A headshot of Nathan.
  • Machine learning researcher (spends some time as a scientific writer).
  • Goal: to understand and develop safe and societally beneficial autonomous systems.
  • Current:¬†ūü§ó Research Scientist at HuggingFace ūü§ó.
  • Priors:¬†Ph.D. from Berkeley AI; Cornell ECE¬†/ C150 `17; Intern at DeepMind, Facebook¬†AI¬†Research, Tesla.
  • want to chat?¬†I host public office hours at ML Collective.

About me

Hello! I am a Research Scientist at HuggingFace.

I recently finished my PhD at the University of California, Berkeley, Department of Electrical Engineering and Computer Sciences, advised by Professor Kristofer Pister in the Berkeley Autonomous Microsystems Lab, and pseudo-advised by Roberto Calandra at Meta AI Research!

Hello! I am a Research Scientist at HuggingFace.

I recently finished my PhD at the University of California, Berkeley studying the intersection of robotics and machine learning. I was a member of the Department of Electrical Engineering and Computer Sciences, advised by Professor Kristofer Pister in the Berkeley Autonomous Microsystems Lab, and pseudo-advised by Roberto Calandra at Meta AI Research! I am actively involved in outreach and inclusion efforts and an advocate for mental health -- I was the EEGSA wellness chair and founder of the UC Berkeley Equal Access to Application Assistance program.

Prior to UC Berkeley, I was a proud member of Cornell Electrical and Computer Engineering 2017 where I learned to do research with the Lab of Plasma Studies and the SonicMEMs Lab. I bring my research foundation in hardware, models, and physics to the data-driven world of machine learning. At Cornell, I was a part of Cornell Lightweight Rowing.

I am happy to be a product of The Ocean State.

Nathan Lambert is a Research Scientist at HuggingFace. He received his PhD from the University of California, Berkeley working at the intersection of machine learning and robotics. He was advised by Professor Kristofer Pister in the Berkeley Autonomous Microsystems Lab and Roberto Calandra at Meta AI Research. He was lucky to intern at Facebook AI and DeepMind during his Ph.D. Nathan was was awarded the UC Berkeley EECS Demetri Angelakos Memorial Achievement Award for Altruism for his efforts to better community norms.

I like to try and have fun between my many projects. You can find me on Strava, I also happen to be a brand ambassador for Picky Bars. I actively track my health, cook, and read (recipe and book pages in construction).

News

  • June 11 2022:¬†I'm co-organizing a workshop on Building Accountable and Transparent RL at RLDM.
  • June 1 2022:¬†I started my job at HuggingFace ūü§ó.
  • May 2022:¬†I defended my thesis and finished my Ph.D.
  • 26 April 2022:¬†We released a new paper on documentation for RL¬†systems -- Reward Reports. [link]
  • 25 April 2022:¬†I gave a talk at Penn on exploration &¬†model-based RL! [link]
  • 20 March 2022:¬†one of the last papers of my Ph.D. is out -- studying compounding prediction error in MBRL! [link]
  • 8 February 2022:¬†our long-coming white-paper on the integration of RL¬†and society is out from the Center for Long-term Cybersecurity! [link]
  • 27 January 2022: I was lucky to be interning with Martin Riedmiller's team at DeepMind last summer, here's our paper. [link]
  • 1 September 2021:¬†we released a new paper on our simulator, BotNet, for studying high-agent count network control (best paper award finalist)! [link]
  • 27 April 2021: I was awarded the UC Berkeley EECS¬†Demetri Angelakos Memorial Achievement Award for Altruism. [link]
  • 25 April 2021: I had another paper on sociotechnics in AI published in IEEE Transactions on Technology and Society. [link]
  • 21 April 2021:¬†We released an open-source library for model-based reinforcement learning. [link]
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Robotics

Intelligent & novel devices to interact with the physical world.

A conceptual rendering of novel microrobot flight trajectories.
A conceptual rendering of novel microrobot flight trajectories.

Machine Learning

The science of using data to decide in the presence of uncertainty.

The optimization landscape with Bayesian Optimization.

Society

Making sure the stakeholders of automation are in the conversation.

A diagram depicting existing fields of socio-technical inquiry in AI
A diagram depicting existing fields of socio-technical inquiry in AI