UCLA Ph.D. Research and Recent Experiences

I graduated (Spring 2024) with my Ph.D. in Electrical and Computer Engineering from the University of California, Los Angeles with a focus on causal generative modeling, model security and robustness, and generative model interpretability.
In Summer 2022, I worked at Street Simplified Inc, using machine learning for a trajectory prediction model to enable real-time traffic intersection safety analytics and interventions.
Since Spring 2023, I have worked as a lead Data Scientist and Machine Learning Engineer for StreetMetrics Inc, where we use statistical processes and AI algorithms on geo-temporal datasets for out-of-home advertising measurement and attribution

Learn More: My Research Projects

Past Expereinces

I graduated in 2017 from the University of Tennessee, Knoxville with a BS in Electrical Engineering. I spent three years working in the defense industry at Lockheed Martin Santa Barbara Focalplane working as a test and systems engineering on cryo-cooled electro-optical infrared imaging systems.

Learn More: About Me

Future

My goal is to do research and build models that utilize the latest in robust generative modeling and interpretability to enable higher-quality and more interpretable outputs. I am interested in multi-modality and understanding latent spaces and bottlenecks withing multi-modal and ensemble models. I am also interested in model compression via pruning and quantization, and how we can improve inference on edge-compute.