I am currently a Ph.D. student at Tianjin University (Wikipedia) and a jointly trained Ph.D. student at Shenzhen Loop Area Institute (SLAI). My supervisors are Guangrong Zhao at Tianjin University and Yu Li (CUHK) at Shenzhen Loop Area Institute.
Previously, I received my B.S. in Biological Science from Xinjiang University in June 2026, graduating with a GPA of 4.30 and ranking in the top 1%.
Research Interests: AI for Synthetic Biology, bio-inspired algorithm optimization, multi-scale coupling simulation of large biomolecules (cross-system / cross-method), and trustworthy scientific AI agents.
Email: ziyan@tju.edu.cn / ziyanzhuang@slai.edu.cn
CV / Github / ORCID / Google Scholar
I love biology — more is different.
PKU taught me to see the spatiotemporal complexity emerging from the central dogma and molecular networks; SJTU showed me how AI can map dense, entangled biological signals into higher-dimensional latent spaces to reveal sparse structure. At XJU, Dr. Wen Zhong's developmental biology teaching showed me how nonlinear development makes causal reasoning essential to biological research. These experiences led me to synthetic biology—augmented by AI—as a path to understand, design, and improve living systems. As Feynman said, “What I cannot create, I do not understand.”
In memory of Dr. Wen Zhong, who passed away on 6 March 2026. Rest in peace.
* denotes corresponding author.
An autonomous scientific intelligence platform that integrates a cross-disciplinary knowledge graph, a multi-agent reasoning system, and hierarchical scientific skills (protein design, molecular simulation, metabolic network analysis) into a closed Think→Act→Observe→Review→Re-decide loop. It enables cross-scale intelligent bioengineering — from catalytic mechanism reasoning and enzyme active-site design to whole-cell metabolic network optimization.
An auditable workflow for preparing CYP450 protein–heme–ligand systems for Amber molecular dynamics, with manifest-based quality gates across parameterization, solvation, and pre-MD preparation.
A reproducible pipeline for protein-structure visualization that separates structural facts, chemical topology, interaction evidence, and Blender rendering.
Participated in Westlake AIVC Week at the Yungu Campus of Westlake University, a flagship international program advancing the AI Virtual Cell (AIVC) vision. Engaged with frontier directions spanning AI virtual cell modeling, multi-omics integration, deep learning foundation models, and AI for Science, gaining insights into how these converging approaches are reshaping biological research toward data-driven simulation of living systems.
Volunteered for Zhejiang University's China Temple Ancient Ginkgo Leaf Collection Initiative, performing standardized sampling of ancient ginkgo trees. Specimen data has been archived in the Zhejiang University Herbarium and incorporated into the GinkgoDB comprehensive ginkgo database, providing important specimens and data for ancient ginkgo germplasm conservation and genetic lineage research.
Participated in the summer school at the Institute of Natural Sciences, Shanghai Jiao Tong University, focusing on the application of artificial intelligence in bioengineering. Learned cutting-edge techniques including AI-driven protein design and computational biology workflows.
Participated in the summer school at the Center for Life Science (CLS), Peking University, exploring quantitative methods in biological research, including mathematical modeling of biological systems and data-driven experimental design.
Participated in field research in the Northern Tianshan Mountains, using infrared camera technology to record and analyze the behavior and distribution of local wild animals. The visual above shows representative footage captured during the internship.