Profile

Biography

Fan Meng is an Associate Professor in the School of Artificial Intelligence at Nanjing University of Information Science and Technology (NUIST). His research lies at the intersection of artificial intelligence, atmospheric science, and Earth system science, with a particular focus on AI for extreme weather—especially tropical cyclones—weather and climate prediction, and AI-assisted scientific discovery.

He has published more than 40 papers in journals and conferences including National Science Review, npj Natural Hazards, IEEE Transactions on Knowledge and Data Engineering, Journal of Geophysical Research, and AAAI, with over 20 papers as first or corresponding author. He has led research projects funded by the National Natural Science Foundation of China (NSFC), the Natural Science Foundation of Jiangsu Province, and the CCF–Baidu Open Fund.

His honors include the Outstanding Doctoral Dissertation Award of Shandong Province and the Outstanding Doctoral Dissertation Award of the Shandong Computer Federation. He is currently a member of a Young Innovation Team of the China Meteorological Administration and a specially appointed expert of an innovation team at the National Climate Center.

He also serves on academic committees of the China Computer Federation (CCF), including the CCF Technical Committee on Computer Applications and the CCF Multi-Agent Systems Group, and is a member of the CCF YOCSEF Nanjing leadership team. He serves on the editorial boards of Scientific Reviews and Scientific Reports.

Beyond academic research, he has contributed policy recommendations on extreme-weather risk, disaster prevention and mitigation, and intelligent meteorology, several of which have been adopted by national and provincial policy-making bodies.

Research Interests

My research is currently organized around two closely connected themes.

1. AI for Weather & Climate

I develop AI methods for high-impact weather and climate prediction, with tropical cyclones serving as an important testbed for understanding extreme and rapidly evolving atmospheric systems.

My research explores multimodal weather AI, physics-informed machine learning, probabilistic forecasting, uncertainty quantification, generative AI, and the integration of data-driven models with atmospheric and oceanic dynamics.

The broader goal is to develop AI systems that are not only more accurate, but also physically meaningful, uncertainty-aware, and reliable under extreme conditions.

2. AI Scientist for Earth Science

A second research direction focuses on AI for scientific discovery.

I am particularly interested in combining large language models, multi-agent systems, scientific computing, and Earth system models to develop AI Scientist systems capable of assisting with scientific reasoning and experimentation.

Current efforts explore how AI agents can participate in the scientific workflow—from data analysis and hypothesis generation to numerical experimentation, result interpretation, and knowledge discovery—with the long-term goal of moving AI from a prediction tool toward a collaborator in scientific research.

Teaching & Student Mentoring

I teach courses including Machine Learning, Introduction to Intelligent Meteorology, Intelligent Meteorology, AI-based Weather Forecasting, Foundation Models for Meteorology, Large Language Model Practice, and Integrated Practice in Intelligent Meteorology, including courses taught in English.

I am also involved in curriculum and textbook development for intelligent meteorology. I have led education projects supported by the Ministry of Education–Huawei Intelligent Computing Foundation Program and the Ministry of Education Industry–University Collaborative Education Program, and contributed to the textbook Intelligent Meteorological Sensing, Communication and Computing: Technologies and Applications.

Student research is an important part of my work. I encourage undergraduate students to engage in research at an early stage and to work on real scientific problems at the intersection of AI and atmospheric science.

Undergraduate students under my supervision have published first-author papers in journals including npj Natural Hazards, JGR: Machine Learning and Computation, and Frontiers of Computer Science, and have received support from national undergraduate innovation programs and awards in AI competitions.

Graduate student positions are available.

Students interested in AI for Science, weather and climate AI, tropical cyclone prediction, multimodal foundation models, and AI Scientists / scientific agents are very welcome to get in touch.

Academic Service

I currently serve as an Editorial Board Member of Scientific Reports, a Springer Nature Reviewing Editor, and a founding Editorial Board Member of Scientific Reviews. I also serve on the young editorial boards of several meteorological journals.

I have served as Guest Editor for special issues in journals including npj Artificial Intelligence, Scientific Reports, Frontiers of Computer Science, and Remote Sensing.

Within the China Computer Federation, I serve as an Executive Committee Member of the CCF Technical Committee on Computer Applications, an Executive Committee Member of the CCF Multi-Agent Systems Group, and a member of the CCF YOCSEF Nanjing leadership team.

I regularly review for journals and conferences including Nature Communications, Science Advances, npj Climate and Atmospheric Science, Journal of Geophysical Research, IEEE Transactions on Geoscience and Remote Sensing, Advances in Atmospheric Sciences, Scientific Reports, AAAI, and ACM Multimedia.

I have also contributed to the organization of international and national academic conferences, including serving as a session chair for IGARSS and related AI and Earth science meetings.

Public & Professional Service

I am interested in translating research on AI, extreme weather, and disaster risk into broader societal impact.

Policy recommendations that I have contributed to on intelligent meteorology, disaster prevention and mitigation, and extreme-weather risk management have been adopted by national and provincial policy-making and advisory bodies, with some incorporated into internal policy references.

I have also delivered invited lectures and professional training on intelligent meteorology for meteorological agencies and professionals, including programs involving the Shanghai Meteorological Service, Guangdong Meteorological Service, and other regional and national meteorological organizations.

