北京科技大学副教授，硕导，入选2023年博士后创新人才支持计划。主要从事多范式联合材料开发新方法、数据驱动机器学习金属新材料设计、关键金属材料加工过程数字孪生等领域的研究，主持国家自然科学基金、中国博士后科学基金等项目6项，在Advance Materialia、Acta Materialia等期刊发表SCI论文20余篇，转让国家发明专利1项、软件著作权2项，获中国有色金属工业科学技术奖一等奖、北京科技大学校长奖章。

   代表性论文：

1. Zhang H, Fu H, Li W, et al. Empowering the Sustainable Development of High‐End Alloys via Interpretive Machine Learning[J]. Advanced Materials, 2024: 2404478.

2. Zhang H,  Fu H, Zhu S, et al. Machine learning assisted composition effective design for precipitation strengthened copper alloys[J].  Acta Materialia, 2021, 215: 117118.

3. Zhang H, Fu H, He X, et al. Dramatically enhanced combination of ultimate tensile strength and electric conductivity of alloys via machine learning screening[J]. Acta Materialia, 2020, 200: 803-810.

4. Zhang H, He J, Yun P, et al. Effect of Ni/Al atomic ratio on the microstructure and properties of Cu-Ni-Al alloys[J]. Materials Science and Engineering: A, 2024, 908: 146718.

5. Zhang H, He J, Zhu J, et al. Effect of Mg microalloying on the microstructure and properties of conductive Cu-Ni-Al alloy with ultra-high strength[J]. Journal of Alloys and Compounds, 2024, 1005: 176186.