Prof. Truong-Son Hy

Tenure-Track Assistant Professor
Department of Computer Science & Heersink School of Medicine
The University of Alabama at Birmingham, United States

My new website

https://hytruongson.github.io/HySonLab/

Basic Information

Research

HySonLab [website] is my research group. We work on graph neural networks, deep generative models on graphs, multiresolution matrix factorization, graph wavelets, group equivariant and multiscale hierarchical models for the purpose of modeling, learning and generating graphs, hypergraphs, N-Body systems, hierarchical structures and highly symmetric structures in the direction of AI for Science, Bioinformatics, Drug Discovery, Drug Repurposing, and Medical AI.

Doctoral Student Opportunities: HySonLab has a plan to recruit 1 fully-funded PhD position for the Spring 2026. The University of Alabama at Birmingham is an R1 university, the highest level of research universities in the United States. Doctoral program & admission information: [website]. Open PhD positions: [website].

Education

PhD. Computer Science (September 2016 -- June 2022)
The University of Chicago, IL, USA
Thesis: Graph representation learning, deep generative models on graphs, group equivariant molecular neural networks and multiresolution machine learning [PhD-Thesis.pdf].
Advisor: Prof. Risi Kondor [website]

MSc. Computer Science (September 2016 -- December 2018)
The University of Chicago, IL, USA
Thesis: Covariant compositional networks for learning graphs and GraphFlow deep learning framework in C++/CUDA [MSc-Thesis.pdf]
Advisor: Prof. Risi Kondor [website]

BSc. Computer Science (September 2013 -- July 2016)
Eotvos Lorand University, Budapest, Hungary
Thesis: Semi-supervised Adaptive Facial Tracking Method [BSc-Thesis.pdf]
Advisor: Prof. Andras Lorincz [website]
Award: First-class Graduation Honour
Sponsor: Stipendium Hungaricum Full Scholarship from the Government of Hungary

Current Positions

The University of Alabama at Birmingham (August 2024 -- Present)
Tenure-Track Assistant Professor, Department of Computer Science, Birmingham, Alabama, United States [info]
Heersink School of Medicine, University of Alabama at Birmingham (August 2024 -- Present)
Associate Scientist, Center for Clinical and Translational Science (CCTS), Birmingham, Alabama, United States [info]

Past Academic Appointments

Indiana State University (August 2023 -- July 2024)
Tenure-Track Assistant Professor, Department of Mathematics and Computer Science, Terre Haute, Indiana, United States
Porter Cancer Research Center (February 2024 -- July 2024)
Affiliated Faculty, Terre Haute, Indiana, United States
The Center for Genomic Advocacy (February 2024 -- July 2024)
Affiliated Faculty, Terre Haute, Indiana, United States
University of California San Diego (September 2022 -- April 2023)
Postdoctoral Fellow & Lecturer, Halicioglu Data Science Institute, San Diego, California, United States

Industry Experience

Facebook Inc. (June -- August 2020)
PhD Intern, Seattle, WA

Google Inc. (June -- September 2019)
Site Reliability Engineer Intern, Sunnyvale, CA

Google Inc. (June -- September 2018)
Site Reliability Engineer Intern, Sunnyvale, CA

Google Inc. (June -- September 2017)
Software Engineer Intern, Chicago, IL

Selected Publications [Google Scholar] [ORCID]

Conference Proceedings

[C18] Nghia Huynh Nguyen Hieu, Ngoc Son Nguyen, Huynh Nguyen Dang, Thieu Vo, Truong-Son Hy, and Van Nguyen, OZSpeech: One-step Zero-shot Speech Synthesis with Learned-Prior-Conditioned Flow Matching, ACL 2025. [abstract] [paper] [code] [demo]

[C17] Khai Le-Duc, Phuc Phan, Tan-Hanh Pham, Bach Phan Tat, Minh-Huong Ngo, Thanh Nguyen-Tang, Truong-Son Hyc, MultiMed: Multilingual Medical Speech Recognition via Attention Encoder Decoder, ACL 2025. [abstract] [paper] [code] [poster]
c: Corresponding author / PI.

[C16] Khai-Nguyen Nguyen, Khai Le-Duc, Bach Phan Tat, Le Duy, Long Vo-Dang, Truong-Son Hyc, Sentiment Reasoning for Healthcare, ACL 2025. [abstract] [paper] [code] [poster]
c: Corresponding author / PI.

