Yonggang Wen
Professor
Works on physics-informed machine learning, digital twins for critical infrastructure, and AI data-centre and large-scale training systems.
Yonggang Wen's lab at NTU works on efficient training & inference, distributed, cloud & edge systems and data management & big data. 60 papers since 2023, 19 at top venues, mostly TPAMI and AAAI. 7 PhD students and 2 master's students. 15 alumni, most often to Huawei and SenseTime.
At a glance
- papers, 2023–2026
- 16/ year
- at T1 venues
- 32%
- PhD students
- 7
- MS students
- 2
- alumni listed
- 15
Papers by yearfrom DBLP, 2023–2026
- 13 papers2026 · T1 3 · collecting
- 9 papers2025 · T1 3
- 17 papers2024 · T1 5
- 21 papers2023 · T1 8
T1 venuesOtherVenues: TPAMI, AAAI, TKDE, ACL, ACM MM
Research focuspaper titles that use each topic's words
- Efficient training & inference15 papers
- Data management & big data15 papers
- Distributed, cloud & edge systems3 papers
- physics-informed machine0 papers
- training systems0 papers
Paper list
From DBLP.
202613 papers
- IEEE Commun. Surv. TutorialsA Survey on Intelligent Predictive Maintenance (IPdM) in the Era of Fully Connected Intelligence (opens in a new tab)
- IEEE Internet Things J.Advancing Generative Artificial Intelligence and Large Language Models for Demand Side Management With Internet of Electric Vehicles (opens in a new tab)
- ACM Trans. Internet ThingsChatDC: Geometric-aware Data Center Digital Twin Generation via Large Language Models (opens in a new tab)
- ICCPSDCoPilot: Generative AI-Empowered Policy Adaptation for Dynamic Data Center Operations (opens in a new tab)
- ICLR (T1)DSA: Efficient Inference For Video Generation Models via Distributed Sparse Attention (opens in a new tab)
- SPEfficient Fuzzy Private Set Intersection from Secret-Shared OPRF (opens in a new tab)
- IEEE Netw.Generative AI in Data Center Networking: Fundamentals, Perspectives, and Case Study (opens in a new tab)
- IEEE Internet Things J.Knowledge-Aware Modeling With Frequency-Adaptive Learning for Battery Health Prognostics (opens in a new tab)
- TPAMI (T1)Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities (opens in a new tab)
- AAAI (T1)Physics-Informed Multi-Task Learning for Battery State of Health Prediction with Uncertainty Quantification (opens in a new tab)
- e-EnergyPhythesis: Physics-Guided Evolutionary Scene Synthesis for Energy-Efficient Data Center Design via LLMs (opens in a new tab)
- ICSSPPO: Making Million-Token LLM Training Practical on Modest GPU Clusters (opens in a new tab)
20259 papers
- IEEE Trans. Sustain. Comput.Adaptive Capacity Provisioning for Carbon-Aware Data Centers: A Digital Twin-Based Approach (opens in a new tab)
- IJCV (T1)ADEM-VL: Adaptive and Embedded Fusion for Efficient Vision-Language Tuning (opens in a new tab)
- TPAMI (T1)Aligning Text-to-Image Diffusion Models With Constrained Reinforcement Learning (opens in a new tab)
- IEEE Trans. ComputersCoFormer: Collaborating With Heterogeneous Edge Devices for Scalable Transformer Inference (opens in a new tab)
- IEEE Trans. Neural Networks Learn. Syst.Federated Learning With Only Positive Labels by Exploring Label Correlations (opens in a new tab)
- IEEE Trans. Parallel Distributed Syst.IceFrog: A Layer-Elastic Scheduling System for Deep Learning Training in GPU Clusters (opens in a new tab)
- Nat. Mac. Intell.Learning from models beyond fine-tuning (opens in a new tab)
- MLSys (T1)Rethinking Key-Value Cache Compression Techniques for Large Language Model Serving (opens in a new tab)
- IEEE Internet Comput.Special Issue on Digital Twins (opens in a new tab)
202417 papers
- ICSAutoSched: An Adaptive Self-configured Framework for Scheduling Deep Learning Training Workloads (opens in a new tab)
- NSDI (T1)Characterization of Large Language Model Development in the Datacenter (opens in a new tab)
- ICML (T1)Confronting Reward Overoptimization for Diffusion Models: A Perspective of Inductive and Primacy Biases (opens in a new tab)
- IEEE Trans. Sustain. Comput.Data Center Sustainability: Revisits and Outlooks (opens in a new tab)
- ACM Comput. Surv.Deep Learning Workload Scheduling in GPU Datacenters: A Survey (opens in a new tab)
- IEEE Trans. Dependable Secur. Comput.Exploring the Practicality of Differentially Private Federated Learning: A Local Iteration Tuning Approach (opens in a new tab)
- WWW (T1)FedDSE: Distribution-aware Sub-model Extraction for Federated Learning over Resource-constrained Devices (opens in a new tab)
- ACM Trans. Cyber Phys. Syst.Green Data Center Cooling Control via Physics-guided Safe Reinforcement Learning (opens in a new tab)
- IJCAI (T1)Joint Input and Output Coordination for Class-Incremental Learning (opens in a new tab)
- IWQoSLins: Reducing Communication Overhead of ZeRO for Efficient LLM Training (opens in a new tab)
- IEEE Trans. Neural Networks Learn. Syst.Not All Instances Contribute Equally: Instance-Adaptive Class Representation Learning for Few-Shot Visual Recognition (opens in a new tab)
- ACM Trans. Multim. Comput. Commun. Appl.Personalized Federated Mutual Learning for Unsupervised Camera-Aware Person Re-Identification (opens in a new tab)
202321 papers
- TKDE (T1)A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications (opens in a new tab)
- TPAMI (T1)Automatic Transformation Search Against Deep Leakage From Gradients (opens in a new tab)
- BuildSysChatTwin: Toward Automated Digital Twin Generation for Data Center via Large Language Models (opens in a new tab)
- ACL (T1)Discriminative Reasoning with Sparse Event Representation for Document-level Event-Event Relation Extraction (opens in a new tab)
- IEEE Trans. Neural Networks Learn. Syst.Distributed Energy Trading and Scheduling Among Microgrids via Multiagent Reinforcement Learning (opens in a new tab)
- IEEE Trans. Multim.Editorial (opens in a new tab)
- ICDCS WorkshopsEnhancing Portfolio Performance with Crypto Tokens: a Correlation Network Analysis (opens in a new tab)
- AAAI (T1)FedABC: Targeting Fair Competition in Personalized Federated Learning (opens in a new tab)
- OSDI (T1)Hydro: Surrogate-Based Hyperparameter Tuning Service in Datacenters (opens in a new tab)
- TKDE (T1)Learning Relation Prototype From Unlabeled Texts for Long-Tail Relation Extraction (opens in a new tab)
- ASPLOS (T1)Lucid: A Non-intrusive, Scalable and Interpretable Scheduler for Deep Learning Training Jobs (opens in a new tab)
- ICCV (T1)MAS: Towards Resource-Efficient Federated Multiple-Task Learning (opens in a new tab)
Where alumni went15 listed, 31% to industry
Industry 4Academia 9
Most often to
- Huawei
- SenseTime
Also to
- Beijing Institute of Technology
- Hefei Institute of Technology
- Nanjing Institute of Technology
Apply to NTUFall 2027
Not announced yet
Computing and Data Science PhD
- Round
- Main
- Opens
- —
- GRE
- not required
- English
- TOEFL/IELTS
- Fee
- See program page
Not yet confirmed for this intake.
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