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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.

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

3 4 月, 20262 4 月, 2026
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?
Tasks such as folding clothes, organizing objects, or operating
…
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