[C15] Khai Le-Duc, David Thulke, Hung-Phong Tran, Long Vo-Dang, Khai-Nguyen Nguyen, Truong-Son Hy, and Ralf Schluter, Medical Spoken Named Entity Recognition, NAACL 2025. [paper] [preprint] [code] [poster]

[C14] Cuong Tran Van, Thanh V. T. Tran, Van Nguyen, and Truong-Son Hyc, Effective Context Modeling Framework for Emotion Recognition in Conversations, ICASSP 2025, DOI 10.1109/ICASSP49660.2025.10888112. [paper] [code] [poster]
c: Corresponding author / PI.

[C13] Co Tran, Quoc-Bao Tran, Truong-Son Hyc, and Thang N. Dinh, Scalable Quantum-Inspired Optimization through Dynamic Qubit Compression, AAAI 2025 (Oral Presentation). [proceedings] [abstract] [preprint] [poster]
c: co-PI.

[C12] Thanh V. T. Tran, Nhat Khang Ngo, Viet Anh Nguyen, and Truong-Son Hyc, GROOT: Effective Design of Biological Sequences with Limited Experimental Data, KDD 2025, Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1., Pages 1385-1396, DOI 10.1145/3690624.3709291. [paper] [preprint] [code]
c: Corresponding author / PI.

[C11] Khai Le-Duc, Khai-Nguyen Nguyen, Long Vo-Dang, and Truong-Son Hyc, Real-time Speech Summarization for Medical Conversations, Interspeech 2024, DOI 10.21437/Interspeech.2024-2250. [paper] [code] [demo]
c: Corresponding author / PI.

[C10] Zhishang Luo, Truong-Son Hy, Puoya Tabaghi, Michael Defferrard, Elahe Rezaei, Ryan Carey, Rhett Davis, Rajeev Jain, and Yusu Wang, DE-HNN: An effective neural model for Circuit Netlist representation, Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4258-4266, 2024. [paper] [abstract] [code] [poster]

[C9] Thuan Trang, Nhat Khang Ngo, Daniel Levy, Thieu N. Vo, Siamak Ravanbakhsh, and Truong-Son Hyc, E(3)-Equivariant Mesh Neural Networks, Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:748-756, 2024. [paper] [abstract] [code] [poster]
c: Corresponding author / PI.

[C8] Minh H. Nguyen, Nghi D. Q. Bui, Truong-Son Hy, Long Tran-Thanh, and Tien N. Nguyen, HierarchyNet: Learning to Summarize Source Code with Heterogeneous Representations, EACL 2024. [paper] [abstract] [code] [talk] [poster] [slides]

[C7] Duc Thien Nguyen*, Manh Duc Tuan Nguyen*, Truong-Son Hy*c, and Risi Kondor, Fast Temporal Wavelet Graph Neural Networks, NeurIPS 2023 (Workshop on Symmetry and Geometry in Neural Representations), Proceedings of Machine Learning Research 228:35-54. [paper] [abstract] [code] [talk] [slides] [poster]
*: Co-first authors.
c: Corresponding author / PI.

Also presented at Temporal Graph Learning Workshop: [paper]

[C6] Chen Cai, Truong-Son Hy, Rose Yu, and Yusu Wang, On the Connection Between MPNN and Graph Transformer, ICML 2023, Proceedings of Machine Learning Research 202:3408-3430. [abstract] [paper] [code] [poster]

[C5] Cong Dao Tran, Nhut Huy Pham, Anh Nguyen, Truong-Son Hyc, and Tu Vu, ViDeBERTa: A powerful pre-trained language model for Vietnamese, EACL 2023. [paper] [abstract] [code] [poster] [talk]
c: Corresponding author / PI.

[C4] Truong-Son Hy, Viet Bach Nguyen, Long Tran-Thanh and Risi Kondor, Temporal Multiresolution Graph Neural Networks For Epidemic Prediction, ICML 2022 (Workshop on Healthcare AI and COVID-19), Proceedings of Machine Learning Research 184:21-32. [abstract] [paper] [code] [talk] [poster]

[C3] Truong-Son Hy and Risi Kondor, Multiresolution Matrix Factorization and Wavelet Networks on Graphs, ICML 2022 (Workshop on Topology, Algebra, and Geometry in Machine Learning), Proceedings of Machine Learning Research 196:172-182. [abstract] [paper] [full paper] [code] [talk] [poster]

