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Jesse Zhang

@Jesse_Y_Zhang • 1,782 subscribers

Robotics Postdoc @uwcse w/ A. Gupta, D. Fox. Collab @allen_ai, @toyotaresearch. Prev: PhD from @csatusc. Intern @ NVIDIA, AWS.

Shorts

How can non-experts quickly teach robots a variety of tasks? Introducing HAND ✋, a simple, time-efficient method of training robots! Using just a **single hand demo**, HAND learns manipulation tasks in under **4 minutes**! 🧵

How can non-experts quickly teach robots a variety of tasks? Introducing HAND ✋, a simple, time-efficient method of training robots! Using just a single hand demo, HAND learns manipulation tasks in under 4 minutes! 🧵

32,109 次观看

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A reward model that works, zero-shot, across robots, tasks, and scenes? Introducing Robometer: Scaling general-purpose robotic reward models with 1M+ trajectories. Enables zero-shot: online/offline/model-based RL, data retrieval + IL, automatic failure detection, and more! 🧵 (1/12)

A reward model that works, zero-shot, across robots, tasks, and scenes? Introducing Robometer: Scaling general-purpose robotic reward models with 1M+ trajectories. Enables zero-shot: online/offline/model-based RL, data retrieval + IL, automatic failure detection, and more! 🧵 (1/12)

101,716 次观看 • 4 个月前

How can we help *any* image-input policy generalize better? 👉 Meet PEEK 🤖 — a framework that uses VLMs to decide *where* to look and *what* to do, so downstream policies — from ACT, 3D-DA, or even π₀ — generalize more effectively! 🧵

How can we help any image-input policy generalize better? 👉 Meet PEEK 🤖 — a framework that uses VLMs to decide where to look and what to do, so downstream policies — from ACT, 3D-DA, or even π₀ — generalize more effectively! 🧵

Jesse Zhang @ RSS 2026 ✈️

13,754 次观看 • 9 个月前

Having humans annotate data to pre-train robots is expensive and time-consuming! Introducing SPRINT: A pre-training approach using LLMs and offline RL to equip robots w/ many language-annotated skills while minimizing human annotation effort! URL: 🧵👇

Having humans annotate data to pre-train robots is expensive and time-consuming! Introducing SPRINT: A pre-training approach using LLMs and offline RL to equip robots w/ many language-annotated skills while minimizing human annotation effort! URL: 🧵👇

Jesse Zhang @ ICML 2026 ✈️

24,665 次观看 • 3 年前

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