Madhumitha Ravichandran is a PhD candidate is interested in advancing heat transfer and sur- face engineering techniques to enhance the safety and performance of nuclear energy systems and to reduce environmental impacts. Specifically, her work is focused on new methods to in- crease boiling heat transfer limits, a key issue for the nuclear industry and other high-technology applications, such as aerospace and computer cooling. Madhumitha’s past research includes the computational modeling of boiling phenomena in nuclear reactors, which yielded new findings on bubble formation on engineered surfaces and the development of innovative AI-driven approaches to data analysis. Most recently, Madhumitha created one of the first autonomous thermal-hydraulics laboratories. With the support of her MathWorks Fellowship, she will refine this system and complete a “self-driving” experiment capable of discovering new physical phenomena and identifying autonomous heat transfer solutions. Drawing extensively on MATLAB tools Madhumitha’s work is changing experimental research in thermal science and offering new possibilities for AI applications in the field. She has also created custom tools that are valuable for thermal science and hold great potential for machine-learning research in other fields.