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.

After a few years developing human-level AI for robotics with Vicarious, I’m moving on to pursue the emerging paradigm of probabilistic programming. Stay tuned!

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!

Interested in my CV? You can also check out some papers on my Google Scholar and arXiv profiles.

Latest Blog Post

05 Sep 2018 . Machine Learning . New Workshop Papers! Comments

New workshop papers this fall*: George, Lavin, et al. “Cortical Microcircuits from a Generative Vision Model”. Conference on Cognitive Computational Neuroscience, 2018. Understanding the information processing roles of…

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  • “In programming, the hard part isn’t solving problems, but deciding what problems to solve.” - Paul Graham

  • 2014-2019

    AI ninja training, with Vicarious and Numenta

  • 2013-2014

    Carnegie Mellon, studied computational mechanics and worked on a lunar rover

  • 2008-2012

    Cornell University, studied mechanical & aero engineering, with cubesat research