ASL LabStanford University
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Amine Elhafsi

amine _at_ stanford _dot_ edu

Amine Elhafsi

Alumni · now at Waymo

Amine is a Ph.D. student in the Department of Aeronautics and Astronautics. He recently obtained his M.S. degree from Stanford in 2019. Prior to joining Stanford, Amine graduated summa cum laude with a B.S. in aerospace engineering from UCLA. Before turning to robotics, he has also held multiple internships with the electric propulsion group at JPL.

Amine's research interests include motion planning, optimal control, machine learning, and robotics. His current work is focused on developing algorithms for safe robotic navigation of unknown or partially occluded environments.

Outside of the lab, Amine enjoys playing piano, soccer, and struggling to lift weights at the gym.

Awards:

  • UCLA Outstanding Bachelor of Science in Aerospace Engineering, 2016
  • NASA Space Technology Research Fellowship, 2019

Publications

8 publications · full lab bibliography

2025
  1. A. Elhafsi, D. Morton, and M. Pavone, “Scan, Materialize, Simulate: A Generalizable Framework for Physically Grounded Robot Planning,” ArXiv 2505.14938, 2025. (Submitted)
  2. Y. Kuang, H. Geng, A. Elhafsi, T. Do, P. Abbeel, J. Malik, M. Pavone, and Y. Wang, “SkillBlender: Towards Versatile Humanoid Whole-Body Loco-Manipulation via Skill Blending,” CoRL 2024 Workshop on Whole-body Control and Bimanual Manipulation, 2025.
  3. M. P. Ronecker, M. Foutter, A. Elhafsi, D. Gammelli, I. Barakaiev, M. Pavone, and D. Watzenig, “Vision Foundation Model Embedding-based Semantic Anomaly Detection,” Proc. IEEE Conf. on Robotics and Automation: Workshop Safe-VLM, 2025.
2024
  1. R. Sinha, A. Elhafsi, C. Agia, M. Foutter, E. Schmerling, and M. Pavone, “Real-Time Anomaly Detection and Planning with Large Language Models,” Robotics: Science and Systems, 2024.
2023
  1. A. Elhafsi, R. Sinha, C. Agia, E. Schmerling, I. A. D. Nesnas, and M. Pavone, “Semantic Anomaly Detection with Large Language Models,” Autonomous Robots, vol. 47, no. 8, pp. 1035--1055, 2023.
2020
  1. B. Ivanovic, A. Elhafsi, G. Rosman, A. Gaidon, and M. Pavone, “MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control,” Conf. on Robot Learning, 2020.
  2. A. Elhafsi, B. Ivanovic, L. Janson, and M. Pavone, “Map-Predictive Motion Planning in Unknown Environments,” Proc. IEEE Conf. on Robotics and Automation, 2020.
2019
  1. S. Chinchali, A. Sharma, J. Harrison, A. Elhafsi, D. Kang, E. Pergament, E. Cidon, S. Katti, and M. Pavone, “Network Offloading Policies for Cloud Robotics: a Learning-based Approach,” Robotics: Science and Systems, 2019.