Ransalu Senanayake is an assistant professor and director of the LENS Lab with 11 years of experience building explainable, uncertainty-aware autonomous systems across domains including autonomous driving, space exploration, and healthcare. His work blends rigorous statistical machine learning, Bayesian inference, and directional statistics with practical deep learning and robotics, developed through postdoctoral research at Stanford and a PhD from the University of Sydney. He has a strong teaching and mentorship background from roles across universities and has translated research into practical tools and frameworks for modeling uncertainty in dynamic environments. Based in Palo Alto, he combines academic leadership with hands-on system design—an engineer who moves from low-level signal processing and embedded implementations to high-level explainability and safety research. A detail that sets him apart: he has repeatedly bridged human factors and machine autonomy, applying gaze and ergonomics research to inform control and interaction models.
10 years of coding experience
2 years of employment as a software developer
Electronic and Computer Engineering, Electronic and Computer Engineering at SLIIT
The University of Sydney
Hong Kong University of Science and Technology (HKUST)
BEng (Hons), Electronic Engineering, BEng (Hons), Electronic Engineering at Sheffield Hallam University
Postdoctoral Scholar, Computer Science, Postdoctoral Scholar, Computer Science at Stanford University
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Ransalu Senanayake - Assistant Professor at LENS Lab