Projects per year
Personal profile
Personal profile
Dr. Daiyun Huang received his B.Sc. degree in Mathematics from the University of Liverpool, M.Sc. degree in Statistical Science from the University of Oxford, and Ph.D. degree in Bioinformatics and Computer Science from the University of Liverpool. There, he gained significant practical experience in developing AI methodologies for applications in biomedical fields. Following his graduation, Dr. Huang took up a postdoctoral position at XJTLU Wisdom Lake Academy of Pharmacy, co-cultivated with Fudan University, where his research focused on the AI-aided drug design.
In early 2025, Dr. Huang advanced to the role of Assistant Professor at XJTLU Wisdom Lake Academy of Pharmacy. Here, he is responsible for teaching courses on Biostatistics and Artificial Intelligence in Pharmacy, while continuing his research on molecular generation, interactions between macromolecules, and intelligent RNA therapies. He has published 20 papers in SCI-indexed journals, including 9 as first or corresponding author in top journals in the field such as Nature Communications, Nucleic Acids Research, Genomics, Proteomics & Bioinformatics, and Bioinformatics. He also presented his work at the reputed conference ISMB/ECCB 2021. Currently, he hosts grants from the NSFC Young Scientist Fund and Jiangsu Science and Technology Programme Fund.
Research interests
- Practical generative AI framework for small molecules and peptides
- Interpretable neural fingerprints to characterize macromolecular interaction, facilitating the design of PROTACs and molecular glues.
- Intelligent RNA Therapeutics, including mRNA therapies, RNA aptamers, and exploring mechanisms initiated by RNA modifications and the translation of non-coding RNAs.
Experience
Postdoc, Academy of Pharmacy, Xian Jiaotong-Liverpool University, 2022-present
Teaching
APH101-2223-S2-Biostatistics and R Programming
APH102-2223-S2-Mathematical Modeling
Awards and honours
2022年入选“苏州市自然科学优秀学术论文一等奖”（SZLW202206，2020-2021年度）
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
PhD, University of Liverpool
Jan 2019 → Jun 2022
Master, University of Oxford
Sept 2017 → Sept 2018
Bachelor, University of Liverpool
Sept 2013 → Jul 2017
Research areas
- AI-aided Drug Design
- Intelligent RNA Therapeutics
- Deep Learning
Person Types
- Staff
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Collaborations and top research areas from the last five years
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Projects
- 5 Active
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Development of Deep Learning Approaches for Intelligent RNA Therapeutics
Huang, D. (PI)
1/07/25 → 30/06/28
Project: Internal Research Project
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Single-Molecule Single-Cell Imaging and Analysis Innovation Platform
Ruan, G. (PI), Zhang, X. (Team member), Wang, Y. (Team member), Zhou, Z. (Team member), Zhang, J. (Team member), Ding, D. (Team member), Ling, C. (Team member), Wu, Q. (Team member), Xu, P. (Team member), Ho, J. (Team member), Cheng, K. (Team member), Song, J. (Team member), Guo, B. (Team member), Wu, S. (Team member), Wang, J. (Team member), Sun, Y. (Team member), Lu, T. (Team member), Li, T. (Team member), Xu, Y. (Team member), Huang, D. (Team member), Cao, S. (Team member), Leng, J. (Team member) & Wen, X. (Team member)
1/10/24 → 30/09/26
Project: Governmental Research Project
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Jiangsu Province Higher Education Key Laboratory of Cell Therapy Nanoformulation (Construction)
Ruan, G. (PI), Lee, M. H. (Team member), Wu, Q. (Team member), Lu, T. (Team member), Xu, P. (Team member), Loo, S. (Team member), Sun, Y. (Team member), Kam, A. (Team member), Liu, X. (Team member), Wen, X. (Team member), Zhang, J. (Team member), Wang, M. (Team member), Xu, M. (Team member), Cheng, K. (Team member), Zhang, X. (Team member), Song, J. (Team member), Guo, B. (Team member), Wang, Y. (Team member), Wang, J. (Team member), Wu, S. (Team member), Yang, J. (Team member), Fu, L. (Team member), Zhang, J. (Team member), Qiao, Y. (Team member), Chen, Y. (Team member), Li, T. (Team member), Zhan, T. (Team member), Wan, Y. (Team member), He, Z. (Team member), Cheng, Y. (Team member), Leng, J. (Team member), Qi, M. (Team member), Ho, J. (Team member), Sun, Y. (Team member), Zhang, N. (Team member), Soe, H. M. S. H. (Team member), Ling, C. (Team member), Zhou, H. (Team member), Huang, D. (Team member) & Gu, J. (Team member)
1/07/24 → 30/06/27
Project: Governmental Research Project
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Prediction and engineering of non-coding sequences of mRNA therapeutics based on deep learning
Huang, D. (PI)
1/01/24 → 31/12/26
Project: Governmental Research Project
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Research on mitigating cold-protein problem in deep learning-based drug hits virtual screening models
Liu, X. (Team member), Li, T. (Team member), Hao, Y. (Team member), Wang, T. (Team member), Zha, H. (Team member), Li, B. (Team member), Chen, Y. (Team member) & Huang, D. (PI)
1/09/23 → 31/08/26
Project: Governmental Research Project
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Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2025
CNCB-NGDC Members and Partners, 6 Jan 2025, In: Nucleic Acids Research. 53, D1, p. D30-D44Research output: Contribution to journal › Article › peer-review
Open Access46 Citations (Scopus) -
OncoTrace-TOO: Interpretable Machine Learning Framework for Cancer Tissue-of-Origin Identification Using Transcriptomic Signatures
Hao, Y., Huang, H., Huang, D., Ruan, J., Liu, X. & Zhang, J., Aug 2025, In: Cancer Reports. 8, 8, e70311.Research output: Contribution to journal › Article › peer-review
Open Access -
Paradigms, innovations, and biological applications of RNA velocity: A comprehensive review
Wang, Y., Li, J., Zha, H., Liu, S., Huang, D., Fu, L. & Liu, X., 1 Jul 2025, In: Briefings in Bioinformatics. 26, 4, bbaf339.Research output: Contribution to journal › Review article › peer-review
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Paradigms, innovations, and biological applications of RNA velocity: a comprehensive review
Wang, Y., Li, J., Zha, H., Liu, S., Huang, D., Fu, L. & Liu, X., 1 Jul 2025, In: Briefings in Bioinformatics. 26, 4, p. bbaf339Research output: Contribution to journal › Article › peer-review
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AI techniques have facilitated the understanding of epitranscriptome distribution
Huang, D., Meng, J. & Chen, K., 11 Dec 2024, In: Cell Genomics. 4, 12, 100718.Research output: Contribution to journal › Comment/debate
Open Access1 Citation (Scopus)
Activities
- 1 Presentation at conference/workshop/seminar
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Weakly supervised learning of RNA modifications from low-resolution epitranscriptome data
Daiyun Huang (Speaker)
25 Jul 2021 → 30 Jul 2021Activity: Talk or presentation › Presentation at conference/workshop/seminar