[C2] Brandon Anderson, Truong-Son Hy and Risi Kondor, Cormorant: Covariant molecular neural networks, NeurIPS 2019. [abstract] [paper] [code] [poster]

[C1] Risi Kondor, Truong-Son Hy, Horace Pan, Brandon Anderson and Shubhendu Trivedi, Covariant compositional networks for learning graphs, ICLR 2018. [paper] [C++ code] [Python code] [poster]

Journal Publications

[J14] Tam Trinh, Anh Dao, Hy Thi Hong Nhung, and Truong-Son Hyc, VietMedKG: Knowledge Graph and Benchmark for Traditional Vietnamese Medicine, ACM Transactions on Asian and Low-Resource Language Information Processing (Impact Factor = 1.8), Volume 24, Issue 7, Article No.: 69, Pages 1-17, DOI 10.1145/3744740. [paper] [code]
c: Corresponding author / PI.

[J13] Phuc Pham, Viet Thanh Duy Nguyen, Kyu Hong Cho, and Truong-Son Hyc, DrugPipe: Generative AI-assisted Virtual Screening Pipeline for Generalizable and Efficient Drug Repurposing, Biology Methods & Protocols (Q1, Impact Factor = 2.5), Volume 10, Issue 1, DOI 10.1093/biomethods/bpaf038. [paper] [code]
c: Corresponding author / PI.

[J12] Thanh V. T. Tran, Nhat Khang Ngo, Viet Thanh Duy Nguyen, and Truong-Son Hyc, LatentDE: Latent-based Directed Evolution for Protein Sequence Design, Machine Learning: Science and Technology (Q1, Impact Factor = 6.3), Volume 6, Number 1, DOI 10.1088/2632-2153/adc2e2. [paper] [code]
c: Corresponding author / PI.

[J11] Quang-Dung Dinh, Daniel Kunk, Truong-Son Hyc, Vamsi J. Nalam, and Phuong Dao, Machine Learning for Automated Electrical Penetration Graph Analysis of Aphid Feeding Behavior: Accelerating Research on Insect-Plant Interactions, PLOS ONE (Q1, Impact Factor = 2.9, H-index = 435), Volume 20, Number 4, Pages 1-25, DOI 10.1371/journal.pone.0319484. [paper] [code]
c: Corresponding author / PI.

[J10] Viet Thanh Duy Nguyen, Nhan Nguyen, and Truong-Son Hyc, ProteinReDiff: Complex-based ligand-binding proteins redesign by equivariant diffusion-based generative models, Structural Dynamics (Q1, Impact Factor = 2.8), Volume 11, Issue 6, DOI 10.1063/4.0000271. [paper] [code]
c: Corresponding author / PI.

[J9] Khanh-Tung Tran, Truong-Son Hy, Lili Jiang, and Xuan-Son Vu, MGLEP: Multimodal Graph Learning for Modeling Emerging Pandemics with Big Data, Scientific Reports (Q1, Impact Factor = 3.8, H-Index = 315), Volume 14, Number 16377, DOI 10.1038/s41598-024-67146-y. [paper] [code]

[J8] Viet Thanh Duy Nguyen * and Truong-Son Hy*c, Multimodal Pretraining for Unsupervised Protein Representation Learning, Biology Methods & Protocols (Q1, Impact Factor = 3.6), Volume 9, Issue 1, DOI 10.1093/biomethods/bpae043. [paper] [code]
*: Co-first authors.
c: Corresponding author / PI.

[J7] Trong Thanh Tran * and Truong-Son Hy*c, Protein Design by Directed Evolution Guided by Large Language Models, IEEE Transactions on Evolutionary Computation (Q1, Impact Factor = 14.3), vol. 29, no. 2, pp. 418-428, April 2025, DOI 10.1109/TEVC.2024.3439690. [paper] [preprint] [code]
*: Co-first authors.
c: Corresponding author / PI.

[J6] Nhat Khang Ngo* and Truong-Son Hy*c, Multimodal Protein Representation Learning and Target-aware Variational Auto-encoders for Protein-binding Ligand Generation, Machine Learning: Science and Technology (Q1, Impact Factor = 6.8), Volume 5, Number 2, DOI 10.1088/2632-2153/ad3ee4. [paper] [code]
*: Co-first authors.
c: Corresponding author / PI.

