Osher Azulay

I’m a Fulbright postdoctoral researcher at the University of Michigan, Ann Arbor, working with Prof. Stella Yu. My research focuses broadly on embodied intelligence, at the intersection of robotics, computer vision, and machine learning, with the goal of enabling reliable behavior under real-world variability.

Previously, I earned my Ph.D. from Tel Aviv University in 2024, under the supervision of Dr. Avishai Sintov. My work focused on robot learning for manipulation, with an emphasis on leveraging multimodal signals for more adaptive interaction.

Email  /  CV Last updated: July 2025  /  LinkedIn  /  GitHub

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News

  • July 2025 — Started my postdoc at the University of Michigan.
  • Winter 2025 — Visiting Scholar at UC Berkeley’s AUTOLab.
  • April 2025 — Gave a talk at Columbia University’s ROAM Lab.
  • Dec 2024 — Invited talk at Bar-Ilan University, Computer Science Department.
  • Dec 2024 — Invited talk at the Technion, Mechanical Engineering Robotics Colloquium.
  • Nov 2024 — Received the Fulbright Postdoctoral Fellowship.
  • Oct 2024 — Defended my Ph.D. at Tel Aviv University.
  • Summer 2023 — Visiting Graduate Researcher at Rutgers University, Robot Learning Lab.
  • Summer 2022 — Robotics Intern Engineer at Unlimited Robotics.
  • 2023 — Received Honorable Mention for Excellence in Teaching at Tel Aviv University.
  • 2023 — Awarded the KLA Ph.D. Excellence Scholarship.
  • 2022 — Awarded the Prof. Nehemia Levtzion Scholarship for Outstanding Doctoral Students.

Selected Publications

Full publication list on Google Scholar.

Test-Time Motion Steering for Perceptive Humanoid Fall Recovery
Osher Azulay*, Cheng-Lin Hsieh*, and Stella Yu.
In submission. * Equal contribution.
project page

Steers visually guided humanoid recovery toward a desired heading, rise timing, or path at test time.
EgoIntercept: Egocentric Object Interception with a Quadruped Robot
Drew Scheffer, Osher Azulay, and Stella X. Yu.
In submission.
project page

Learns egocentric object-motion prediction and locomotion to catch flying objects using only onboard RGB-D sensing.
VIGOR Unified Perceptive Fall Safety for Humanoids
Osher Azulay, Zhengjie Xu, Andrew Scheffer, and Stella X. Yu.
Tech Report.
project page / paper

VIGOR unifies perceptive fall mitigation and stand-up recovery using sparse flat-ground demonstrations.
ViDEN Embodiment-Agnostic Navigation Policy Trained with Visual Demonstrations
Nimrod Curtis*, Osher Azulay*, and Avishai Sintov.
Tech Report. * Equal contribution.
project page / paper / code / video

Learns adaptive, collision-free motion from just a few visual demonstrations using diffusion.

Visuotactile insertion Visuotactile-Based Learning for Insertion with Compliant Hands
Osher Azulay, Dhruv Metha Ramesh, Nimrod Curtis and Avishai Sintov.
IEEE RA-L & IROS, 2025.
project page / paper / code

Visuotactile policy learning for contact-rich insertion with zero-shot sim-to-real transfer.
AllSight AllSight: A Low-Cost and High-Resolution Round Tactile Sensor with Zero-Shot Learning Capability
Osher Azulay, Nimrod Curtis, Rotem Sokolovsky, Guy Levitski, Daniel Slomovik, Guy Lilling and Avishai Sintov.
IEEE RA-L & ICRA, 2024.
paper / code / video

Introducing AllSight, an optical tactile sensor with a round 3D structure designed for robotic inhand manipulation tasks
Tactile simulators Augmenting Tactile Simulators with Real-like and Zero-Shot Capabilities
Osher Azulay*, Alon Mizrahi*, Nimrod Curtis* and Avishai Sintov.
ICRA 2024. * Equal contribution.
paper / code

Bridges the sim-to-real gap for 3D shaped high-resolution tactile sensing using generative modeling.
SE(3) insertion Haptic-Based and SE(3)-Aware Object Insertion Using Compliant Hands
Osher Azulay, Max Monastirsky and Avishai Sintov.
IEEE RA-L & ICRA, 2023.
paper / video

Exploring complaint hands characteristics for object insertion using haptic-based residual RL.
Throwing Learning to Throw With a Handful of Samples Using Decision Transformers
Max Monastirsky, Osher Azulay and Avishai Sintov.
IEEE RA-L & IROS, 2023.
paper / video

Exploring the use of Decision Transformers for throwing and their ability for sim2real policy transfer.
Haptic pose estimation Learning Haptic-based Object Pose Estimation for In-hand Manipulation Control with Underactuated Robotic Hands
Osher Azulay, Inbar Meir and Avishai Sintov.
IEEE Transactions on Haptics, 2022.
paper / code / video

In-hand object pose estimation and manipulation using Model Predictive Control.
Open-sourcing generative models Open-Sourcing Generative Models for Data-driven Robot Simulations
Eran Bamani, Osher Azulay, Anton Gurevich, and Avishai Sintov.
Data-Centric AI workshop, NeurIPS, 2021
project page / paper

Exploring the possibility of investing the recorded data in a generative model rather than directly to a regression model for real-robot applications.
Komodo Wheel Loader Scooping Controller Using Deep Reinforcement Learning
Osher Azulay and Amir Shapiro.
IEEE Access, 2021
paper / code / video

A deep reinforcement learning-based controller for an unmanned ground vehicle with a custom-built scooping mechanism.

Teaching Experience

  • Advanced Topics in Computer Vision (EECS 542) - LEO Lecturer, University of Michigan, Winter 2026.
  • Robotics and Control Lab - Course Designer and Teaching Assistant, Tel Aviv University, Spring 2021-2024.
  • Introduction to Control Theory - Teaching Assistant, Tel Aviv University, Fall 2020-2024.
  • Introduction to Electrical Engineering - Teaching Assistant, Ben-Gurion University, Spring 2019.
  • C Programming - Teaching Assistant, Ben-Gurion University, Fall 2019.
  • Introduction to Mechanical Engineering - Lab Instructor, Ben-Gurion University, Fall 2018.

Template from source code.