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Style3D Tech Expert Team

Huamin Wang Chief Scientist at Style3D, with long-standing expertise in high-performance, high-fidelity physical simulation, and an internationally recognized scholar in GPU-based deformable simulation and the physical modeling of flexible materials (fabrics). Prior to joining Style3D, he was a tenured Associate Professor at The Ohio State University and a postdoctoral researcher at UC Berkeley. He has published over 80 papers in top-tier venues such as SIGGRAPH and CVPR, including 4 single-author SIGGRAPH papers. He was elected ACM Distinguished Member and IEEE Senior Member in 2025 and serves as Vice Chair of the SIGGRAPH Asia 2026 Technical Papers Committee. Fanfu Jiangchen Professor of Mathematics at UCLA and Director of the AI and Visual Computing Lab (AIVC). His research spans physical AI, 3D vision, generative modeling, and embodied intelligence. He is the creator and driving force behind widely adopted simulation methods such as APIC, MLS-MPM, and IPC. He has received multiple best paper awards and nominations at SIGGRAPH, ICRA, and IROS. Yin Yang Associate Professor at the Kahlert School of Computing, University of Utah, and co-leader of the Utah Graphics Lab, with affiliations to the Utah Robotics Center. His research bridges computer graphics, simulation, and robotics. He previously held positions at the University of New Mexico and Clemson University and earned his PhD from UT Dallas (David Daniel Fellowship). His honors include the NSF CRII Award and CAREER Award, with a focus on scalable computational methods for real-world applications.

SynReal Decode 03: Closing the ”Last Mile” of AI — The Answer to Style3D’s Multiphysics Simulation

22 4 月, 2026 Style3D Tech Expert Team
At NVIDIA GTC 2026, Jensen Huang made a clear statement: physical AI has arrived.

Yet the core bottleneck of Physical AI has never been the model itself. It lies in a more fundamental constraint: whether we can faithfully reconstruct the …
Categories Style3D Research

SynReal Decode 02: Why Does “Deformable Object Simulation” Determine The Upper Limit of Physical AI?

17 4 月, 202616 4 月, 2026 Style3D Tech Expert Team
In the previous article, we established that: simulation is a key source of data for AI.

But this raises an important question:
what kind of simulation is truly valuable?

The answer is simple: not all simulations are created …
Categories Style3D Research

SynReal Decode 01: Demystifying Synthetic Simulation Data: Why It Is Essential for Embodied AI Training

16 4 月, 20262 4 月, 2026 Style3D Tech Expert Team
Large-scale AI models can now write, generate images, and even perform reasoning tasks.
Yet a more fundamental question remains: Why can’t AI work in the real world the way humans do?



gif from bilibili

Tasks such as folding clothes, organizing
…
Categories Style3D Research

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