Michael Everett - Northeastern University College of Engineering

Michael Everett - Northeastern University College of Engineering
Michael Everett
Assistant Professor,
Electrical and Computer Engineering
Assistant Professor,
Khoury College of Computer Sciences
Contact
m.everett@northeastern.edu
360 Huntington Ave
Boston, MA 02115
Social Media
Office
EXP 730C
Related Links
Personal Webpage
Lab Webpage
University Research Profile
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.
Spotlight Story
Mar 09, 2026
Driven by Curiosity: Rohith Poola’s Journey in Autonomous Robotics
Rohith Poola, MS’26, is a robotics student in the Autonomy and Intelligence Lab at Northeastern, where he works on projects in autonomous navigation and off-road traversability estimation. Guided by a deep curiosity and strong mentorship, he plans to pursue a PhD and eventually establish his own research in autonomy and planning.
Faculty
Oct 31, 2025
Making Exoskeletons Safe Through Uncertainty
Research conducted by Fatima Mumtaza Tourk, PhD’27, mechanical engineering; Bishoy Galoaa, PhD’29, computer engineering; Sanat Shajan, COS’25; ECE/Khoury Assistant Professor Michael Everett; and Bouvé/MIE Assistant Professor Max Shepherd on “Uncertainty-Aware Ankle Exoskeleton Control” was published in Robotics.
Faculty
Sep 23, 2025
2025 Stanford University Annual Assessment of Author Citations
The following COE professors are among the top scientists worldwide selected by Stanford University representing the top 2% of the most-cited scientists with single-year impact in various disciplines. The selection is based on the top 100,000 by c-score (with and without self-citations) or a percentile rank of 2% or above.
Spotlight Story
Jul 21, 2025
The Value of Collaboration and Time in the World of Research
Bishoy Galoaa, MS’25, electrical and computer engineering, has participated in multiple, impactful research projects throughout his time at Northeastern. These projects have taught him valuable skills and the importance of time and collaboration when conducting research. Galoaa has decided to continue his education and pursue a PhD in computer engineering to dive deeper into the world of research.
Faculty
Jun 04, 2025
Enhancing Sensory Capabilities of Autonomous Vehicles in Boston
Michael Everett, ECE and computer science assistant professor, is enthusiastic about the prospect of introducing Waymo’s self-driving vehicles to Boston. Everett says this opportunity could help address a key technical challenge: enhancing the sensors of autonomous vehicles in adverse weather conditions, like rain, snow, or fog.
Faculty
Jan 31, 2025
2024 Stanford University Annual Assessment of Author Citations
The following COE professors are among the top scientists worldwide selected by Stanford University representing the top 2% of the most-cited scientists with single-year impact in various disciplines. The selection is based on the top 100,000 by c-score (with and without self-citations) or a percentile rank of 2% or above. The list below includes those who published a paper in 2024 or later.
In the Media
Jul 10, 2024
Tesla Isn’t as Far Ahead as You Think in Robotaxis
ECE/Khoury Assistant Professor Michael Everett was featured in TheStreet article “Tesla Isn’t as Far Ahead as You Think in Robotaxis.”
Faculty
May 20, 2024
Preparing Autonomous Vehicles for the Mainstream Market
ECE/Khoury Assistant Professor Michael Everett explains why current autonomous vehicle technology isn’t ready for the mainstream market. The autonomy kits used on these vehicles aren’t precise enough to meet safety standards, he says.
Faculty
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.
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