Excited to share that I’ve been selected as a member for the Robotics Science and Systems (RSS) Pioneers 2026!
Many academic researchers whose work has influenced me over the years are an alumni of RSS Pioneers, so being part of this cohort means a lot.
See y’all in sydney!
We are excited to announce the 2026 cohort of RSS Pioneers! This year’s cohort brings together an outstanding group of early-career researchers whose work spans the breadth of robotics. A heartfelt thank you to all the organizers who made this year’s program possible.
"The space of actions is tiny" — that's what he said...
A 7-DoF command is low-dimensional, but the problem isn't. Contact makes the dynamics hybrid and non-smooth; you're optimizing across manifold switches every time something touches. That hardness is the geometry being waved away.
Conveniently, the field is debating exactly this on Friday! Come weigh in: "Geometry in the Age of Data-Driven Robotics," #ICRA2026, Hall C4, Fri Jun 5.
https://t.co/OiEWWcWFXT
Presenting DreamControl at ICRA 2026 today! 💫
@DvijKalaria, @pushkalkatara and Sangkyung Kwak will present our workflow for building whole-body humanoid AI skills — combining diffusion models and RL to train skills without expensive real-world data collection.
17:35 – 17:45 | Session WeBT3 | Lehar 1-4
More about DreamControl: https://t.co/Lvl27flPGy
#ICRA2026 #DreamControl #Humanoid #PhysicalAI
A parallel masking approach for differentiable logic that significantly accelerates robustness computation and enables scalable integration with robot learning.
Joint Work with Zuki, @eskang09 and Karen
also big thx to @genrobotics_ai
Website: https://t.co/Wohqb5X52O
#ICRA2026
Attending ICRA 2026 in Vienna? Please stop by and check out our poster on STLCG++ tomorrow!
The RA-L paper has been out for about a year and I am grateful to the robotics community for the support and appreciation for STLCG++.
TuI1I.22 — Tuesday, June 2, 09:00–10:30
I’m excited to share that I successfully defended my Ph.D. thesis on Specification-Driven Planning for Safe Autonomy!
I’m deeply grateful to my committee Sebastian Scherer, Changliu Liu, Karen Leung and Eunsuk Kang for their time and guidance throughout this journey. More in 🧵
This work has been shaped by many collaborations and conversations around how we can build robot learning systems that are not only capable, but also safe, reliable, and formally grounded. A huge shoutout to my labs @AirLabCMU and SoDA!
Stay tuned for where I’m headed next 👀
In the coming months, I will be presenting parts of my thesis research at ICML 2026 in Seoul (https://t.co/j3O5XkVPbA) and ICRA 2026 in Vienna (https://t.co/Wohqb5X52O). I will also be at RSS 2026 in Sydney for RSS pioneers! If you’re gonna be at these venues, please reach out!
Last year, I came across the idea of constrained decoding (I know, late to the party) and was fascinated. The ability to enforce constraints for LLMs at inference time without fine tuning is a powerful idea. It got me thinking, can we do this for robot foundation models?
1/n🧵