Gregory J Stein
Curriculum Vitae

Education
Awards
Professional Experience
Talks
Service & Leadership
Teaching
Publications

Education

Ph.D. in Electrical Engineering & Computer Science
Sep 2015 – Feb 2020 | Cambridge, ma MIT, Computer Science & Artificial Intelligence Laboratory
Concentration: Robot Autonomy & Machine Learning | gpa 5.0/5.0

S.M. in Electrical Engineering & Computer Science
Sep 2013 – Aug 2015 | Cambridge, ma MIT, Research Laboratory of Electronics
Concentration: Numerical Modeling & Ultrafast Laser Physics | gpa 5.0/5.0

B.S. in Engineering Physics
Sep 2013 – Aug 2015 | Ithaca, ny Cornell University, College of Engineering
Concentration: Numerical Modeling & Ultrafast Laser Physics | gpa 4.0/4.3

Awards

Best Paper Finalist | Conference on Robot Learning , Oct 2018
Nominated a top-3 paper out of over 300 submissions.

Best Oral Presentation | Conference on Robot Learning , Oct 2018
Selected best presentation for talk to over 400 conference attendees.

Trevor R. Cuykendall Memorial Award | Cornell University , Jun 2013
For outstanding teaching assistantship in Applied & Engineering Physics.

Summa Cum Laude | Cornell University , Jun 2013
For exemplary grade point average.

Honors in Engineering Physics | Cornell University , Jun 2013
Awarded for exceptional undergraduate thesis.

Professional Experience

George Mason University
Robotic Anticipatory Intelligence (rail) Group
Aug 2020 – present Assistant Professor | Robot Planning & Machine Learning

  • I run the Robotic Anticipatory Intelligence & Learning (rail) Group and serve as Directory of the Autonomous Robotics Labratory at George Mason University. Our research, at the intersection of robotics and machine learning, is centered around developing representations that allow robots to better understand the impact of their actions, so that they may plan quickly and intelligently in a dynamic and uncertain world.

MIT | Robust Robotics Group
Sep 2015 – Feb 2020 Ph.D. Graduate Researcher | Robotics & Machine Learning

  • Thesis Committee: Nicholas Roy (Advisor), Leslie P. Kaelbling, George Konidaris, Phillip Isola
  • Developed method for planning with high-level, topological actions to tractably estimate cost when navigating through unknown environments, improving expected cost of travel through real-world environments by 20% yet with orders of magnitude less data than deep reinforcement learning.
  • Formulated sparse map representation to overcome noise limitations of monocular slam to enable noise-robust topological planning in uncertain environments.
  • Created method for realistic synthetic data generation with unsupervised image-to-image translation; demonstrated real-world quadrotor obstacle avoidance trained only on synthetic data.

Niantic | Computer Vision Team
Jan 2018 – Apr 2018 Intern (Jan) | Computer Vision Consultant (Feb – Apr)

  • Taught weekly seminars on computer vision fundamentals—including Sparse Feature Learning, Deep Learning, Monocular slam, and Bundle Adjustment—to nascent Computer Vision Team.
  • Produced a weekly literature deep dive (as consultant) to educate Computer Vision Team on state- of-the-art results and further support development of Niantic’s world-scale ar platform.

MIT | Optics and Quantum Electronics Group
Aug 2013 – Jul 2015 sm Graduate Researcher | Optics & Numerical Simulation

  • Advisor: Franz X. Kärtner
  • Designed and implemented numerical simulation tool to support optics experiments for lab of 12.
  • Co-authored 8 journal and 15 conference publications for work on numerical simulation.

Talks

  • April 2023, talk for Intel's Deep Learning in Practice Series
  • October 2022, talk at MIT
  • August 2022, talk at Brown University

Service & Leadership

Reviewer | Reviewer for ICLR, CoRL, ICRA, RSS Pioneers, 2023

IEEE Big Data Workshop on Multimodal AI 2023 | Program Committee Member & Reviewer, Dec 2023

IROS Session Co-Chair, Oct 2023

Contributed to the National Robotics Roadmap | Attended a workshop at Penn to contribute to the next National Robotics Roadmap. Sep 2023

Mentored 4 High-School Summer Interns | Students hosted in the RAIL Group, recruited via the GMU assip program. Summer 2023

Mentored 2 High-School AI Final Projects | Students were from the Ideaventions Academy. May 2023

Reviewer | Reviewer for ICLR, IROS, CoRL, IEEE Intelligent Systems, 2022

Conference on Robot Learning | Co-Organized Workshop, Dec 2022 Title: Learning, Perception, and Abstraction for Long-Horizon Planning, Co-organized with Rohan Chitnis, 'YZ' Yezhou Yang, Tom Silver, and Jana Košecká

IEEE Big Data Workshop on Multimodal AI 2022 | Program Committee Member & Reviewer, Dec 2022

Mentored 3 High-School Summer Interns | Students hosted in the RAIL Group, recruited via the GMU assip program., Summer 2022

Reviewer | Reviewer for CoRL, NeurIPS, ICLR, RA-L, 2021

Reviewer | Reviewer for top conferences: iclr, corl, icra, rss, 2020

MIT EECS Communication Lab | Communication Advisor, Aug 2016 – Dec 2019
Coached over 100 MIT students in 1-on-1 sessions to improve their technical communication.

MIT Resources for Easing Friction and Stress | Peer Counselor, Jan 2017 – Dec 2019
Counseled students across the EECS department on mental wellness and managing stress.

