About
Ziyan Wang is a researcher affiliated with Carnegie Mellon University's School of Computer Science, Department of Computer Science. Their work focuses on computer graphics, machine learning, and medical imaging, with a strong emphasis on dynamic capture and animation of human hair and heads. They hold a PhD in Computer Science from Carnegie Mellon University (2023).
Research interests include 3D modeling, neural networks, reinforcement learning, and applications in medical informatics. Notable contributions include high-fidelity hair modeling using computed tomography and neural dynamic models for volumetric hair capture. Their work spans conferences like CVPR, NeurIPS, and ECCV, demonstrating expertise in both theoretical and applied aspects of computer vision and graphics.
Publications highlight advancements in diffusion models, multi-agent reinforcement learning, and domain adaptation for fault diagnosis. Collaborations span institutions like the University of Washington, Max Planck Institute, and NVIDIA Research, reflecting interdisciplinary engagement. Recent work explores AI-generated content in virtual environments and cybersecurity in package management systems.
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