Asst. Prof. at Khoury College of CS at Northeastern

Joined February 2020
1 Photos and videos
Robin Walters retweeted
5 more days (AOE) to submit to the 2026 TAG-DS collaborative conference organized in partnership with @bostonsymmetry! Don’t miss out on this awesome opportunity to share your work with this vibrant research community! Info at: tagds.com/events/tag-ds-2026
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Robin Walters retweeted
Our community poster session starts in 30min and runs til 5:30pm, followed by a social nearby! The closest entrance to the Raytheon Amphitheater is here: maps.app.goo.gl/KvuYHVUYKi2L…
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Robin Walters retweeted
Replying to @bostonsymmetry
@bostonsymmetry is hosting a poster session (4-5:30pm) social on Tuesday, June 9th, at Northeastern! All are welcome to come chat about geometry, symmetries, AI! Location: Raytheon Amphitheater, maps.app.goo.gl/oDZc3Rw7iN4q… Register here: neu.co1.qualtrics.com/jfe/fo…
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Robin Walters retweeted
Just under two weeks until the submission deadline for the Boston TAG Party 2026– a joint conference organized collaboratively by the Boston Symmetry Group and TAG-DS! Papers are due June 12th— full archival papers, extended abstracts, and open problem tracks!
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Robin Walters retweeted
Last Thursday, @stefanos_pert Stefanos Pertigkiozoglou defended his PhD. Stefanos is one of the deepest and most thorough thinkers I worked with. He is the definition of quiet power. His key insight was that enforcing exact equivariance throughout optimization can unnecessarily restrict expressivity. By relaxing equivariance constraints during training, his methods reached solutions that preserve the benefits of symmetry while escaping the restricted equivariant landscapes (ICML'25 and Neurips'24, plus TMLR, ICLR, Neureps). I am so proud of you Stefanos! Thank you @_onionesque for the inspiration and Stefanos' mentoring in the relaxation work, as well as to @RobinSFWalters, @ParisPerdikaris, @EdgarDobriban, Pratik Chaudhari, and Jean Gallier, for making committee exams a resource for learning.
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Robin Walters retweeted
Can BC policies be quickly improved through real world experience? Our new #RSS2026 paper proposes Q2RL, a method that bridges BC and RL for on-robot learning. Q2RL improves BC policies by up to 3.75x with just 1-2 hours of online interaction! So when life gives you BC, make Q-functions! 🍋 Details in thread 🧵
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Robin Walters retweeted
And now we are very proud and humbled to have received the ICLR 2026 Honorable Mention award for this work blog.iclr.cc/2026/04/23/anno… Very fun to have found this useful math nugget that can actually speed-up LLM training.

Are you interested in the new Muon/Scion/Gluon method for training LLMs? To run Muon, you need to approximate the matrix sign (or polar factor) of the momentum matrix. We've developed an optimal method *The PolarExpress* just for this! If you're interested, climb aboard 1/x
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Robin Walters retweeted
TL;DR: poster today at 3:15pm, P3-#1109! Have you ever benchmarked your method on QM9, MD17, OC20, or ModelNet? It turns out that the 3D orientations of point clouds in commonly used datasets are highly non-random. How did we prove this and why should you care? 🧵
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Robin Walters retweeted
Introducing our recent work [ICLR2026] EquAct: An SE(3)-Equivariant Multi-Task Transformer for 3D Robotic Manipulation with Yu Qi, Yizhe Zhu, Robin Walters, and Robert Platt. [Paper](openreview.net/forum?id=d1wu…) [Video](youtu.be/ymrNQusB6Mw?si=D0mT…) [Code](github.com/ZXP-S-works/EquAc…
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Robin Walters retweeted
🚨New paper alert 🚨 from @rai_inst! arxiv.org/abs/2603.15757 🤖You robot policy is actually better than you think! We find that for a given policy, ALWAYS denoising a single noise vector, which we call a ✨Golden Ticket ✨, leads to consistent performance improvements! 🧵...
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Robin Walters retweeted
Our paper "On Universality of Deep Equivariant Networks" will appear at ICLR 2026. We show that appropiate depth or readout layers are enough to reach universality up to the separation constraint imposed by the architecture, e.g., WL for IGNs. arxiv.org/abs/2510.15814
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Robin Walters retweeted
📢The second edition of ✨GRaM workshop✨ is here this time at #ICLR26. 🌟Submit your exciting works in Geometry-grounded representations. We welcome submissions in multiple tracks i.e. 📄 Proceedings 📝extended abstract 👩‍🏫Tutorial/blogpost as well as an exciting challenge!
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Robin Walters retweeted
📢 GRaM workshop is back!! This time at #ICLR2026 🌟Excited to be in Brazil 🇧🇷! More information coming soon! @iclr_conf @GRaM_org_
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ISP can do equivariant learning from only RGB images. We leverage the spherical projection technique we previously used in Image2Sphere for prediction.
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Robin Walters retweeted
27 Nov 2025

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Robin Walters retweeted
Excited to share our #ICML2025 paper, Hierarchical Equivariant Policy via Frame Transfer. Our Frame Transfer interface imposes high-level decision as a coordinate frame change in the low-level, boosting sim performance by 20% and enabling complex manipulation with 30 demos.
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Robin Walters retweeted
19 Jun 2025
When and why are neural network solutions connected by low-loss paths? In our #ICML2025 paper, we show that mode connectivity often arises from symmetries—transformations of parameters that leave the network’s output unchanged. Paper: arxiv.org/abs/2505.23681 (1/6)
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Robin Walters retweeted
Registration is now open for Boston Symmetry Day on March 31! Sign up by March 21st at docs.google.com/forms/d/e/1F… We have an exciting lineup of speakers (see our website: bostonsymmetry.github.io/ )  Also featuring a poster session so you have a chance to present your awesome work!
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Robin Walters retweeted
Save the date -- Boston Symmetry Day 2025 will be held on March 31st, at Northeastern University! Speakers and sponsors to be announced in the coming weeks, but you can expect another great lineup of talks, networking, and posters. We'll see you there!
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Robin Walters retweeted
17 Jan 2025
What can we learn from neural network model weights? Join us for the Weight Space Learning Workshop at #ICLR2025! @iclr_conf 📄Accepting extended abstracts & full papers 🗓️Submission Deadline: Feb 4, 2025 🔗weight-space-learning.github…
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