Biography
I am affiliated with the Australian Artificial Intelligence Institute (AAII) at the University of Technology Sydney, where my research focuses on machine learning, multimodal learning, agentic AI, and AI for scientific design and problem solving. I do research purely out of curiosity. I have published over 50 peer-reviewed papers with 1000+ citations, with most of my first-author work appearing in top-tier venues, including conferences (NeurIPS, ICLR, ICML, ACM MM, AAAI, IJCAI, WWW, ICMR, MICCAI) and journals (IEEE TGRS, IEEE JBHI, IF, KBS, OE).
I bring over three years of industry experience in applied machine learning. I was a Research Associate in deep learning at the Shenzhen Institute of Meteorological Innovation, China (2021–2024), where I worked on real-world climate modeling based on remote-sensing data. In 2024, I was a visiting researcher at The Hong Kong Polytechnic University (PolyU), working on medical imaging processing.
I have delivered invited talks and tutorials, including Federated Intelligence in Web: A Tutorial at WWW 2025 (Sydney, Australia), Personalized Adapter for Large Meteorology Models on Devices at the FLFM Workshop @ AJCAI 2024 (Melbourne, Australia), and Federated Prompt Learning for Weather Foundation Models on Devices at the Main Track & AI4CI Workshop @ IJCAI 2024 (Jeju, South Korea).
I actively contribute to the research community as an Associate Editor of JESIT, and as a reviewer and Area Chair for numerous leading journals and conferences (e.g., TPAMI, TKDE, TNNLS, JMLR, NeurIPS, ICLR, ICML, CVPR, MM, KDD, AAAI, IJCAI), handling over 60 papers each year.
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Research Interest
My long-term vision is to build AI systems that can learn, reason, and act reliably in the messy, ever-changing real world, from planetary-scale weather and climate to the fine-grained structure of medical images and photonic sensor data. My research spans machine learning, multimodal learning, agentic AI, and AI for scientific design and problem solving, unified by a central question: how can intelligent agents learn from limited, heterogeneous, and privacy-sensitive data across devices, institutions, and modalities, while remaining robust, generalizable, and trustworthy in an open world? This has led me to work on federated and foundation models for time series, weather, and climate; multimodal learning for medical imaging; and AI-driven scientific discovery in photonics and remote sensing. My work centers on the following focus areas:
- Machine Learning
- Multimodal Learning
- Agentic AI
- AI for Scientific Design and Problem Solving
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* indicates co-first authorship; indicates corresponding author.
Large-Scale Federated Foundation Models
Pushing foundation models to learn at scale across distributed, privacy-sensitive data without ever centralizing it.
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Bi-Level Heterogeneous Learning for Time Series Foundation Models: A Federated Learning Approach
Shengchao Chen, Guodong Long, Dikai Liu, Jing Jiang
arXiv preprint arXiv:2604.06727 [Preprint], 2026.
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FeDaL: Federated Dataset Learning for General Time Series Foundation Models
Shengchao Chen, Guodong Long, Michael Blumenstein, Jing Jiang
The Fourteenth International Conference on Learning Representations (ICLR) [Core A*/CCF-A], 2026.
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Federated Foundation Models on Heterogeneous Time Series
Shengchao Chen, Guodong Long, Jing Jiang, Chengqi Zhang
Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI) [Core A*/CCF-A], 2025.
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Federated Intelligence in Web: A Tutorial
Peng Yan*,
Shengchao Chen*, Guodong Long*
Companion Proceedings of the ACM on Web Conference (WWW) [Core A*/CCF-A], 2025.
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Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models
Shengchao Chen, Guodong Long, Jing Jiang, Chengqi Zhang
Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS) [Core A*/CCF-A], 2024.
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Federated Prompt Learning for Weather Foundation Models on Devices
Shengchao Chen, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang
The 33rd International Joint Conference on Artificial Intelligence (IJCAI) [Core A*/CCF-A], 2024.
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Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data
Shengchao Chen, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang
The 32rd International Joint Conference on Artificial Intelligence (IJCAI) [Core A*/CCF-A], 2023.
Trustworthy Medical AI
Building AI that clinicians can trust, bridging the gap between algorithmic performance and real clinical impact.
Remote Sensing Intelligence
Turning raw signals from sky and space into real-time, actionable understanding of a changing planet.
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Free Lunch for Federated Remote Sensing Target Fine-Grained Classification: A Parameter-Efficient Framework
Shengchao Chen, Ting Shu, Huan Zhao, Jiahao Wang, Sufen Ren, Lina Yang
Knowledge-Based Systems (KBS) [JCR Q1/TOP], 2024.
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MASK-CNN-Transformer for Real-Time Multi-Label Weather Recognition
Shengchao Chen, Ting Shu, Huan Zhao, Yuan Yan Tang
Knowledge-Based Systems (KBS) [JCR Q1/TOP], 2023.
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TempEE: Temporal-Spatial Parallel Transformer for Radar Echo Extrapolation Beyond Auto-Regression
Shengchao Chen, Ting Shu, Huan Zhao, Guo Zhong, Xunlai Chen
IEEE Transactions on Geoscience and Remote Sensing (IEEE TGRS) [JCR Q1/TOP], 2023.
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Dynamic Multiscale Fusion Generative Adversarial Network for Radar Image Extrapolation
Shengchao Chen, Ting Shu, Huan Zhao, Qilin Wan, Jincan Huang, Cailing Li
IEEE Transactions on Geoscience and Remote Sensing (IEEE TGRS) [JCR Q1/TOP], 2022.
AI for Scientific Design and Problem Solving
Treating AI as a scientific instrument that can reason, design, and discover alongside human experts.
