Ransalu Senanayake
Ransalu Senanayake
Assistant Professor
Computer Science

Welcome to the Laboratory for Learning Evaluation and Naturalization of Systems (LENS Lab). We focus on operationalizing machine learning (ML) models in autonomous systems, robots, and beyond. Our mission is to develop tools that not only evaluate these models but also naturalize them and making them compatible with the complex, dynamic requirements of the real world. Evaluating models solely by accuracy on a held-out dataset is insufficient for true readiness. That's why we ask deeper questions: When and how do models fail? How can we explain black-box neural networks? How do we assess uncertainty, fairness, and adaptability to new environments? Our work helps engineers build robust, trustworthy systems while guiding policymakers in setting legal and ethical standards. Ransalu Senanayake is the director of the LENS Lab and is an Assistant Professor in Computer Science at the School of Computing and Augmented Intelligence (SCAI), Arizona State University (ASU). He is also a member of the CHART center. Previously, he was a postdoctoral scholar in the Machine Learning Group at Stanford University, working with Carlos Guestrin, Emily Fox, and David Scheinker. He also collaborated with Mykel Kochenderfer in Aeronautics & Astronautics and was a visiting PhD student in Dieter Fox’s lab at the University of Washington. He earned his PhD in Computer Science under Fabio Ramos at the University of Sydney and an MPhil in Industrial Engineering from the Hong Kong University of Science and Technology. He grew up in Sri Lanka.

News

June '15
Som and Aditya's paper "Trustworthy Explainations for Robot Behaviors" was accepted to IROS'25.
May '25
Dec '24
Som and Aditya will be presenting four workshop papers at NeurIPS'24.
Nov '24
We are currently accepting PhD students with strong backgrounds in ML, robotics, CV, or NLP. Master's and undergrad students enrolled at ASU can also apply to the LENS Lab. See Join Us!
Nov '24
Kelly Raines defended her Barrett Honors thesis titled "Generative AI-Aided Navigation for the Visually Impaired and Blind". Congrats!
May '24
Som's paper "Failures Are Fated, But Can Be Faded: Characterizing and Mitigating Unwanted Behaviors in Large-Scale Vision and Language Models" was accepted to ICML'24 as a spotlight-designated paper 🎗 (top 3.5%).