What are the properties underlying intelligence? How do these manifest in neural computation? And how can we build software based on these principles? At the intersection of artificial intelligence (AI) and neuroscience, I build probabilistic machine learning systems with neural-inspiration, in pursuit of general AI.
What else am I up to? I’m a runner, a yogi, a traveler, a concertgoer. My bookshelf spreads the gamut from DF Wallace and Heinlein, to Brian Greene and Tim Maudlin.
I’ll occasionally blog (below), but check me out on Twitter @theAlexLavin for more recent ramblings.
I was selected to the Forbes 30 Under 30 list for Science!
Several new workshop papers this fall: Lavin & Mansingkha. “Probabilistic programming for data-efficient robotics”. Int’l Conference on Probabilistic Programming, 2018. Many probabilistic programming languages decouple model- ing and…