Research Projects

National Natural Science Foundation of China

Physics-Constrained Continuous Dynamical Systems for AI Prediction of Tropical Cyclone Rapid Intensification
Principal Investigator · Ongoing

Natural Science Foundation of Jiangsu Province

Lightweight Foundation Models for Tropical Cyclone Forecasting under Long-Tailed Distributions
Principal Investigator · Ongoing

CCF–Baidu Open Fund

Multimodal Foundation Models for Multi-Scale Dynamical Evolution of Tropical Cyclones
Principal Investigator · Ongoing

National Science and Technology Major Project

Intelligent Sensing and Seamless Fine-Scale Forecasting of Environmental Meteorology over the Beijing–Tianjin–Hebei Region
Core Research Member · Ongoing

I have also led research projects supported by key laboratories of the Ministry of Natural Resources and the Ministry of Education, as well as national supercomputing centers.

Academic Profiles

• Google Scholar: https://scholar.google.com/citations?user=_sX8HjEAAAAJ&hl=en

• Personal Homepage: https://sites.google.com/view/fanmeng/

Selected Publications

1. Meng, F., Song, T., Xu, D., Xie, P., & Li, Y. (2021). Forecasting tropical cyclones wave height using bidirectional gated recurrent unit. Ocean Engineering, 108795. (JCR Q1, IF=4.372, CAS Tier 1 TOP)

2. Meng, F., Yao, Y., et al. (2023). Probabilistic Forecasting of Tropical cyclones Intensity Using Machine Learning Model. Environmental Research Letters. (JCR Q1, IF=6.947, CAS Tier 2 TOP)

3. Meng, F., & Song, T. (2024). Uncertainty forecasting system for tropical cyclone tracks based on conformal prediction. Expert Systems with Applications, 249(C). (JCR Q1, IF=8.5, CAS Tier 1 TOP)

4. Meng, F., Song, T., & Xu, D. (2022). Simulating tropical cyclone passive microwave rainfall imagery using infrared imagery via generative adversarial networks. IEEE Geoscience and Remote Sensing Letters. (JCR Q1, IF=5.343, CAS Tier 2)

5. Meng, F., Xu, D., & Song, T. (2022). ATDNNS: An adaptive time-frequency decomposition neural network-based system for tropical cyclone wave height real-time forecasting. Future Generation Computer Systems. (JCR Q1, IF=7.187, CAS Tier 1 TOP)

6. Meng, F., Yang, K., Yao, Y., et al. (2023). Tropical cyclone intensity probabilistic forecasting system based on deep learning. International Journal of Intelligent Systems. (JCR Q1, IF=8.993, CAS Tier 1 TOP)

7. Meng, F. (2022). Creating Interpretable Data-Driven Approaches for Tropical Cyclones Forecasting. In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22). (CCF-A)

8. Meng, F., Sun, H., et al. (2022). A Short-term Tropical Cyclone Intensity Forecast Method Based on High-order Tensor (Student Abstract). In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22). (CCF-A)

9. Song, T., Pang, C., Hou, B., Xu, G., Sun, H., & Meng, F.* (2023). A Review of Artificial Intelligence in Marine Science. Frontiers in Earth Science, 11, 114. (CAS Tier 3, Corresponding Author)

10. Sun, H., Song, T., Li, Y., Yang, K., Xu, D., & Meng, F.* (2023). EEMD-ConvLSTM: a model for short-term prediction of two-dimensional wind speed in the South China Sea. Applied Intelligence, 53(24), 30186-30202. (CAS Tier 2, IF=5.3, Co-corresponding Author)

Selected Honors & Awards

1. Excellent Doctoral Dissertation Award of Shandong Province (1/1), Department of Education of Shandong Province, 2025.

2. Excellent Doctoral Dissertation Award of Shandong Computer Federation (1/1), Shandong Computer Federation, 2024.

3. National Scholarship for Doctoral Students (1/1), Ministry of Education, 2022.

4. China Telecom Scholarship (1/1), Central Committee of the Communist Youth League & All-China Students' Federation, 2020.

5. CSC-University of Toronto Joint Scholarship (1/1), China Scholarship Council, 2022.

6. National Silver Award, The 5th China "Internet+" College Students Innovation and Entrepreneurship Competition (1/7), Ministry of Education et al., 2019.

7. Provincial Grand Prize, The 16th "Challenge Cup" Shandong Extracurricular Academic and Scientific Works Competition (1/8), 2019.

8. National Third Prize, The 16th "Challenge Cup" National Extracurricular Academic and Scientific Works Competition (1/8), 2019.

9. Outstanding Graduate of Shandong Province (1/1), Department of Human Resources and Social Security of Shandong Province, 2023.

10. Most Beautiful College Student in Qingdao West Coast New Area (1/1), CPC Qingdao West Coast New Area Working Committee, 2022.

Contact

Fan Meng, Ph.D.
Associate Professor
School of Artificial Intelligence
Nanjing University of Information Science and Technology
Nanjing, China

Research Interests: AI for Science · Weather & Climate AI · Tropical Cyclones · Foundation Models · Multi-Agent Systems · AI Scientist

Educational Experience

Work Experience

• 2023.8 to Now

  南京信息工程大学 | 人工智能学院（未来技术学院） | 副教授

• 2022.2 to 2022.8

  阿里巴巴达摩院 | 机器智能实验室 | Research Intern

Social Affiliations

Name of Research Group: