论文发表Publications

Direction 1: Representation Learning & Biomolecular Mechanisms

My current research leverages state-of-the-art Deep Learning techniques to decipher complex biological systems. I focus on overcoming the limitations of traditional bioinformatics by introducing novel inductive biases and representation strategies. My work spans protein structure prediction, protein design, and molecular dynamics, aiming to provide robust, high-throughput tools for the life sciences.

1. Wang, Y., Cai, M., Dong, Y., Ma, Y., & Wei, K. (2025). From Signal to Symphony: Exploring 2D Sequence Representations for Protein Function Prediction. Journal of Chemical Information and Modeling, 65(23), 12723-12736. [PDF]

2. Wang, Y.*, & Cai, M. (2026). Integrative transcriptomics, machine learning, and molecular docking derive a DAM-like macrophage signature for risk stratification and therapeutic nomination in glioblastoma. Computational Biology and Chemistry.

3. Wang, Y.*, Cai, M., Ma, Y., & Wei, K. (2026). Sequence-context-aware decoding enables robust reconstruction of protein dynamics from crystallographic B-factors. Learning Meaningful Representations of Life (LMRL) Workshop at ICLR 2026.

4. Wang, Y.*, Cai, M., Ma, Y., Wang, X., & Wei, K. (2026). Protein Language Models Encode Evolutionary Grammar but Conflate Topological and Thermodynamic Phases. bioRxiv, 2026-04.

5. Wang, Y.†, Ma, Y.†, Chang, Y., Yan, J., Zhang, J., Cai, M., & Wei, K. (2025). Diffusion Models at the Drug Discovery Frontier: A Review on Generating Small Molecules versus Therapeutic Peptides. Biology, 14(12), 1665. [PDF]

6. Wang, X.†, Wang, Y.†*, Huang, T. Y., Dong, Y., Deng, J., Xu, L., ..., & He, R. (2025). Octopus Inspired Optimization (OIO): A Hierarchical Framework for Navigating Protein Fitness Landscapes. In 2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 6897-6904). IEEE. [PDF]

7. Cai, M., Lei, H., Zhang, Y., Zou, J., Cao, W., Wang, Y.*, & Wei, K.* (2025). APOE ε4-Associated Hippocampal Atrophy Trajectories Across the Alzheimer's Disease Continuum: A Systematic Review, Meta-Analysis, and Longitudinal Validation. Frontiers in Aging Neuroscience.

8. Wang, Y.*, & Huang, T. Y.* (2026). Comment on: "GLM7 – A Novel Composite Glycolipid Index Derived from Routine Health Indicators for Enhanced Diagnosis and Prediction of Multimorbidity". Advanced Science. (correspondence).

9. Wang, Y.*, Cai, M., & Huang, T. Y. (2025). AI for disease prediction: Performance insights and key limitations. Journal of Clinical Neuroscience: Official Journal of the Neurosurgical Society of Australasia, 138, 111360. (correspondence). [PDF]

Direction 2: First-Principles of Biological Complexity Based on Mathematical Physics

While Deep Learning provides powerful approximations, my ultimate goal is to find the analytical ground truths of biological systems. I am transitioning from purely data-driven approaches to physics-informed theories. I aim to use Condensed Matter Physics, Topology, Manifold Learning, and Differential Geometry to describe the energy landscapes of proteins and the thermodynamic essence of life.

1. Wang, Y.* (2026). Sub-residue sharpness of protein helix-coil transitions reveals a spatial-spectral uncertainty limit. arXiv preprint arXiv:2602.21787. [arXiv]

2. Wang, Y.* (2026). Piecewise integrability of the discrete Hasimoto map for analytic prediction and design of helical peptides. arXiv preprint arXiv:2602.16255. [arXiv]

3. Wang, Y.* (2026). Structural barriers of the discrete Hasimoto map applied to protein backbone geometry. arXiv preprint arXiv:2602.13160. [arXiv]

Direction 3: Interdisciplinary Explorations & Collaborative Synergies

My research journey is fueled by broad curiosity. I have collaborated with experts in linguistics, computer vision, cryptography, and operations research. These diverse experiences have equipped me with a unique toolkit—allowing me to transfer methodologies and tackle problems from orthogonal perspectives.