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The Physicist, the Coder, and the Critic: Agentic Photonic Crystal Fiber Inverse Design via Verbal Gradient Descent
Shengchao Chen, Ting Shu
Findings of the Association for Computational Linguistics: EMNLP 2026 (EMNLP) [Core A*/CCF-B].
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Learning Design Skills as Memory Policies for Agentic Photonic Inverse Design
Shengchao Chen, Ting Shu, Sufen Ren
Knowledge-Based Systems (KBS) [JCR Q1/TOP], 2026.
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Towards Scalable and Accurate Property Prediction for Photonic Crystal Fibers with Federated Learning
Guanjun Wang, Jiacheng Liu,
Shengchao Chen, Sufen Ren
Optics Express 33 (16), 33421-33434, 2025. [JCR Q1]
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Federated Learning-Based Wavelength Demodulation System for Multi-Point Distributed Multi-Peak FBG Sensors
Xuan Hou, Sufen Ren, Kebei Yu, Yule Hu, Haoyang Xu, Chenyang Xue,
Shengchao Chen, Guanjun Wang
Optics Express 32 (23), 41297-41313, 2024. [JCR Q1]
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Collaborative Photonic Crystal Fiber Property Optimization: A New Paradigm for Reverse Design
Shengchao Chen, Xinchen Wang, Sufen Ren, Jianli Yang, Yaqian Zhang, Guanjun Wang
IEEE Photonics Technology Letters 35 (19), 1035-1038, 2023. [JCR Q2]
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Efficient Calculation of Optical Properties of Suspended-Core Fiber via a Machine Learning Algorithm
Shuyu Yuan*,
Shengchao Chen*, Jianli Yang, Qian Yang, Sufen Ren, Guanjun Wang, Benguo Yu
Applied Optics 61 (19), 5714-5721, 2022. [JCR Q2]
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Fabry-Perot Interferometric Sensor Demodulation System Utilizing Multi-Peak Wavelength Tracking and Neural Network Algorithm
Shengchao Chen, Feifan Yao, Sufen Ren, Jianli Yang, Qian Yang, Shuyu Yuan, Guanjun Wang, Mengxing Huang
Optics Express 30 (14), 24461-24480, 2022. [JCR Q1]
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Cost-Effective Improvement of the Performance of AWG-Based FBG Wavelength Interrogation via a Cascaded Neural Network
Shengchao Chen, Feifan Yao, Sufen Ren, Guanjun Wang, Mengxing Huang
Optics Express 30 (5), 7647-7663, 2022. [JCR Q1]
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Reconstruction of Fabry-Perot Interferometric Sensor Spectrum from Extremely Sparse Sampling Points Using Dense Neural Network
Shengchao Chen, Sufen Ren, Jianli Yang, Feifan Yao, Qian Yang, Lu Wang, Guanjun Wang, Mengxing Huang
IEEE Photonics Technology Letters 34 (24), 1337-1340, 2022. [JCR Q2]
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Awards & Honors
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AAII Best Student Paper Award – 1 of 3 awarded annually, top 1.5% of ~200 AAII PhD students (UTS)
2025
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Outstanding Master's Thesis (Provincial) – Top 0.05% provincewide
2025
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National Scholarship – Top 0.1% nationally, 1/1,218 (Ministry of Education, China)
2022
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Outstanding Master's Thesis – 1st of 3 recipients, top 1.4% of 210 in cohort
2023
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Outstanding Graduates – Ranked 1st in college
2023
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Outstanding Graduate Student – Ranked 1st in college
2022
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Academia Services
Associate Editor
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JESIT, Journal of Electrical Systems and Information Technology.
Area Chair
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IJCNN, International Joint Conference on Neural Networks.
Conference Reviewer / PC Member
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NeurIPS, Neural Information Processing Systems [Core A*].
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ICML, International Conference on Machine Learning [Core A*].
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ICLR, International Conference on Learning Representations [Core A*].
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AAAI, AAAI Conference on Artificial Intelligence [Core A*].
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IJCAI, International Joint Conference on Artificial Intelligence [Core A*].
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CVPR, Computer Vision and Pattern Recognition [Core A*].
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ECCV, European Conference on Computer Vision [Core A*].
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MICCAI, Medical Image Computing and Computer Assisted Intervention [Core A].
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KDD, ACM SIGKDD Conference on Knowledge Discovery and Data Mining [Core A*].
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ECAI, European Conference on Artificial Intelligence [Core A].
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ICASSP, IEEE Int. Conf. on Acoustics, Speech and Signal Processing [Core B].
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ICME, IEEE Int. Conf. on Multimedia and Expo [Core A].
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ICCV, International Conference on Computer Vision [Core A*].
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WWW, The Web Conference [Core A*].
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MM, ACM International Conference on Multimedia [Core A*].
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WSDM, ACM International Conference on Web Search and Data Mining [Core A].
Journal Reviewer
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JMLR, Journal of Machine Learning Research.
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Machine Learning, Machine Learning (Springer).
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TPAMI, IEEE Transactions on Pattern Analysis and Machine Intelligence.
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TNNLS, IEEE Transactions on Neural Networks and Learning Systems.
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TKDE, IEEE Transactions on Knowledge and Data Engineering.
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TGRS, IEEE Transactions on Geoscience and Remote Sensing.
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TETC, IEEE Transactions on Emerging Topics in Computing.
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KBS, Knowledge-Based Systems.
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AIM, Artificial Intelligence in Medicine.
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Information Systems, Information Systems (Elsevier).
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Computer Networks, Computer Networks (Elsevier).
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TMI, IEEE Transactions on Medical Imaging.
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TDSC, IEEE Transactions on Dependable and Secure Computing.
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TCE, IEEE Transactions on Consumer Electronics.
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TII, IEEE Transactions on Industrial Informatics.
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TMLR, Transactions on Machine Learning Research.
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