Curriculum Vitae


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
Awarded for outstanding teaching assistantship in Applied & Engineering Physics.

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

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


Research Experience

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.


Service & Leadership

Reviewer | Reviewer for top conferences: ICLR, ICRA, RSS , Ongoing

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

  • Teaching Assistant Machine Learning (Graduate) | MIT, Fall 2015
  • Teaching Assistant Fluid Mechanics (Senior Undergrad) | Cornell University, Spring 2013

Publications

  • Gregory J. Stein, Christopher Bradley, Victoria Preston, and Nicholas Roy. "Enabling Topological Planning with Monocular Vision". In: International Conference on Robotics and Automation (ICRA). 2020. paper, talk (10 min).
  • Gregory J. Stein, Christopher Bradley, and Nicholas Roy. "Learning over Subgoals for Efficient Navigation of Structured, Unknown Environments". In: Conference on Robot Learning (CoRL). 2018. paper, talk (14 min).

    Best Paper Finalist at CoRL 2018; Best Oral Presentation at CoRL 2018.

  • Gregory J. Stein and Nicholas Roy. “GeneSIS-RT: Generating Synthetic Images for training Secondary Real-World Tasks”. In: International Conference on Robotics and Automation (ICRA). 2018. paper.
  • Mycal Tucker, Derya Aksaray, Rohan Paul, Gregory J. Stein, and Nicholas Roy. "Learning Unknown Groundings for Natural Language Interaction with Mobile Robots". In: International Symposium on Robotics Research (ISRR). 2017.

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.