Presented at NeurIPS 2023 (Machine Learning for Structural Biology & Generative AI and Biology Workshops): [paper] [poster]

[J5] Thuan Nguyen Anh Trang, Khang Nhat Ngo, Hugo Sonnery, Thieu Vo, Siamak Ravanbakhsh, Truong-Son Hyc, Scalable Hierarchical Self-Attention with Learnable Hierarchy for Long-Range Interactions, Transactions on Machine Learning Research (TMLR). [paper] [pdf] [code] [talk]
c: Corresponding author / PI.

[J4] Thong Bach, Anh Tong, Truong-Son Hy, Vu Nguyen, and Thanh Nguyen-Tang, Long-Tailed Visual Recognition with Global Contrastive Learning and Prototype Learning, Transactions on Machine Learning Research (TMLR). [paper] [code]

[J3] Nhat Khang Ngo*, Truong-Son Hy*c, and Risi Kondor, Multiresolution Graph Transformers and Wavelet Positional Encoding for Learning Long-Range and Hierarchical Structures, Journal of Chemical Physics (Q1, Impact Factor = 4.4), Volume 159, Issue 3, DOI 10.1063/5.0152833. [html] [paper] [code]
*: Co-first authors.
c: Corresponding author / PI.

Presented as a spotlight at ICML 2023 (Workshop on Computational Biology): [paper] [poster] [slides]

[J2] Truong-Son Hy and Risi Kondor, Multiresolution Equivariant Graph Variational Autoencoder, Machine Learning: Science and Technology (Q1, Impact Factor = 6.8), Volume 4, Number 1, DOI 10.1088/2632-2153/acc0d8. [paper] [code]

Presented at ICML 2022 (AI for Science Workshop): [paper] [talk] [poster]

[J1] Truong-Son Hy, Shubhendu Trivedi, Horace Pan, Brandon M. Anderson and Risi Kondor, Predicting molecular properties with covariant compositional networks, Journal of Chemical Physics (Q1, Impact Factor = 4.4), Volume 148, Issue 24, DOI 10.1063/1.5024797. [paper] [C++ code] [Python code]

Workshop Paper Presentations

[W11] Duy Do, Truong-Son Hyc, and Thang Dinh, RELIC: Reinforcement Learning Based Ising Optimization via Graph Compression, IEEE International Conference on Quantum Computing and Engineering (QCE25 QCRL Workshop).
c: co-PI.

[W10] Tien Dang, Viet Thanh Duy Nguyen, Minh Tuan Le, and Truong-Son Hyc, Multimodal Contrastive Representation Learning in Augmented Biomedical Knowledge Graphs, BIOKDD 2025: 24th International Workshop on Data Mining in Bioinformatics. [paper] [code] [poster]
c: Corresponding author / PI.

[W9] Tan-Hanh Pham, Bui Trong Duong, Luu Quang Minh, Pham Tan Huong, Chris Ngo, and Truong-Son Hyc, SilVar-Med: A Speech-Driven Visual Language Model for Explainable Abnormality Detection in Medical Imaging, CVPR 2025 (Multimodal Algorithmic Reasoning Workshop). [paper] [preprint] [code] [slides] [poster]
c: Corresponding author / PI.

[W8] Viet Anh Nguyen, Nhat Khang Ngo, and Truong-Son Hyc, Range-aware Positional Encoding via High-order Pretraining: Theory and Practice, NeurIPS 2024 (Workshop on Symmetry and Geometry in Neural Representations). [paper] [abstract] [code] [poster]
c: Corresponding author / PI.

[W7] Thanh V. T. Tran, Nhat Khang Ngo, Viet Thanh Duy Nguyen, and Truong-Son Hyc, LatentDE: Latent-based Directed Evolution accelerated by Gradient Ascent for Protein Sequence Design, NeurIPS 2024 (AI for Accelerated Materials Design). [paper] [code] [poster]
c: Corresponding author / PI.

Also presented at other workshops of NeurIPS 2024: [W6] Khai-Nguyen Nguyen, Khai Le-Duc, Bach Phan Tat, Le Duy, Jerry Ngo, Long Vo-Dang, Anh Totti Nguyen, and Truong-Son Hyc, Sentiment Reasoning for Healthcare, NeurIPS 2024 (Advancements In Medical Foundation Models: Explainability, Robustness, Security, and Beyond). [paper]
c: Corresponding author / PI.

[W5] Quang Pham Phuoc Minh, Tiet Nguyen Khoi Nguyen, Lan Chi Ngo, Tho Truong Do, and Truong-Son Hyc, ESGNN: Towards Equivariant Scene Graph Neural Network for 3D Scene Understanding, 2024 33rd IEEE International Conference on Robot and Human Interactive Communication. [paper] [poster]
c: Corresponding author / PI.

