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Yunhao Yang Academic CV

Yunhao Yang

Research profile · 中文简历

Research Interests

My research focuses on the rational design of biomaterial systems and structures across scales. I combine physics-informed artificial intelligence, multiscale simulation, and experimental validation to investigate how composition, hierarchical organization, and interactions govern material properties and function. Current work spans structural proteins, fibrous networks, and flexible material systems.

Education

2026 – PresentPh.D. student in Polymer Chemistry and Physics
Fudan University · Department of Macromolecular Science
Advisor: Prof. Shengjie Ling · Biomacromolecules Group

Research Experience

2025 – 2026Engineer, Zhangjiang Institute, Fudan University
Department of Macromolecular Science · Biomacromolecules Group
Simulation and optimization of complex three-dimensional fibrous networks with manufacturing constraints

Honors and Awards

  • 2026 — Runner-up, AI for Research Track, Inaugural World AI Open Source Competition
  • 2026 — Second Prize in the Achievement Category, Invention and Entrepreneurship Award, China Invention Association (third contributor)
  • 2026 — Ruiqing Scholarship, Fudan University

First- and Co-first-author Publications

# Equal contribution.

  1. Yang Y., Sun S., Xu C. et al. Machine Learning–Driven Structural Optimization of Zigzag Silk Fibroin Ionic Conductors for Spatially Resolved Wearable Motion Detection. npj Flexible Electronics, 2026.
  2. Yang Y., Ren J., Cao L. et al. A manufacturability-informed topology framework for AI-guided design of fibrous network materials. Nature Communications, 2026, 17, 9237. DOI.
  3. Ma C.#, Ma X.#, Yang Y.# et al. Processing-History-Programmed Silk Fibers Integrating Mechanical Robustness, Ionic Conduction, and Optical Waveguiding for Intelligent Wearables. Advanced Functional Materials, 2026, 36(51), e76164. DOI.
  4. Yang S.#, Yang Y.#, Huang C. et al. Physics-informed graph neural networks for predicting deformation in disordered fibrous materials. Nano Letters, 2026, 26(1), 205–213. DOI.
  5. Yang Y., Cao L., Ren J. et al. Artificial intelligence for fibrous network design and mechanics. AI for Science, 2025, 1, 012001. Publisher page.
  6. Yang Y.#, Bai R.#, Gao W. et al. Optimizing Biomimetic 3D Disordered Fibrous Network Structures for Lightweight, High-Strength Materials via Deep Reinforcement Learning. Advanced Science, 2025, 12, 2413293. DOI.

Co-authored Publications

  1. Peng R.#, Zhou L.#, Bai R., Yang Y. et al. Early pathway selection precedes conformational locking in protein self-assembly. ACS Nano, 2026.
  2. Chi Q., Liu Y., Yang Y. et al. Study of Structure-Property Relationship in Silkworm Cocoons for Bio-inspired Design and Fabrication. Acta Polymerica Sinica, 2026, 26163. DOI.
  3. Zhou Y.#, Yang S.#, Cao L., Ren J., Bai R., Yang Y. et al. A percolation-based theoretical model reveals the structural origin of strain-stiffening in semiflexible fibrous networks. Soft Matter, 2026, 22, 4371–4381. DOI.
  4. Ye C.#, Zhang H.#, Yang Y. et al. Sustainable Silk Fibroin Ionic Touch Screens for Flexible Biodegradable Electronics with Integrated AI and IoT Functionality. Advanced Materials, 2025, 37(22), 2412972. DOI.
  5. Yang S.#, Zhao C.#, Yang Y. et al. The Fractal Network Structure of Silk Fibroin Molecules and Its Effect on Spinning of Silkworm Silk. ACS Nano, 2023, 17(8), 7662–7673. DOI.

Patents

  1. Lin J., Ren G., Zeng Y., … Ling S., Yang Y., Huang C. Shoe midsole for sports shoes and corresponding sports shoes. Application no. 202521751713.1.
  2. Ling S., Gao W., Yang Y. Method, device, and electronic equipment for generating weaving patterns. Publication no. CN121637586A.

Industry Collaborations

  • AI-Enhanced Design Engine, Anta Sports · December 2023 – June 2024
  • Mechanical Metamaterial Design for Sports Shoe Midsoles, Anta Sports · December 2024 – June 2025
  • Digital Design Software for Mesh Insoles, Anta Sports · September 2026 – September 2027 (ongoing)

Open Source

fibernet · An open-source Python library for fibrous network research.