Scholar
Trong Nghia Hoang
Google Scholar ID: E-kZZeQAAAAJ
Assistant Professor, Washington State University
Machine Learning
Federated Learning
Meta Learning
Model Fusion
Gaussian Processes
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Citations & Impact
All-time
Citations
2,230
H-index
20
i10-index
29
Publications
20
Co-authors
58
list available
Contact
Email
hoangtrongnghia87@gmail.com
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Publications
13 items
Diffusion-Inspired Reconfiguration of Transformers for Uncertainty Calibration
2026
Cited
0
Federated Prompt-Tuning with Heterogeneous and Incomplete Multimodal Client Data
2026
Cited
1
Leveraging Soft Prompts for Privacy Attacks in Federated Prompt Tuning
arXiv.org · 2026
Cited
0
ForeSWE: Forecasting Snow-Water Equivalent with an Uncertainty-Aware Attention Model
2025
Cited
0
Learning Reconfigurable Representations for Multimodal Federated Learning with Missing Data
2025
Cited
0
Expressive and Scalable Quantum Fusion for Multimodal Learning
2025
Cited
0
ROOT: Rethinking Offline Optimization as Distributional Translation via Probabilistic Bridge
2025
Cited
0
Boosting Offline Optimizers with Surrogate Sensitivity
International Conference on Machine Learning · 2025
Cited
2
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Resume (English only)
Academic Achievements
Multiple papers accepted at top-tier venues including NeurIPS, ICML, ICCV, UAI, AAAI, and IEEE Transactions on Computers
NeurIPS-25 Spotlight: 'Rethinking Offline Optimization as Distributional Translation via Probabilistic Bridge' (led by PhD student Hung Tran and undergraduate Cuong Dao)
NeurIPS-25: 'Learning Reconfigurable Representations for Multimodal Federated Learning with Missing Data' (led by Duong Nguyen)
ICCV-25: 'Federated Prompt-Tuning with Heterogeneous and Incomplete Multimodal Client Data' (led by Hang Phung and Duong Nguyen)
IEEE Transactions on Computers: 'Federated Learning with Sparse and Scarce Data' (led by Hung Nguyen)
NeurIPS-24: 'Probabilistic Federated Prompt-Tuning' (led by PhD student Pei-Yau Weng)
NeurIPS-24: 'Incorporating Surrogate Gradient Norm to Improve Offline Optimization Techniques' (led by undergraduate Cuong Dao)
ICML-24: 'Boosting Offline Optimizers with Surrogate Sensitivity' (led by Cuong Dao)
ICML-24: 'Learning Surrogates for Offline Black-Box Optimization via Gradient Matching' (led by PhD student Azza Fadhel and collaborator Minh Hoang)
UAI-24: 'Revisting Kernel Attention with Correlated Gaussian Process Representation' (led by PhD student Long Bui)
Delivered tutorials on 'Advances in Robust Time-Series ML' at AAAI-24 and 'Black-Box Optimization with Offline Datasets' at AAAI-26
Co-authors
58 total
Bryan Kian Hsiang Low
Associate Professor (with tenure), Department of Computer Science, National University of Singapore
Kristjan Greenewald
Senior Research Scientist and Manager, MIT-IBM Watson AI Lab, IBM Research
Soumya Ghosh
MIT-IBM Watson AI Lab, IBM Research
Quang Minh Hoang
Carnegie Mellon University
Mikhail Yurochkin
Staff AI Scientist, IFM MBZUAI, ex MIT-IBM Watson AI Lab
Patrick Jaillet
Dugald C. Jackson Professor, EECS, MIT
Mayank Agarwal
Senior Research Engineer, IBM Research
Co-author 8
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