[W4] Hugo Sonnery, Thuan Trang, Thieu N. Vo, Siamak Ravanbakhsh, and Truong-Son Hyc, Sequoia: Hierarchical Self-Attention Layer with Sparse Updates for Point Clouds and Long Sequences, ICLR 2023 (Workshop on Sparsity in Neural Networks). [paper] [code] [poster]
c: Corresponding author / PI.

[W3] Viet Bach Nguyen*, Truong-Son Hy*c, Long Tran-Thanh, and Nhung Nghiem, Predicting COVID-19 pandemic by spatio-temporal graph neural networks: A New Zealand's study, NeurIPS 2023 (Temporal Graph Learning Workshop). [paper] [long paper] [code] [talk] [poster]
*: Co-first authors.
c: Corresponding author / PI.

[W2] Nhat Khang Ngo*, Truong-Son Hy*c, and Risi Kondor, Predicting Drug-Drug Interactions using Deep Generative Models on Graphs, NeurIPS 2022 (AI for Science Workshop). [paper] [code] [poster]
*: Co-first authors.
c: Corresponding author / PI.

[W1] Yanan Long, Horace Pan, Chao Zhang, Truong-Son Hy, Risi Kondor, and Andrey Rzhetsky, Molecular Fingerprints Are a Simple Yet Effective Solution to the Drug-Drug Interaction Problem, ICML 2022 (Workshop on Computational Biology). [paper] [talk]

Preprints & Under Review

[P24] Tam Trinh, Manh Nguyen, and Truong-Son Hyc, Towards Robust Fact-Checking: A Multi-Agent System with Advanced Evidence Retrieval, 2025. [paper] [code]
c: Corresponding author / PI.

[P23] Nguyen Phu Vinh, Anh Chung Hoang, Chris Ngo, and Truong-Son Hyc, Repeton: Structured Bug Repair with ReAct-Guided Patch-and-Test Cycles, 2025. [paper] [code]
c: Corresponding author / PI.

[P22] Tan-Hanh Pham, Phu-Vinh Nguyen, Dang The Hung, Bui Trong Duong, Vu Nguyen Thanh, Chris Ngo, Tri Quang Truong, and Truong-Son Hyc, IQBench: How "Smart'' Are Vision-Language Models? A Study with Human IQ Tests, 2025. [paper] [code]
c: Corresponding author / PI.

[P21] Luu Tung Hai, Thinh D. Le, Zhicheng Ding, Qing Tian, and Truong-Son Hyc, Topology-Guided Knowledge Distillation for Efficient Point Cloud Processing, 2025. [paper] [code]
c: Corresponding author / PI.

[P20] Tien Dang and Truong-Son Hyc, EquiHGNN: Scalable Rotationally Equivariant Hypergraph Neural Networks, 2025. [paper] [code]
c: Corresponding author / PI.

[P19] Tung D. Vu, Chung Hoang, and Truong-Son Hyc, Multimodal graph representation learning for website generation based on visual sketch, 2025. [paper] [code]
c: Corresponding author / PI.

[P18] Quy-Anh Dang, Chris Ngo, and Truong-Son Hyc, RainbowPlus: Enhancing Adversarial Prompt Generation via Evolutionary Quality-Diversity Search, 2025. [paper] [code]
c: Corresponding author / PI.

[P17] Viet Thanh Duy Nguyen, and Truong-Son Hyc, Advances in Protein Representation Learning: Methods, Applications, and Future Directions, 2025. [paper]
c: Corresponding author / PI.

[P16] Tuan-Anh Yang, Truong-Son Hyc, and Phuong D. Dao, MOB-GCN: A Novel Multiscale Object-Based Graph Neural Network for Hyperspectral Image Classification, 2025. [paper] [code]
c: Corresponding author / PI.

[P15] Cong Nga Ha, Phuc Pham, and Truong-Son Hyc, LANTERN: Leveraging Large Language Models and Transformers for Enhanced Molecular Interactions, DOI 10.1101/2025.02.10.637522. [paper] [code]
c: Corresponding author / PI.