1. Wang, Y.*, Huang, T. Y., Gao, Q., Chang, Y., & Zhang, J. (2026). AI Driven Discovery of Bio Ecological Mediation in Cascading Heatwave Risks. Physics and Chemistry of the Earth; also presented at ICLR 2026 Workshop on Foundation Models for Science (FM4Science). [PDF]

2. Wang, Y.*, Chang, Y., Zhang, J., Cai, M., Yan, J., Zhao, H.*, & Alzheimer's Disease Neuroimaging Initiative. (2026). Geometric Fragility in Alzheimer's Disease: Probing the Loss of Hippocampal Hierarchical Abstraction via Contrastive Point Cloud Modeling. In 2026 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE.

3. Wang, Y., Liu, Z., Zai, J., Chen, J., & Sabir, E. (2026). Resilient AI Infrastructure by Design: A Spatially-Aware Framework for Tolerating Clustered Failures. In 4th Annual AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE). [PDF]

4. Wang, Y.*, Cai, M., Zhang, J., Chang, Y., & Yan, J. (2026). Adaptive Decision-Making in Multi-Stage Production: A Framework for Cost Optimization under Sampling Uncertainty. Applied Operations and Analytics, 2(1), 1-23. [PDF]

5. Zuo, J., Wang, Y., & Yibulayin, X. (2026). Relative-to-human Benchmark Cognitive Divergence and Semantic Comprehensibility in Chinese–Uyghur LLM Translation. Frontiers in Psychology.

6. Wang, X.†, Wang, Y.†, & Huang, T. Y.† (2025). Crypto-ncRNA: Non-coding RNA (ncRNA) Based Encryption Algorithm. ICLR 2025 Workshop on AI for Nucleic Acids.[PDF]

7. Wang, X., Wang, F., & Wang, Y. (2025). DIALOGUES BETWEEN ADAM AND EVE: EXPLORATION OF UNKNOWN CIVILIZATION LANGUAGE BY LLM. ICLR 2025 Workshop on World Models: Understanding, Modelling and Scaling.

8. Wang, X.†, Wang, Y.†*, & Pan, J. (2025). Digital Art Creation and Copyright Protection in Pollock Style Using GANs, Fractal Analysis, and NFT Generation. The 1st Workshop on GenAI Watermarking (ICLR 2025). [PDF]

9. Wang, X., Huang, T. Y., Wang, Y., & Yuan, Y. (2025). StrucTrace: Fourier Watermarking for Traceable Bio-molecular Assets. bioRxiv, 2025-10.

10. Zhao, H.*, Lin, H., Yao, X., Zhang, J., Chang, Y., Wang, Y., & Yan, J. (2026). Bridging the Semantic Gap: Hierarchical Mid-level Interaction Graph Reasoning for Video Anomaly Recognition. In 2026 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE.

11. Zhao, H., Shi, W., Liu, C., & Wang, Y. (2025). Boundary Box-Guided Targeted Adversarial Attacks with Semantic Perturbation. In 2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 1604-1609). IEEE.

12. Zuo, J., Wang, Y., Pan, Y., & Yibulayin, X. (2025). Construction and educational application of a linguistically grounded dependency treebank for Uyghur. arXiv preprint arXiv:2507.21536.

13. Wang, Y.*, Wang, J., Huang, T. Y., Yang, J., & Xu, Z. (2025). STGCN-LSTM for Olympic Medal Prediction: Dynamic Power Modeling and Causal Policy Optimization. arXiv preprint arXiv:2501.17711.

14. Luo, Z.†, Wang, X.†, Wang, Y.†, Zhang, H., & Li, Z. (2024). A personalized MOOC learning group and course recommendation method based on graph neural network and social network analysis. arXiv preprint arXiv:2410.10658.

15. Wang, Y.*, Zhang, J., & Chang, Y. (2024). A probability prediction model for flood disasters based on Multi-layer Perceptron. Journal of Physics: Conference Series, 2905(1), 012003. [PDF]

16. Wang, J., & Wang, Y.* (2024). Multi-stage Crop Planting Strategy Optimization Model Based on PSO Algorithm. In 2024 3rd International Conference on Electronics and Information Technology (EIT) (pp. 915-919). IEEE.

17. Wang, G., Wang, Y., & Li, W. (2024). Research on Travel Route Planning Problems Based on Greedy Algorithm. In 2024 4th International Conference on Electronic Information Engineering and Computer Science (EIECS) (pp. 755-758). IEEE.