Welcome!
I’m an incoming tenure-track assistant professor in the Department of Electrical and Computer Engineering at The University of British Columbia (UBC), where I will direct the Artificial Intelligence in Robotics & Engineering (AIRE) Lab.
We’re Hiring
The AIRE Lab is looking for highly motivated graduate students that are interested in advancing research at the intersection of machine learning, reinforcement learning, robotics, control, autonomous systems, and computational modeling. We have openings for fully funded MASc and PhD positions within the Department of Electrical and Computer Engineering at UBC’s Vancouver campus, beginning September 2025. More details can be found in the following application instructions.
The first round of application reviews will take place on December 20th, 2024. For PhD applicants, applications submitted before December 31st, 2024 are preferred and will be considered by the department for a four-year fellowship. The final deadline for all applicants is January 15th, 2025.
Research Interests
Realizing the full potential of artificial intelligence (AI) requires a dual approach: developing engineering methodologies to design AI systems, and designing AI algorithms to solve specific engineering problems. My research leverages this dual perspective to develop AI systems for purposes of control, robotics, autonomy, dynamics modeling, and computational engineering. Specifically, my research asks: how can we engineer AI systems within budget constraints, certify them against stakeholder requirements, and ensure that they meet the needs of the end user? On the other hand, how can we design AI algorithms that embrace the unique characteristics of engineering applications?
Towards answering these questions, my research develops theory and algorithms that span topics from multiagent reinforcement learning, to physics-informed machine learning, to the reliable use of large language models in the design of autonomous systems. Through compositional approaches to system design, my research enables independent development and testing of separate AI modules, with the goal of facilitating the process of reliably deploying their compositions in practice. By integrating data with prior physics and engineering knowledge, my research creates systems that effectively control hardware after mere minutes of data collection and training. More broadly, my research aims to address the diverse and ever-expanding challenges and opportunities associated with engineering AI systems to tackle societally impactful problems.
If you’re interested in learning more, see my publications for an overview of relevant past projects.
About Me
I’m currently a postdoctoral researcher in the Robotics and Embodied AI Lab at Mila and l’Université de Montréal.
I received my Ph.D. (2024) and M.Sc. (2021) degrees in Computational Science, Engineering, and Mathematics from The Oden Institute at The University of Texas at Austin. There, I worked with Professor Ufuk Topcu as a member of the Center for Autonomy. I was also a member of the Center for Scientific Machine Learning.
Prior to my graduate studies in Austin, I obtained a Bachelors of Applied Science degree from The University of British Columbia, where I studied Engineering Physics and minored in Honours Mathematics.