[P14] Minh Ngoc Nguyen, Khai Le-Duc, Tan-Hanh Pham, Trang Nguyen, Quang Minh Luu, Ba Kien Tran, Truong-Son Hy, Viktor Dremin, Sergei Sokolovsky, and Edik Rafailov, A Wearable Device Dataset for Mental Health Assessment Using Laser Doppler Flowmetry and Fluorescence Spectroscopy Sensors, 2024. [paper] [code]

[P13] Van Quang Nguyen, Quoc Chuong Nguyen, Thu Huong Dang, and Truong-Son Hyc, Hybridising Reinforcement Learning and Heuristics for Hierarchical Directed Arc Routing Problems, 2024. [paper] [code]
c: Corresponding author / PI.

[P12] Tan-Hanh Pham, Hoang-Nam Le, Phu-Vinh Nguyen, Chris Ngo, and Truong-Son Hyc, SilVar: Speech Driven Multimodal Model for Reasoning Visual Question Answering and Object Localization, 2024. [paper] [code]
c: Corresponding author / PI.

[P11] Quang Dung Dinh, Daniel Kunk, Truong-Son Hyc, Vamsi J Nalam, and Phuong Dao, DiscoEPG: A Python package for characterization of insect electrical penetration graph (EPG) signals, DOI 10.1101/2024.12.05.627099. [paper] [code]
c: Corresponding author / PI.

[P10] Quang P. M. Pham, Khoi T. N. Nguyen, Lan C. Ngo, Dezhen Song, Truong Do, and Truong-Son Hyc, TESGNN: Temporal Equivariant Scene Graph Neural Networks for Efficient and Robust Multi-View 3D Scene Understanding, 2024. [paper] [code]
c: Corresponding author / PI.

[P9] Viet Anh Nguyen, Nhat Khang Ngo, and Truong-Son Hyc, Range-aware Positional Encoding via High-order Pretraining: Theory and Practice, 2024. [paper] [code]
c: Corresponding author / PI.

[P8] Viet Tien Pham, Minh Hieu Ha, Bao V. Q. Bui and Truong-Son Hyc, LightMed: A Light-weight and Robust FFT-Based Model for Adversarially Resilient Medical Image Segmentation, DOI 10.1101/2024.09.28.615584, 2024. [paper] [code]
c: Corresponding author / PI.

[P7] Khai Le-Duc, Quy-Anh Dang, Tan-Hanh Pham, and Truong-Son Hyc, wav2graph: A Framework for Supervised Learning Knowledge Graph from Speech, 2024. [paper] [code]
c: Corresponding author / PI.

[P6] Khai Le-Duc, Ryan Zhang, Ngoc Son Nguyen, Tan-Hanh Pham, Anh Dao, Ba Hung Ngo, Anh Totti Nguyen, and Truong-Son Hyc, LiteGPT: Large Vision-Language Model for Joint Chest X-ray Localization and Classification Task, 2024. [paper] [code]
c: Corresponding author / PI.

[P5] Cong Dao Tran*, Thong Bach*, and Truong-Son Hy*c, Symmetry-preserving graph attention network to solve routing problems at multiple resolutions, 2023. [paper] [code]
*: Co-first authors.
c: Corresponding author / PI.

[P4] Truong-Son Hy and Cong Dao Tran, Graph Attention-based Deep Reinforcement Learning for solving the Chinese Postman Problem with Load-dependent costs, 2023. [paper] [code]

[P3] Ngoc-Dung Do*, Truong-Son Hy*c and Duy Khuong Nguyen, Sparsity exploitation via discovering graphical models in multi-variate time-series forecasting, 2023. [paper] [code]
*: Co-first authors.
c: Corresponding author / PI.

[P2] Erik Henning Thiede, Truong-Son Hy and Risi Kondor, The general theory of permutation equivarant neural networks and higher order graph variational encoders, 2020. [paper] [code]

[P1] Truong-Son Hy and Chris Jones, Graph neural networks with efficient tensor operations in CUDA/GPU and GraphFlow deep learning framework in C++ for quantum chemistry, 2019. [paper] [code]

PhD Students

At University of Alabama at Birmingham, I am grateful to advise talented and hard-working PhD students:

PhD Committee

It is my honor to serve in the PhD committee of: At University of Alabama at Birmingham, I am serving in the PhD committee for junior PhD students:

Organizer & Area Chair

With other colleagues, I co-organize and am a senior meta-reviewer, i.e. area chair, for the following workshops / conferences:

Reviewer

Journals (for records: [ORCID])
  1. Nature - Scientific Reports [Certificate - 01/26/25] [Certificate - 02/24/25]
  2. Computational and Structural Biotechnology Journal (Elsevier) [Certificate]
  3. Neural Networks (Elsevier) [Certificate]
  4. International Journal of Biological Macromolecules (Elsevier) [Certificate]
  5. Information Fusion (Elsevier) [Certificate]
  6. Computer Vision and Image Understanding (Elsevier) [Certificate]
  7. Information Processing and Management (Elsevier) [Certificate]
  8. Knowledge-Based Systems (Elsevier) [Certificate]
  9. Expert Systems With Applications (Elsevier) [Certificate]
  10. Engineering Applications of Artificial Intelligence (Elsevier) [Certificate]
  11. BMC Biology (Springer Nature) [Certificate]
  12. BMC Bioinformatics (Springer Nature) [Certificate]
  13. Molecular Diversity (Springer Nature) [Certificate]
  14. Discover Artificial Intelligence (Springer Nature) [Certificate]
  15. npj Drug Discovery (Springer Nature) [Certificate]
  16. Quantum Machine Intelligence (Springer Nature) [Certificate]
  17. Nature - Communications Biology (Springer Nature)
  18. Machine Learning (Springer Nature)
  19. PLOS Computational Biology
  20. SIAM Journal on Matrix Analysis and Applications
  21. IEEE Journal of Biomedical and Health Informatics
  22. IEEE Transactions on Computational Biology and Bioinformatics
  23. IEEE Transactions on Multimedia
  24. ACM Transactions on Knowledge Discovery from Data
  25. National Science Review (Oxford University Press)
  26. Biology Methods and Protocols (Oxford University Press)
  27. Advanced Science (Wiley)
  28. ACS Omega (American Chemical Society)
  29. International Journal of Public Health (Frontiers Media)
  30. Frontiers in Public Health (Frontiers Media)
  31. Machine Learning: Science and Technology (IOP Publishing)
  32. Physica Scripta (IOP Publishing)
  33. Journal of Machine Learning Research (JMLR)

Conferences
  1. NeurIPS: 2025, 2024, 2023, 2022, 2021
  2. CVPR: 2025
  3. ICCV: 2025
  4. WACV: 2026
  5. ICML: 2022
  6. ICLR: 2025, 2024
  7. AISTATS: 2025, 2024
  8. AAAI: 2026, 2025, 2024, 2023
  9. KDD: 2025, 2024
  10. BIO KDD: 2025
  11. Learning on Graphs (LoG): 2023, 2022
  12. EMNLP: 2025, 2023
  13. ACL: 2025, 2024
  14. NAACL: 2025
  15. IEEE ROMAN: 2024
  16. ICASSP: 2025 [Certificate]

Software [HySonLab] [HyTruongSon]

38. FactAgent [repo]: A sophisticated multi-agent fact-checking system that combines advanced evidence retrieval techniques to verify factual claims across diverse domains.

37. MatCPP [repo]: Efficient Matheuristics for Solving the Chinese Postman Problem with Load Constraints.

36. PointDistill [repo]: Topology-Guided Knowledge Distillation for Efficient Point Cloud Processing.

35. EquiHGNN [repo]: Rotationally Equivariant HyperGraph Neural Networks.

34. Design2Code [repo]: Multimodal graph representation learning for website source code generation given visual sketch.

33. WaveletPE [repo]: Range-aware Graph Positional Encoding via High-order Pretraining.

32. LANTERN [repo]: Leveraging Large Language Models and Transformers for Enhanced Molecular Interactions.

31. MOB-GCN [repo]: Multiscale Object-Based Graph Neural Network for Hyperspectral Image Segmentation and Classification.

30. BioMedKG [repo]: Multimodal Contrastive Representation Learning in Augmented Biomedical Knowledge Graphs.

29. ArcRoute [repo]: Hybrid algorithm combining Reinforcement Learning (RL) and heuristics to solve Hierarchical Directed Capacitated Arc Routing Problem (HDCARP).

28. DrugPipe [repo]: Generative AI-assisted Drug Repurposing Pipeline.

27. TESGNN [repo]: 3D Temporal Equivariant Scene Graph Neural Networks.

26. LightMed [repo]: A Light-weight and Robust FFT-Based Model for Adversarially Resilient Medical Image Segmentation.

25. EntityKG [repo]: A Framework for Supervised Learning Knowledge Graph from Speech.

24. VietMedKG [repo]: Knowledge Graph and Benchmark for Traditional Vietnamese Medicine.

23. ML4Insects [repo]: A library for EPG signal analysis of pierce-sucking insects.

22. Hierarchical Attention [repo]: Scalable Hierarchical Self-Attention with Learnable Hierarchy for Long-Range Interactions (TMLR).

