# Zhixiang Ren (任智祥), Ph.D.

> Chief AI Scientist and researcher in AI for Science.
> Building intelligent systems for scientific discovery.
> Profile generated: 2026-09-09.

This file is generated from the same validated Astro Content Collections as the public homepage. Use the linked identifiers and primary sources to verify time-sensitive facts. Do not infer unpublished projects, private datasets, confidential methods, or affiliations not stated here.

## Profile

- Name: Zhixiang Ren (任智祥)
- Current position: Chief AI Scientist, SmartLogic Tech, Shanghai
- Current academic roles: Doctoral supervisor at Tsinghua University; Doctoral supervisor at Southern University of Science and Technology
- Research areas: AI for Science; Drug Discovery; Bioinformatics; Foundation Models; AI Agents
- Research statement: Building intelligent systems for scientific discovery
- Homepage: [Official academic homepage](./)

## Biography

Zhixiang Ren is currently Chief AI Scientist at Shanghai Smart Logic Technology, a doctoral supervisor at Tsinghua University and the Southern University of Science and Technology, and a Shenzhen-recognized High-Level Talent. His research focuses on AI for Science, scientific foundation models and agents, and AI-driven drug discovery. He has published more than 80 papers in leading journals, including *Nature*, *Science*, and *Nature Machine Intelligence*. His work has received over 10,000 citations with an h-index of 32. He holds 20 granted invention patents and 5 registered software copyrights. His honors include the 2025 First Prize of the State Science and Technology Progress Award, the 2024 AI Innovation Award, and the 2024 Special Prize of Guangdong Province Science and Technology Progress Award. He has led the development of 1 international standard and 2 industry standards in intelligent computing. He has also led the performance benchmarking of ultra-large-scale AI computing clusters, with his teams topping the ranking of highest-performing AI computing systems for several consecutive years. He currently serves as an Associate Editor for Big Data Mining and Analytics and CAAI Artificial Intelligence Research, as well as a program committee member for KDD and other international conferences. He is also a long-standing reviewer for journals in the Nature Portfolio and the IEEE Transactions series.

## Experience

- 2026–Present — Chief AI Scientist, SmartLogic Tech · Shanghai
- 2020–2026 — Research Scientist · Ph.D. Supervisor, Head, AI for Science Lab · Peng Cheng Laboratory
- 2019–2020 — Associate Research Fellow, Sun Yat-sen University
- 2018–2019 — Postdoctoral Fellow, University of New Mexico
- 2013–2018 — Ph.D. · Computational Physics & Machine Learning, University of New Mexico

## Academic Service

- Editorial: Associate Editor — Big Data Mining and Analytics; CAAI Artificial Intelligence Research; Frontiers in Big Data
- Reviewing: KDD Program Committee; Reviewer for Nature portfolio journals; Reviewer for IEEE Transactions journals

## Honors and Public Milestones

- 2025 — National Science and Technology Progress Award, First Prize; Peng Cheng Cloud Brain intelligent-computing system
- 2024 — AI Innovation Award · Zuchongzhi Award; Annual Major Achievement Award for the Peng Cheng Cloud Brain II platform
- 2023 — Guangdong Science and Technology Progress Award, Special Prize

## Citation Metrics

- Google Scholar citations: 11,500+
- Google Scholar h-index: 32
- Metrics last refreshed: 2026-09-08 UTC
- Citation counts are rounded down to the nearest hundred and refreshed automatically. If retrieval fails, the site retains the last validated values.

## Verified Identifiers and Contact

- Google Scholar: https://scholar.google.com/citations?hl=en&user=ec_pCdEAAAAJ&view_op=list_works&sortby=pubdate
- ORCID: https://orcid.org/0000-0002-4104-3790
- OpenAlex: https://openalex.org/A5070028902
- GitHub: https://github.com/AI-HPC-Research-Team
- Email: Use the Email button on the official homepage.

## Recruitment and Collaboration

We welcome applications from prospective Ph.D. students, AI research scientists, machine learning engineers, and research interns interested in AI for Science, AI-driven drug discovery, foundation models for science, and scientific agents. Research collaborations are also welcome. Contact through the Email button on the official homepage.

