Joshua Bloom

Dept. Chair; Professor of Astronomy

UC Berkeley


Josh is the chair of the Astronomy Department and professor at the University of California, Berkeley teaching radiative processes, high-energy astrophysics, astronomy data lab, and a graduate-level “Python for Data Science” course. He has published over 300 refereed articles largely on time-domain transients events, artificial intelligence, and telescope/insight automation. His book on gamma-ray bursts, a technical introduction for physical scientists, was published by Princeton University Press. Josh has been awarded the Data-Driven Discovery prize from the Gordon and Betty Moore Foundation and the Pierce Prize from the American Astronomical Society; he is also a former Sloan Fellow, Junior Fellow at the Harvard Society, and Hertz Foundation Fellow. He was co-founder and CTO of Wise.io, an AI application startup, acquired by GE in 2016.

Much of Josh's current group activities can be found at ML4Science.

Note on Speaking Invitations: In the interest of fostering diverse representation, before inviting me to speak at a conference or the like, I ask that organizers pay particular attention to attracting women and those from underrepresented groups to be on the panel(s)/speaker list. I've served on too many academic and industry panels where the representation of such groups was nil or close to zero. If logistics work out, I'd be happy to participate so long as there are some assurances that it will be a diverse group on stage.


  • Machine learning meets Physics
  • Time domain (Black hole transients, Gamma-ray bursts)
  • Optical/infrared instrumentation


  • PhD in Astrophysics, 2002


  • MPhil in Astronomy, 1997

    Cambridge University

  • AB in Astrophysics and Astronomy and Physics, 1996

    Harvard College

Recent Publications

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Kilonova Luminosity Function Constraints Based on Zwicky Transient Facility Searches for 13 Neutron Star Merger Triggers during O3

Recent Posts

Making a Mask with an E-Ink Banner

We wear masks out in public so often it occurred to me we should be able to dynamically customize them to suit our moods and maybe even …

Dynamic Programming with Python dataclasses and joblib

Starting in Python 3.7, the module dataclasses introduces a decorator that allows us to create immutable structures (like tuples) but …

Serverless Distributed Decision Forests with AWS Lambda

Within the Wise.io team in GE Digital, we have monthly "edu-hackdays" where the entire tech team spends the entire day trying to learn …

Darwinistic Pressure in the Land of Cryptocurrency

For many just waking up to the burgeoning land of programmable decentralized value and trust, Bitcoin and cryptocurrency are …

Towards Cost-Optimized Artificial Intelligence

If accuracy improves with more computation, why not throw in more time, people, hardware, and the concomitant energy costs? Seems …




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