Tomorrow I'll speak at the FPTalks series on floating point and numerical analysis, about robust geometry for neural implicit surfaces (work w/ @_AlecJacobson). The other talks sound amazing, and I love this area! Check out this great organization. fptalks.org/talks/fptalk...

Have you dug deep into an evolving area of visual computing? Consider submitting to the 2027 EG STARs track! STARs are survey reports providing insight into the current state of the art and future directions. They're impactful and highly-cited! eg2027.isti.cnr.it/call-for-sta...

Next week at #SIGGRAPH 2026, we'll present "Locality-Aware Automatic Differentiation on the GPU for Mesh-Based Computations," with Rahul Goel, Jonathan Ragan-Kelley, and @justinmsolomon.bsky.social . Talk: Mon., July 20, 2:50 PM, Room 403-B Paper: dl.acm.org/doi/10.1145/... More below (1/7):

📣 LOGML'26 Speaker Series 🎤 Nicholas Sharp @nmwsharp.bsky.social (NVIDIA) Researcher in geometry processing, computer graphics/vision & 3D ML — building methods for geometric computing. 📍 Imperial College London 📅 13–17 July 2026 Website: 🔗 www.logml.ai/ #LOGML #Summerschool #MachineLearning

Check out our Lyra2.0 for generating virtual worlds! The key is combining representations---the generative prior is a video model, but we leverage explicit 3D to scale to large scenes and support physical interaction. Huge kudos to Tianchang+Xuanchi who led it. research.nvidia.com/labs/sil/pro...

Our Rising Stars 2026 application campaign is currently open so we thought we would share some updates about our past rising stars 🌟 follow us in the next couple weeks to read more! Learn more about the program and apply >> www.wigraph.org/events/2026-...

Call for Rising Stars Applications

The Rising Stars in Computer Graphics program is designed to bring new perspectives to computer graphics research. This is a two-year program that will be co-located with SIGGRAPH 2026 and SIGGRAPH 20...

wigraph.org

Computing a convex decomposition of a shape is a classically-hard geometry problem, yet essential for fast physics simulators. Yuezhi found a way to accelerate it by training a large model!

Yuezhi Yang@yyuezhi.bsky.social · 5mo ago

Excited to share our new work at CVPR 2026: Learning Convex Decomposition via Feature Fields. We introduce the first feedforward openworld model that generates high-quality convex decompositions for any 3D shapes in seconds, enabling faster simulation. Project: research.nvidia.com/labs/sil/pro...

My PhD student Abhishek Madan is getting ready to graduate and he’s looking for a postdoc or industry position. Checkout his website www.dgp.toronto.edu/~amadan/ He’s been an amazing student , basically does all his research by himself. Fantastic math and implementation acumen.

📢want to create realistic dynamic 3D worlds (>100 splats)? my NVIDIA internship project, VoMP, is the first feed-forward approach turning surface geometry into volumetric sim-ready assets with real-world materials. 🌐Project: research.nvidia.com/labs/sil/pro... 📜Paper: arxiv.org/abs/2510.22975

The Spatial Intelligence Lab at NVIDIA (research.nvidia.com/labs/sil/) is looking for 2026 research interns! We do all kinds of cool work across graphics/vision, geometry, physics, & ML. Now is the time to apply & reach out! nvidia.eightfold.ai/careers/job/... (not limited to Canada-only)

Code is now out! Try it for yourself here: github.com/abhimadan/st...

GitHub - abhimadan/stochastic-barnes-hut: A reference implementation of the SIGGRAPH 2025 paper, "Stochastic Barnes-Hut Approximation for Fast Summation on the GPU".

A reference implementation of the SIGGRAPH 2025 paper, "Stochastic Barnes-Hut Approximation for Fast Summation on the GPU". - abhimadan/stochastic-barnes-hut

github.com

Abhishek Madan@abhishekmadan.bsky.social · last yr.

At SIGGRAPH 2025, we’ll be presenting the paper “Stochastic Barnes-Hut Approximation for Fast Summation on the GPU”. By injecting a bit of randomization into the classic yet deterministic Barnes-Hut approximation for fast kernel summation, we can achieve nearly 10x speedups on the GPU!

