I have a passion for leveraging basic, academic research to solve large-scale industrial problems. My primary goal is to be a bridge between academia and industry by making scientific information interpretable to all and helping to draw connections between scientific advancements and pressing industrial problems.
I’m currently the Director of AI at Rebuy, a personalized search and recommendations platform for D2C e-commerce brands. I work with an amazing team of engineers and researchers to investigate topics such as language model agent systems, reinforcement learning for product merchandizing, personalized product ranking, and more. Prior to Rebuy, I was a Research Scientist at Alegion, where I built pre-labeling systems that improved human efficiency by 200+% on image and video data annotation tasks. Additionally, I worked for Salesforce Commerce Cloud for two years, where I developed embedding and tagging models used for content-based recommendations (i.e., similar and complimentary products).
I earned my Ph.D. in Computer Science from Rice University (advised by Dr. Anastasios Kyrillidis) in Houston, TX. My research interests are related to math and machine/deep learning, including non-convex optimization, theoretically-grounded algorithms for deep learning, continual learning, and practical tricks for building better systems with neural networks. Prior to Rice, I was an undergraduate student in Computer Science at UT Austin, where I worked with the Neural Networks Research Group on research in genetic algorithms and evolutionary computation.