Hengjie Yu, Ph.D.

Profile

Dr. Hengjie Yu is an Assistant Researcher in the Department of Artificial Intelligence at Westlake University. He received his Ph.D. from the Department of Biosystems Engineering, Zhejiang University, in 2024. During his doctoral studies, he completed a one-year joint training program in the Department of Chemistry at the National University of Singapore. He subsequently completed his postdoctoral training in the Department of Artificial Intelligence at Westlake University from 2024 to 2026.

Dr. Yu’s research lies at the intersection of AI for Science, nano–bio interfaces, and biomacromolecular analysis and design. As an early adopter of explainable AI (XAI) in nano–bio interface research, he integrates wet-lab experimentation, domain knowledge, and advanced AI to investigate nanomaterial–protein/plant–environment interactions. He also applies advanced AI approaches to investigate protein and RNA function and reactivity, with the goal of uncovering their underlying molecular mechanisms. His interdisciplinary work has been published in journals spanning environmental science, nanotechnology, and chemical engineering, including Environmental Science & Technology, Chemical Engineering Journal, Environmental Science: Nano, and Nanoscale, as well as AI and computational venues such as Artificial Intelligence Review, MICCAI and IJCNN. Driven by a passion for interdisciplinary innovation, he is dedicated to leveraging advanced AI methodologies to address important scientific challenges.

News

Empowering scientific discovery with explainable small domain-specific and large language models. Our article is now online in Artificial Intelligence Review！We hope that our research experience in AI and Science can provide some unique perspectives on AI for Science from a knowledge perspective.

Unlocking the Potential of AI Researchers in Scientific Discovery: What Is Missing?.Drawing on the Diffusion of Innovation theory, we project that AI4Science’s share of total publications will rise from 3.57% in 2024 to approximately 25% by 2050. Unlocking the potential of AI researchers is essential for driving this shift and fostering deeper integration of AI expertise into the research ecosystem. To this end, we propose structured and actionable workflows, alongside key strategies to position AI researchers at the forefront of scientific discovery.

Congratulations to Prof. Yaochu Jin for winning the 2025 IEEE Frank Rosenblatt Award!!!

Optimizing benefit-risk trade-off in nano-agrochemicals through explainable machine learning: Beyond concentration. Our article is now online in Environmental Science: Nano！This study proposes an explainable optimization method for accelerating the screening and design of nano-agrochemicals.

Contact

Email: yuhengjie@westlake.edu.cn