Nathan O. Lambert

I am a third year Ph.D. student at the University of California, Berkeley, Department of Electrical Engineering and Computer Sciences. I have the pleasure of being advised by Professor Kristofer Pister. For the summer of 2019, I had the pleasure to be working with Roberto Calandra at Facebook AI Research, which is now a continuing collaboration!

I completed my undergraduate education at Cornell University's College of Engineering in 2017. While there, I worked with the Lab of Plasma Studies and SonicMEMs Lab .

Email  /  CV  /  Google Scholar  /  LinkedIn  /  Github  /  Blog

Fun news in my life is that I will be lecturing CS188: Intro to Artificial Intelligence here in spring 2020.

Research

I'm interested in the intersection of machine learning and control, with applications to experimental robotics. With Kris, I am working on direct synthesis of robot controllers with model-based reinformcent learning where we do not need any past system knowledge.

Learning for Microrobot Exploration: Model-based Locomotion, Robust Navigation, and Low-Power Deep Classification
Nathan Lambert, Fahran Toddywala, Brian Liao, Eric Zhu, Lydia Lee, Kristofer S.J. Pister
Preprint, 2020
Paper   /  More

A collections of steps towards an autonomous microrobot. Recent work has pushed capabilities of the device forward, but little progress has been made in creating an autonomous platform.

Objective Mismatch in Model-based Reinforcement Learning
Nathan Lambert, Brandon Amos, Omry Yadan, Roberto Calandra
Arxiv Preprint, 2020
Paper   /  Workshop Presentation   /  More

Learning how to walk with a real-world hexapod using a hierarchy of model-free RL for basic motion primitives with model-based RL for higher level planning.

Learning Generalizable Locomotion Skills with Hierarchical Reinforcement Learning
Tianyu Li, Nathan Lambert, Roberto Calandra, Franziska Meier, Akshara Rai
International Conference on Robotics and Automation , 2020
Paper   /  Related Press

Learning how to walk with a real-world hexapod using a hierarchy of model-free RL for basic motion primitives with model-based RL for higher level planning.

Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learning
Nathan Lambert, Daniel Drew, Joseph Yaconelli, Roberto Calandra, Sergey Levine, Kristofer Pister
IEEE Robotics and Automation Letters (RA-L), 2019
Paper  /  website

We used deep model-based reinforcement learning to have a quadrotor learn to hover from less than 7 minutes of all experimental training data. No system knowledge was needed for thise experiment, reading raw sensor values and commading motor PWMs.

Toward Controlled Flight of the Ionocraft: A Flying Microrobot Using Electrohydrodynamic Thrust With Onboard Sensing and No Moving Parts
Daniel Drew, Nathan Lambert, Craig Schindler, Kris Pister
IEEE Robotics and Automation Letters (RA-L), 2018

A collection of steps towards controlled flight of The Ionocraft, a completely silent microrobot with ion thrust!

Enhanced Lithium Niobate Pyroelectric Ionizer for Chip-Scale Ion Mobility-Based Gas Sensing
K.B. Vinayakumar, Ved Gund, Nathan Lambert, S Lodha, Amit Lal
IEEE Sensors, 2016

We used a pyroelectric crystal to cause dielectric breakdown events in the air, which can be used for chip scale ion based gas sensing.

Teaching
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Lecturer - CS188 Introduction to Artifical Intelligence, Spring 2020.
Website / Co-Instructor / Lecture Cast

Graduate Student Instructor - EECS16B Designing Information Devices and Systems II, Fall 2019.
Website / Instructor

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Teaching Assistant - ECE 3250: Mathematics of Signal and System Analysis, Fall 2016.
Lectures / Instructor

Grader - ECE 4320: Integrated Micro-Sensors and Actuators, Spring 2017.
Instructor

Personal
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I had the pleasure of rowing for Cornell's Varisty Lightweight Crew for four years after walking on, we had some success. At Berkeley, I coached the lightweight rowing team for a year. I am shifting to triathlons & continuing competition - for the endurance training folk you can find my strava here .

Otherwise, my personal interests are generally in nuitrition, training, math, robot ethics, and more. I follow Tesla fairly closely after spending a summer there. Graduate school has been an emergence of reading books for me, and my current recommended list in no particualr order is: Godel Escher Bach, An Eternal Golden Braid; Shoe Dog; A Brief History of Time; Tribe; Deep Nuitrition

Press and Media
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Some of my work has been featured elsewhere. In my time, the ionocraft was featured in the IEEE Spectrum Magazine here. Back at Cornell, a fun robotics-like project was published in Circuit Cellar, and got some press.


Last updated 20 November 2019, this guy makes a nice wesbite.