
Earlier, Rajesh founded and built the Data Driven Innovation office at EMD Serono, the North American biopharma business of Merck KGaA. There, he established enterprise AI capabilities and applied machine learning across the organization, enabling more effective commercial strategies and contributing to billion+ dollar product launches in Neurology, Immunology, and Oncology.
Rajesh began his career in quantitative finance, where he developed machine learning systems operating at the scale of billions of options trades per day across global markets.
He holds a Ph.D. in Computer Science from ETH Zürich, Switzerland.