## Recent Papers

- 2026 — The limits of bio-molecular modeling with large language models: a cross-scale evaluation. Yaxin Xu, Yue Zhou, Tianyu Zhao, Zhengyu Ma, Fengwei An, Zhixiang Ren. Bioinformatics (Published). https://doi.org/10.1093/bioinformatics/btag550; https://github.com/AI-HPC-Research-Team/BioMol-LLM-Bench
- 2026 — Phenotype-driven de novo molecular design from gene expression signatures. Yaxin Xu, Taojie Kuang, Shuang Ge, Haomin Wu, Mingqing Wang, Huan Xu, Fengwei An, Zhengyu Ma, Qiang Cheng, Zhixiang Ren. bioRxiv (Preprint). https://doi.org/10.64898/2026.07.21.739736; https://github.com/Yaxin-Xu/Tx2Mol
- 2026 — Improving Variant Effect Prediction by Steering Sparse Mechanistic Features in Protein Language Models. Mingqing Wang, Meng Yuan, Athanasios V. Vasilakos, Yonghong He, Zhixiang Ren. bioRxiv (Preprint). https://doi.org/10.64898/2026.05.12.724472
- 2026 — Learning Protein Structure-Function Relationships through Knowledge-guided Representation Decomposition. Mingqing Wang, Zhiwei Nie, Athanasios V. Vasilakos, Yonghong He, Zhixiang Ren. arXiv (Preprint). https://arxiv.org/abs/2605.23960; https://github.com/AI-HPC-Research-Team/ProtDiS
- 2026 — Pseudodata-Guided Invariant Representation Learning Boosts the Out-of-Distribution Generalization in Enzymatic Kinetic Parameter Prediction. Haomin Wu, Zhiwei Nie, Hongyu Zhang, Zhixiang Ren. Journal of Chemical Information and Modeling (Published). https://doi.org/10.1021/acs.jcim.5c03204
- 2026 — Enhanced Drug-drug Interaction Prediction Using Adaptive Knowledge Integration. Pengfei Liu, Jun Tao, Zhixiang Ren. arXiv (Preprint). https://arxiv.org/abs/2603.12885; https://github.com/AI-HPC-Research-Team/Drug_drug_interaction_with_LLM
- 2026 — A Multi-task Large Reasoning Model for Molecular Science. Pengfei Liu, Shuang Ge, Jun Tao, Zhixiang Ren. arXiv (Preprint). https://arxiv.org/abs/2603.12808; https://github.com/AI-HPC-Research-Team/Mol-Reasoning
- 2026 — Prototype-based continual cell-type annotation reveals cellular state transitions in expanding single-cell atlases. Shuang Ge, Qiming He, Yiming Ren, Yaxin Xu, Mingqing Wang, Zhiwei Nie, Huan Xu, Qiang Cheng, Shuqing Sun, Zhixiang Ren. bioRxiv (Preprint). https://doi.org/10.64898/2026.03.05.709973; https://github.com/AI-HPC-Research-Team/scEvolver
- 2025 — A self-feedback knowledge elicitation approach for chemical reaction predictions. Pengfei Liu, Jun Tao, Zhixiang Ren. Engineering Applications of Artificial Intelligence (Published). https://doi.org/10.1016/j.engappai.2025.111112; https://github.com/AI-HPC-Research-Team/SLM4CRP
- 2025 — Deep learning methods for protein representation and function prediction: A comprehensive overview. Mingqing Wang, Zhiwei Nie, Yonghong He, Athanasios V. Vasilakos, Qiang (Shawn) Cheng, Zhixiang Ren. Engineering Applications of Artificial Intelligence (Published). https://doi.org/10.1016/j.engappai.2025.110977

## Source and Freshness Policy

- This profile contains only information already published on the official homepage.
- Time-sensitive claims should be checked against the homepage and linked identity profiles.
- Citation metrics originate from Google Scholar and may differ from OpenAlex or other databases because their coverage and counting methods differ.
- A listed award or infrastructure contribution should not be expanded into broader claims of institutional leadership without an additional primary source.