Princeton CITP Workshops on AI and Ethics | Invitee, Mar 2018 & Nov 2018
Invited as a technical expert at the intersection of AI, Machine Learning, and Robotics to participate in two workshops on AI and Ethics co-organized by the Princeton University Center for Information Technology Policy.

MIT EECS Visiting Committee | Graduate Student Body Co-organizer , Feb 2017
Prepared report and made recommendations for how to improve student wellness and advising quality to panel of experts, reflecting two months of surveys, interviews, and town-hall meetings.

MIT EECS Graduate Student Association | Board Member , Dec 2015 – Dec 2016
Elected Communications Vice President by peers for organization representing 630 graduate students; Co-organized week-long orientation for 120 EECS graduate students.

Teaching

As faculty at George Mason University, I have taught multiple courses at the intersection of Machine Learning, Planning, and Robotics.

  • CS 695: Reinforcement Learning & Decision Making (Graduate), GMU, Fall 2023
  • CS 482: Computer Vision (Undergraduate), GMU, Spring 2023
  • CS 685: Autonomous Robotics (Graduate), GMU, Fall 2022
  • CS 695: Foundations of Planning (Graduate), GMU, Spring 2022
  • CS 682: Computer Vision (Graduate), GMU, Fall 2021
  • CS 482: Computer Vision (Undergraduate), GMU, Spring 2021
  • CS 682: Computer Vision (Graduate), GMU, Fall 2020
  • (Teaching Assistant) Machine Learning (Graduate), MIT, Fall 2015
  • (Teaching Assistant) Fluid Mechanics (Senior Undergrad), Cornell University, Spring 2013

Publications

For a full list of publications, see our publications page.

Publications (Physics)

  • Krishna Murari, Gregory J. Stein, Huseyin Cankaya, Benoit Debord, Frederic Gerome, Giovanni Cirmi, Oliver D Mücke, Peng Li, Axel Ruehl, Ingmar Hartl, Fetah Benabid, and Franz X Kärtner. “Kagome- fiber-based pulse compression of mid-infrared picosecond pulses from a Ho:YLF amplifier”. In: Optica 3.8 (2016), pp. 853–853.
  • Gregory J. Stein, Phillip D Keathley, Peter Krogen, Houkun Liang, Jonathas P Siqueira, Chun-Lin Chang, Chien-Jen Lai, Kyung-Han Hong, Guillaume M Laurent, and Franz X Kärtner. “Water-window soft x-ray high-harmonic generation up to the nitrogen K-edge driven by a kHz, 2.1 μm OPCPA source”. In: Journal of Physics B: Atomic, Molecular and Optical Physics 49.15 (2016).
  • Cheng Jin, Gregory J. Stein, Kyung-Han Hong, and Chii D Lin. “Generation of bright, spatially coherent soft X-ray high harmonics in a hollow waveguide using two-color synthesized laser pulses”. In: Physical Review Letters 115.4 (2015).
  • Chun-Lin Chang, Peter Krogen, Kyung-Han Hong, Luis E Zapata, Jeffrey Moses, Anne-Laure Calendron, Houkun Liang, Chien-Jen Lai, Gregory J. Stein, Phillip D Keathley, Guillaume Laurent, and Franz X Kärtner. “High-energy, kHz, picosecond hybrid Yb-doped chirped-pulse amplifier”. In: Optics Express 23.8 (2015), pp. 10132–10144.
  • Houkun Liang, Peter Krogen, Ross Grynko, Ondrej Novak, Chun-Lin Chang, Gregory J. Stein, Darshana Weerawarne, Bonggu Shim, Franz X Kärtner, and Kyung-Han Hong. “Three-octave-spanning supercontinuum generation and sub-two-cycle self-compression of mid-infrared filaments in dielectrics”. In: Optics Letters 40.6 (2015), pp. 1069–1072.
  • Chun-Lin Chang, Peter Krogen, Houkun Liang, Gregory J Stein, Jeffrey Moses, Chien-Jen Lai, Jonathas P Siqueira, Luis E Zapata, Franz X Kärtner, and Kyung-Han Hong. “Multi-mJ, kHz, ps deep-ultraviolet source”. In: Optics Letters 40.4 (2015), pp. 665–668.
  • Chien-Jen Lai, Kyung-Han Hong, Jonathas P Siqueira, Peter Krogen, Chun-Lin Chang, Gregory J Stein, Houkun Liang, Phillip D Keathley, Guillaume Laurent, Jeffrey Moses, Luis E Zapata, and Franz X Kärtner. “Multi-mJ mid-infrared kHz OPCPA and Yb-doped pump lasers for tabletop coherent soft x-ray generation”. In: Journal of Optics 17.9 (2015).
  • Kyung-Han Hong, Chien-Jen Lai, Jonathas P Siqueira, Peter Krogen, Jeffrey Moses, Chun-Lin Chang, Gregory J. Stein, Luis E Zapata, and Franz X Kärtner. “Multi-mJ, kHz, 2.1 μm optical parametric chirped-pulse amplifier and high-flux soft x-ray high-harmonic generation”. In: Optics Letters 39.11 (2014), pp. 3145–3148.
  • Andrew J Lohn, Barney L Doyle, Gregory J Stein, Patrick R Mickel, Jim E Stevens, and Matthew J Marinella. “Rutherford forward scattering and elastic recoil detection (RFSERD) as a method for characterizing ultra-thin films”. In: Nuclear Inst. and Methods in Physics Research, B 332 (Aug. 2014), pp. 99–102.

Gregory J Stein
Assistant Professor
Computer Science

gjstein@gmu.edu
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curriculum vitae (CV)