I am a senior machine learning researcher at Apple. I build experimental product prototypes that leverage modern research in machine learning, artificial intelligence, deep learning, and computer vision. I also contribute to fundamental research through conference publications. My work has primarily focus has been efficient machine learning on edge devices, though my interests broadly encompass modern research efforts in artificial intelligence.
I earned my PhD in Computer Science in June 2022 from the University of Washington. I studied efficient deep learning under Ali Farhadi and Mohammad Rastegari, focusing on model compression in scenarios with limited data. Concurrent to completing my PhD, I worked at Xnor.Ai, where I built efficient machine learning solutions capable of running on low-compute edge devices (e.g. smarthome doorbells, home security cameras). I developed state-of-the-art efficient models for image classification, object detection, segmentation, facial recognition, and keyword spotting. Not all of my product-related work could be made public, but you can read more about my public-facing contributions to research (as well as patents) on my Google Scholar page. You can view my resume here.
I’ve lived in every corner of the United States for some period of time, but am currently based in Santa Monica, CA. In my spare time, I enjoy hiking in Malibu, Griffith Park, and the San Gabriels. I also enjoy cooking, playing guitar, and traveling.
I occasionally post short articles on whatever I feel like (usually cooking). Check it out here.