黄翔，男，1995年7月生，汉族，浙江安吉人，副教授、硕士生导师，入选江苏省“双创博士”。2024年6月于上海交通大学获得工学博士学位，目前主要从事微纳尺度热输运计算与模拟、人工智能辅助的热功能材料/器件设计、能源大数据与智慧能源等研究工作。自2025年11月起，在清华大学马维刚教授课题组开展聚合物及其复合界面热测量相关的合作研究。

作为核心成员先后参与国家自然科学基金、上海市科委基础研究领域项目和上海市浦江人才计划项目等多项课题研究。在npj Computational Materials、Journal of Materials Chemistry A、Materials Today Physics和International Journal of Heat and Mass Transfer等期刊共发表SCI/EI论文30余篇，授权发明专利1项。

欢迎具有工程热物理、能源、动力、机械和材料等背景学生报考，招生专业：动力工程及工程热物理、动力工程、流体力学。

欢迎本科生联系加入课题组参加科研训练！

主要论文成果:

[1] Xiang Huang, Junfeng Zhu, Jing Zhao, Ji'an Wang, Bing Yao, Shenghong Ju, Weigang Ma. Quantum-inspired genetic algorithm for designing thermally conductive polymers. Applied Physics Letters, 2026, 128 (7), 072201.

[2] Xiang Huang, Xizhao Xie, Congcong Luo, Bing Yao, Yongqiang Chen, Weigang Ma. Accelerating design of synthesizable thermally conductive polymers using atomic interaction-embedded deep learning. International Journal of Heat and Mass Transfer, 2026, 262, 128585.

[3] Xiang Huang*, Shaobo Song, Yongqiang Chen, Zongze Lv, Xingyi Huang, Shenghong Ju. Machine learning-assisted efficient discovery and rational design of thermally conductive polymers. ACS Applied Materials & Interfaces, 2026, 18 (1), 2781-2794.

[4] Yigen Wu, Bing Yao, Xiang Huang*, Yongqiang Chen. Integrating machine learning and molecular dynamics for accelerated discovery of polymers with high thermal conductivity. Journal of Applied Physics, 2025, 138 (17), 175101.

[5] Hongwei Du, Xiang Huang, Jian Hui, Lanting Zhang, Yuanxun Zhou, Hong Wang. Assessment and application of universal machine learning interatomic potentials in solid-state electrolyte research. ACS Materials Letters, 2025, 7 (10), 3403-3412.

[6] Xiang Huang, Shenghong Ju. Tutorial: AI-assisted exploration and active design of polymers with high intrinsic thermal conductivity. Journal of Applied Physics, 2024, 135, 171101.

[7] Xiang Huang, Changying Zhao, Hong Wang, Shenghong Ju. AI-assisted inverse design of sequence-ordered high intrinsic thermal conductivity polymers. Materials Today Physics, 2024, 44, 101438.

[8] Xiang Huang, Shengluo Ma, Changying Zhao, Hong Wang, Shenghong Ju. Exploring high thermal conductivity polymers via interpretable machine learning with physical descriptors. npj Computational Materials, 2023, 9 (1), 191.

[9] Xiang Huang, Shengluo Ma, Yunwen Wu, Chaoying Wan, Changying Zhao, Hong Wang, Shenghong Ju. High-throughput screening of amorphous polymers with high intrinsic thermal conductivity via automated physical feature engineering. Journal of Materials Chemistry A, 2023, 11(38), 20539-20548.

[10] Xiang Huang, Shengluo Ma, Hong Wang, Shangchao Lin, Changying Zhao, Hong Wang, Shenghong Ju. Enhancing thermoelectric properties of isotope graphene nanoribbons via machine learning guided manipulation of disordered antidots and interfaces. International Journal of Heat and Mass Transfer, 2022, 197, 123332.

[11] 黄翔, 宋少博, 赵婧,张一帆.人工智能辅助的酯类润滑油分子设计[J]. 摩擦学学报（中英文）, 2025, 45(12): 1733−1743.