教育经历

2023-至今，博士（在读）土木工程，清华大学
2021-2023，辅修工学学士学位，软件工程，清华大学，GPA: 3.85/4.00， 30学分
2019-2023，主修工学学士学位，土木、水利与海洋工程（土木工程方向），清华大学，GPA: 3.98/4.00， 191学分

工作经历

2023，本科生课程《土木工程与防灾减灾》，助教
2023，研究生课程《灾害学》，助教
2020-2022，清华大学土木工程系暨建设管理系学生科协，部员、部长、主席
2019-2021，清华大学学生创客空间社团，会员、常务副会长

荣誉

学业荣誉

2023.08，清华大学博士生“未来学者”奖学金
2023.07，北京市优秀毕业生
2023.06，清华大学优秀毕业生
2023.03，茅以升科学技术奖——工程教育学生奖（全国共9人）
2022.12，清华大学本科生特等奖学金提名（全校共15人）
2022.12，国家奖学金
2022.12，清华大学综合优秀奖学金
2022.12，清华大学科技创新优秀奖学金（清华之友-龙湖奖学金）
2021.12，清华大学综合优秀奖学金（清华之友-汐泰奖学金）
2020.12，清华大学综合优秀奖学金（清华之友-恒大奖学金）
2020.12，清华大学实践优秀奖学金（清华之友-金门一等奖学金）

科学研究

2024.06，“星河奖”（土木工程诊治与运维领域）优秀论文银奖（唯二学生获奖）
2023.12，北京市普通高校优秀本科毕业设计（论文）
2023.06，清华大学本科生综合论文训练优秀论文
2023.05，第48届日内瓦国际发明展评审团特别嘉许金奖（团队内唯一本科生）

科创竞赛

2024.07，“北京西城 · 高校发展联盟”青年数字创新创意大赛一等奖（2/100+)
2022.12，“盈建科杯”全国大学生智能建造数字化设计大赛一等奖（队长，1/600+)
2022.07，“中铁十四局杯”第四届“茅以升公益桥-小桥工程”创新设计大赛特等奖（队长，1/99)

技能

计算机技能
- 编程语言：python、C、C++、C#、java、js、matlab、sql
- 前端：Vue.js
- 后端：Django、flask
- 操作系统：Windows、Linux
- AI：基本熟悉深度学习和机器学习常用模型（CNN、RNN、GNN、LSTM、Transformer……）
有限元分析
- Marc、Midas、SAP2000
建模绘图
- AutoCAD、Revit、Sketchup

论文发表

Leveraging data-driven artificial intelligence in optimization design for building structures: A review

QIN SZ, FEI YF, LIAO WJ, et al. Leveraging data-driven artificial intelligence in optimization design for building structures: A review[J/OL]. Engineering Structures, 2025, 341: 120810. DOI:10.1016/j.engstruct.2025.120810.

Comparative analysis of intelligent retrofit design methods of RC frame structures using buckling-restrained braces

QIN S Z, LIAO W J, TAN Z, et al. Comparative analysis of intelligent retrofit design methods of RC frame structures using buckling-restrained braces[J/OL]. Bulletin of Earthquake Engineering, 2025[2025-04-15]. DOI:10.1007/s10518-025-02164-3.

Graph neural network-assisted evolutionary algorithm for rapid optimization design of shear-wall structures

FEI Y F, QIN S Z, LIAO W J, et.al. Graph neural network-assisted evolutionary algorithm for rapid optimization design of shear-wall structures[J/OL]. Advanced Engineering Informatics, 2025, 65: 103129. DOI:10.1016/j.aei.2025.103129.

Intelligent design for component size generation in reinforced concrete frame structures using heterogeneous graph neural networks

QIN S Z, LIAO W J, HUANG Y L, et.al. Intelligent design for component size generation in reinforced concrete frame structures using heterogeneous graph neural networks[J/OL]. Automation in Construction, 2025, 171: 105967. DOI:10.1016/j.autcon.2025.105967.

Intelligent generation and optimization method for the retrofit design of RC frame structures using buckling-restrained braces

TAN Z, QIN S Z, HU K G, et al. Intelligent generation and optimization method for the retrofit design of RC frame structures using buckling-restrained braces[J/OL]. Earthquake Engineering & Structural Dynamics, 2025, 54(2): 530-547. DOI:10.1002/eqe.4268.

ChatHouseDiffusion: Prompt-guided generation and editing of floor plans

QIN S Z, HE C Y, CHEN Q Y, et al. ChatHouseDiffusion: Prompt-guided generation and editing of floor plans[A/OL]. arXiv, 2024[2024-10-17]. http://arxiv.org/abs/2410.11908. DOI:10.48550/arXiv.2410.11908.

Intelligent design and optimization system for shear wall structures based on large language models and generative artificial intelligence

QIN S Z, GUAN H, LIAO W J, et.al. Intelligent design and optimization system for shear wall structures based on large language models and generative artificial intelligence[J/OL]. Journal of Building Engineering, 2024, 95: 109996. DOI:10.1016/j.jobe.2024.109996.

AIstructure-Copilot: Assistant for generative AI-driven intelligent design of building structures

QIN S Z, LIAO W J, HUANG S N, et.al. AIstructure-Copilot: Assistant for generative AI-driven intelligent design of building structures[J/OL]. Smart Construction, 2024, 1(1): 0001. DOI:10.55092/sc20240001.

基于BIM和深度学习点云分割的施工检查方法模拟研究

张帆, 孙楚津, 覃思中, 赵馨怡. 基于BIM和深度学习点云分割的施工检查方法模拟研究[J]. 工程力学, 2024, 41(2): 194-201. DOI: 10.6052/j.issn.1000-4750.2022.04.0281

An efficient assessment method for intelligent design results of shear wall structure based on mechanical performance, material consumption, and empirical rules

QIN S Z, LIAO W J, LIN Y Q, LU X Z. An efficient assessment method for intelligent design results of shear wall structure based on mechanical performance, material consumption, and empirical rules[J/OL]. Engineering Mechanics, 2023, 40(12): 148-159. DOI:10.6052/j.issn.1000-4750.2023.05.0360.

覃思中