I’m a research scientist by trade, currently on a self-funded sabbatical to study the mathematics underlying machine learning 1. Previous positions include:
|senior software engineer|
|senior staff research scientist||Intel Research Berkeley||Intel|
|member of research staff||Computer Science Laboratory||Xerox PARC|
|Ph.D.||Computer Science||U.C. Berkeley|
|surface warfare officer||USS MERRILL (DD 976)||U.S. Navy|
|B.S.||Electrical Engineering||U.C. Berkeley|
I’ve published and reviewed research papers on topics including human-computer interaction, computer-supported cooperative work, international development, and sociolinguistics; ubiquitous computing and sensing systems; and database and distributed systems. Much of this work has involved a substantial amount of data science and GIS work.
This is covered in more detail here.
I don’t just mean, “how does backprop work” – that’s just the first stop of the deep learning hype train. Well, yes, I’ve been riding that train, too. But I’ve also been wading into stuff like optimization, Fourier analysis, and mathematical statistics that were not fashionable for computer scientists when I was in school. ↩