GAMES Webinar 2021 – 176期(几何处理专题) | 黄相如 (The University of Texas at Austin)

【GAMES Webinar 2021-176期】(几何处理专题)

报告嘉宾:黄相如 (The University of Texas at Austin)


报告题目:Learning to Optimize for Geometry Processing


Geometry processing, which focuses on reconstructing and analyzing physical objects and scenes, enjoy a wide range of applications, including medical diagnosis, architecture, bio-imaging, virtual reality, etc. Thanks to the popularity of portable 3D scanning devices and the emergence of big 3D data and exciting progress in artificial intelligence, there is a shift in this field from reconstructing and processing a single model to developing techniques that enable 3D models as a data modality for machine perception. Compared to other data modalities such as images, videos, audios, and natural language descriptions, 3D models provide the most accurate recording of our physical world. As a result, 3D models are critical for applications involving geometric quantities such as distances and orientations, and physical properties such as stability and affordance, etc. However, to enable the 3D model as a data modality for machine perception, we have to develop efficient and robust geometry processing techniques ranging from 3D reconstruction to 3D understanding.

Our work focuses on geometry processing from the perspective of robust optimization, a field that is gaining increasing attention in the era of big data, machine learning, and artificial intelligence, but is under-explored in the field of geometry processing. Important aims include developing robust and efficient optimization procedures with provable guarantees, and learning to optimize to adapt to input and output distributions.


I’m Xiangru Huang (黄相如). I’m received my PhD in Computer Science Department of University of Texas at Austin under professor Qixing Huang . My research focuses on Machine Learning, 3D vision, Optimization and their applications. I received my Bachelor’s Degree from Shanghai JiaoTong University, ACM Honored Class. I’m going to work as a post-doc with Justin Solomon at MIT beginning from April.



朱晨阳,现在国防科技大学计算机学院担任教职。本科毕业于国防科技大学计算机学院,2019年于加拿大西蒙弗雷泽大学应用科学学院获得工学博士学位。研究方向为计算机图形学、三维视觉。博士期间参与加拿大国家自然科学基金项目(NSERC),发表领域内顶级会议期刊文章9篇(CCF A类8篇),其中SIGGRAPH/TOG文章4篇,CVPR Oral 1篇。作为负责人建设了军队十三五“首次任职课程”一门,作为主要完成人参与建设了一门湖南省级金课。承担了国家自然科学基金青年项目一项、军队院校科研项目一项,同时参与多项自然科学基金项目、科技部重点研发项目。入选中国图学学会2020年度“青年托举计划”、中国人民解放军国防科技大学卓越青年科技人才计划。担任中国工业与应用数学学会几何设计与计算专委会副秘书长。


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