Michael Everett
Assistant Professor, Electrical and Computer Engineering
Assistant Professor, Khoury College of Computer Sciences
Contact
- m.everett@northeastern.edu
- Mailing Address:
360 Huntington Ave
129 ISEC
Boston, MA 02115
Social Media
Office
- 517 ISEC
Related Links
Research Focus
Robotics, motion planning, control theory, neural network verification, reinforcement learning
Education
- PhD, Mechanical Engineering, Massachusetts Institute of Technology, 2020
- SM, Mechanical Engineering, Massachusetts Institute of Technology, 2017
- SB, Mechanical Engineering, Massachusetts Institute of Technology, 2015
Honors & Awards
- Runner-Up: Best Paper Award (1st Workshop on Formal Verification of Machine Learning, ICML 2022)
- Editors’ Top 5 Published Articles of 2021 (IEEE Access)
- Winner: Best Paper Award on Cognitive Robotics (IROS 2019)
- Winner: Best Student Paper (IROS 2017)
- Finalist: Best Paper Award on Cognitive Robotics (IROS 2017)
- Finalist: Best Multi-Robot Systems Paper (ICRA 2017)
Research Overview
Robotics, motion planning, control theory, neural network verification, reinforcement learning
Selected Publications
Below are some sample publications in key areas of research in the Northeastern Autonomy & Intelligence Laboratory
Certifiable Machine Learning
- Everett, Michael. “Neural Network Verification in Control.” In 2021 60th IEEE Conference on Decision and Control (CDC), pp. 6326-6340. IEEE, 2021.
- Everett, Michael, Björn Lütjens, and Jonathan P. How. “Certifiable robustness to adversarial state uncertainty in deep reinforcement learning.” IEEE Transactions on Neural Networks and Learning Systems (2021).
- Everett, Michael, Golnaz Habibi, Chuangchuang Sun, and Jonathan P. How. “Reachability analysis of neural feedback loops.” IEEE Access 9 (2021): 163938-163953.
- Rober, Nicholas, Sydney M. Katz, Chelsea Sidrane, Esen Yel, Michael Everett, Mykel J. Kochenderfer, and Jonathan P. How. “Backward Reachability Analysis of Neural Feedback Loops: Techniques for Linear and Nonlinear Systems.” arXiv preprint arXiv:2209.14076 (2022).
High-Speed, Off-Road Autonomy
- Everett, Michael, Justin Miller, and Jonathan P. How. “Planning beyond the sensing horizon using a learned context.” In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1064-1071. IEEE, 2019.
- Tordesillas, Jesus, Brett T. Lopez, Michael Everett, and Jonathan P. How. “FASTER: Fast and safe trajectory planner for navigation in unknown environments.” IEEE Transactions on Robotics 38, no. 2 (2021): 922-938.
- Cai, Xiaoyi, Michael Everett, Jonathan Fink, and Jonathan P. How. “Risk-Aware Off-Road Navigation via a Learned Speed Distribution Map.” arXiv preprint arXiv:2203.13429 (2022).
- Sharma, Lakshay, Michael Everett, Donggun Lee, Xiaoyi Cai, Philip Osteen, and Jonathan P. How. “RAMP: A Risk-Aware Mapping and Planning Pipeline for Fast Off-Road Ground Robot Navigation.” arXiv preprint arXiv:2210.06605 (2022).
- Cai, Xiaoyi, Michael Everett, Lakshay Sharma, Philip R. Osteen, and Jonathan P. How. “Probabilistic Traversability Model for Risk-Aware Motion Planning in Off-Road Environments.” arXiv preprint arXiv:2210.00153 (2022).
Autonomy in Human Environments
- Everett, Michael, Yu Fan Chen, and Jonathan P. How. “Collision avoidance in pedestrian-rich environments with deep reinforcement learning.” IEEE Access 9 (2021): 10357-10377.
- Chen, Yu Fan, Michael Everett, Miao Liu, and Jonathan P. How. “Socially aware motion planning with deep reinforcement learning.” In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1343-1350. IEEE, 2017.
- Brito, Bruno, Michael Everett, Jonathan P. How, and Javier Alonso-Mora. “Where to go next: learning a subgoal recommendation policy for navigation in dynamic environments.” IEEE Robotics and Automation Letters 6, no. 3 (2021): 4616-4623.
Dec 20, 2022
New Faculty Spotlight: Michael Everett
Michael Everett joins the Electrical and Computer Engineering department in January 2023 as an Assistant Professor with a joint appointment in Khoury College of Computer Sciences.