Also: this paper was recognized with a best paper award at SGP! Huge thanks to the organizers & congrats to the other awardees. I was super lucky to work with Yousuf on this one, he's truly the mastermind behind it all!

Nicholas Sharp@nmwsharp.bsky.social · last yr.

Logarithmic maps are incredibly useful for algorithms on surfaces--they're local 2D coordinates centered at a given source. Yousuf Soliman and I found a better way to compute log maps w/ fast short-time heat flow in "The Affine Heat Method" presented @ SGP2025 today! 🧵

Logarithmic maps are incredibly useful for algorithms on surfaces--they're local 2D coordinates centered at a given source. Yousuf Soliman and I found a better way to compute log maps w/ fast short-time heat flow in "The Affine Heat Method" presented @ SGP2025 today! 🧵

Holding SIGGRAPH Asia 2026 in Malaysia is a slap in the face to the rights of LGBTQ+ people. Especially now, when underrepresented people need as much support as we can possibly give them ! Angry like me ? Sign this open letter to let them know. 🏳️‍⚧️🏳️‍🌈 docs.google.com/document/d/1...

Open Letter to the SIGGRAPH Leadership

RE: Call for SIGGRAPH Asia to relocate from Malaysia and commit to a venue selection process that safeguards LGBTQ+ and other at-risk communities. To the SIGGRAPH Leadership: SIGGRAPH Executive Commit...

docs.google.com

Sampling points on an implicit surface is surprisingly tricky, but we know how to cast rays against implicit surfaces! There's a classic relationship between line-intersections and surface-sampling, which turns out to be quite useful for geometry processing.

Selena Ling@selenaling.bsky.social · last yr.

Our #SGP25 work studies a simple and effective way to uniformly sample implicit surfaces by casting rays. (1/9) “Uniform Sampling of Surfaces by Casting Rays” w/ @abhishekmadan.bsky.social @nmwsharp.bsky.social and Alec Jacobson

My child’s doll and tools I captured as 3D Gaussians, turned digital with collisions and dynamics. We are getting closer to bridging the gap between the world we can touch and digital 3D. Experience the bleeding edge at #NVIDIA Kaolin hands-on lab, #CVPR2025! Wed, 8-noon. tinyurl.com/nv-kaolin-cv...

Check out Abhishek's research! I was honestly surprised by this result: classic Barnes-Hut already builds a good spatial hierarchy for approximating kernel summations, but you can do even better by adding some stochastic sampling, for significant speedups on the GPU @ matching average error.

Abhishek Madan@abhishekmadan.bsky.social · last yr.

At SIGGRAPH 2025, we’ll be presenting the paper “Stochastic Barnes-Hut Approximation for Fast Summation on the GPU”. By injecting a bit of randomization into the classic yet deterministic Barnes-Hut approximation for fast kernel summation, we can achieve nearly 10x speedups on the GPU!

Selena's #Siggraph25 work found a simple, nearly one-line change that greatly eases neural field optimization for a wide variety of existing representations. “Stochastic Preconditioning for Neural Field Optimization” by Selena Ling, Merlin Nimier-David, Alec Jacobson, & me.

Fun new paper at #SIGGRAPH2025: What if instead of two 6-sided dice, you could roll a single "funky-shaped" die that gives the same statistics (e.g, 7 is twice as likely as 4 or 10). Or make fair dice in any shape—e.g., dragons rather than cubes? That's exactly what we do! 1/n

The Symposium on Geometry Processing is an amazing venue for geometry research: meshes, point clouds, neural fields, 3D ML, etc. Reviews are quick and high-quality. The deadline is in ~10 days. Consider submitting your work, I'm planning to submit! sgp2025.my.canva.site/submit-page-...

Hi BlueSky! I'm trying to get back to a "write" relationship with social media after hiding from it for a while. I like geometry research, useful code, pierogies [sic], triangles, outdoorsy life, etc. I mainly post about research/software, but glad to chat about anything.