Haisen Zhao

Professor, School of Computer Science and Technology
Shandong University

My research focuses on geometric computing for design and manufacturing, including manufacturability analysis, process and toolpath planning, microstructure design, and additive–subtractive hybrid manufacturing.

Publications Google Scholar CV GitHub

Interdisciplinary Research Center · Qingdao, China
haisenzhao [at] sdu.edu.cn

中文简介

赵海森，山东大学计算机科学与技术学院教授、博士生导师，山东大学杰出中青年人才、国家级青年人才。主要研究计算机图形学、数字几何设计，以及人工智能驱动的几何设计与制造。2018年获山东大学工学博士学位，导师为陈宝权教授；2019—2022年先后在美国华盛顿大学和奥地利科学技术研究所从事博士后研究，合作导师为 Adriana Schulz 教授和 Bernd Bickel 教授。

在 ACM TOG、ACM SIGGRAPH / SIGGRAPH Asia、IEEE TVCG、IROS 等期刊和会议发表多篇论文，出版专著1部，申请国家发明专利十余项和美国发明专利1项。主持国家自然科学基金优秀青年科学基金项目（海外）、国家重点研发计划课题、国家自然科学基金面上项目等，担任 CCF CAD&CG 专委会等多个学术组织委员。曾获山东省自然科学奖一等奖、CCF 优秀博士学位论文奖等。

Research

My group studies computational methods across geometric design, analysis, and fabrication.

AI-Driven Geometric Design

Geometric learning, generative design, microstructures, and performance-driven optimization.

Manufacturability and Process Planning

Accessibility analysis, decomposition, packing, process sequencing, and geometric verification.

Computational Fabrication

Toolpath optimization, additive and subtractive manufacturing, hybrid manufacturing, and robotic fabrication.

Selected publications

Full publication list

DeepMill++ neural guidance and rasterization for accessibility analysis

SIGGRAPH 2026 · Conference Track

DeepMill++: Neural Guidance Meets Rasterization for Efficient Accessibility Analysis

Combines neural guidance with rasterization for efficient tool-accessibility analysis in subtractive manufacturing.

Project

SIGGRAPH Asia 2025 · Journal Track

Chapper: Carvable Hull-and-Pack for Subtractive Manufacturing

Jointly decomposes and packs shapes into carvable hulls for efficient subtractive manufacturing.

Project Code

SIGGRAPH 2025 · Conference Track

DeepMill: Neural Accessibility Learning for Subtractive Manufacturing

Learns tool accessibility to efficiently analyze manufacturability for subtractive processes.

Project Code

ACM TOG · SIGGRAPH Asia 2023

VASCO: Volume and Surface Co-Decomposition for Hybrid Manufacturing

Co-decomposes volume and surface to plan additive–subtractive hybrid manufacturing.

Project

MIND microstructure inverse design with a generative hybrid neural representation

SIGGRAPH 2025 · Conference Track

MIND: Microstructure INverse Design with Generative Hybrid Neural Representation

Uses a generative hybrid neural representation for performance-driven inverse design of microstructures.

Code

ACM TOG · SIGGRAPH 2016

Connected Fermat Spirals for Layered Fabrication

Generates connected, low-curvature spiral paths for continuous layered fabrication.

Project Paper

Academic background

Haisen Zhao is a Professor at Shandong University and a member of the Interdisciplinary Research Center. He received his Ph.D. from Shandong University and conducted postdoctoral research at the University of Washington and IST Austria.

Selected Funding

2025–2028 National Natural Science Foundation of China, PI
2024–2027 National Key R&D Program of China, PI
2023–2025 Science Fund Program for Excellent Young Scientists (Overseas), PI

Background

2022–present Professor, Shandong University
2021–2022 Postdoctoral Researcher, IST Austria
2019–2021 Postdoctoral Researcher, University of Washington

Selected Recognition

2020 First Prize, Shandong Natural Science Award
2019 CCF Doctoral Dissertation Award
2016 President Scholarship, Shandong University

A complete record of publications, teaching, funding, experience, and awards is available in the full CV.