21. EquiMesh [repo]: E(3)-Equivariant Mesh Neural Networks (AISTATS 2024).

20. Protein-Redesign [repo]: Complex-based Ligand-Binding Proteins Redesign by Equivariant Diffusion-based Generative Models.

19. LatentDE [repo]: Latent-based Directed Evolution guided by Gradient Ascent for Protein Design.

18. Protein-Pretrain [repo]: Multimodal Pretraining for Unsupervised Protein Representation Learning.

17. Protein-Design [repo]: Protein Design by Machine Learning guided Directed Evolution.

16. Multires-NP-hard [repo]: Symmetry-preserving and multiresolution Reinforcement Learning to solve NP-hard problems in Operations Research including TSP and VRP.

15. CPP-LC [repo]: Implementation in C++ for the Chinese postman problem with load constraints (CPP-LC) with Evolutionary Algorithm, Ant Colony Optimization and many other meta-heuristics.

14. Ligand generation [repo]: Target-aware Variational Auto-encoders for Ligand Generation with Multimodal Protein Representation Learning.

13. GraphLASSO [repo]: Sparsity exploitation via discovering graphical models in multi-variate time-series forecasting.

12. Machine Learning for Epidemiology [repo]: Predicting COVID-19 pandemic by spatio-temporal graph neural networks.

11. Multiresolution Graph Transformers [repo]: Learning hierarchical structures including proteins, peptides, and polymers by multiresolution graph transformers and wavelet positional encoding.

10. TWGNN [repo]: Fast Temporal Wavelet Graph Neural Networks for learning timeseries with underlying graph structure with applications in traffic prediction and brain networks.

9. ViDeBERTa [repo]: A powerful pre-trained language model for Vietnamese (EACL 2023).

8. Drugs-Proteins knowledge graph [repo]: Large-scale deep generative models on multi-modal knowledge graph for predicting drug interactions.

7. Spherical CNNs [repo]: PyTorch implementation of Spherical Convolutional Neural Networks with Clebsch-Gordan transform for nonlinearity in the Fourier space.

6. Learnable MMF [repo]: Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs.

5. MGVAE [repo]: Multiresolution Equivariant Graph Variational Autoencoder (MGVAE) and Multiresolution Graph Networks (MGN) for supervised molecular properties prediction, unsupervised molecular representation learning, graph generation, citation link prediction and graph-based image generation.

4. LibCCNs [repo]: Covariant Compositional Networks Library is an easy-to-use and efficient implementation of Covariant Compositional Networks (CCNs) with TensorFlow and PyTorch's APIs based on a shared common C++ core.

3. Invariant Graph Networks [repo]: A PyTorch implementation of the Invariant and Equivariant Graph Networks.

2. GraphFlow [repo]: Deep Learning framework built from scratch in C++/CUDA that supports symbolic/automatic differentiation, dynamic computation graphs, tensor/matrix operations accelerated by GPU and implementations of various state-of-the-art graph neural networks and other Machine Learning models.

1. Fourier Transform Library [repo]: FFT 1D/2D, DFT 1D/2D, DCT 1D/2D, JPEG image compression, etc.

Media

Invited Talks

16. Adobe Research
Talk: Geometric Deep Learning: From 3D Point Clouds and Meshes to Scene Understanding and Distillation.
Host: Dr. Viet Lai.
Date: August 21, 2025

15. Department of Computer Science and Electronics at Universitas Gadjah Mada (DCSE UGM), Indonesia [invitation] [certificate]
Talk: Generative AI & Geometric Deep Learning for Protein Science and Drug Discovery.
Host: Dr. Muhammad Husni Santriaji.
Date: July 29, 2025

14. Robotics & AI Expert Talk [certificate]
Talk: Generative AI & Geometric Deep Learning for Protein Science and Drug Discovery.
Host: Dr. Tan-Hanh Pham, Harvard Medical School.
Date: July 18, 2025

13. UAB Department of Mechanical and Materials Engineering
Talk: Geometric Deep Learning for Protein Science and Drug Discovery.
Host: Prof. Mark Banaszak Holl.
Date: January 24, 2025

12. University of Alabama at Birmingham
Talk: Geometric Deep Learning for Protein Science and Drug Discovery.
Host: Prof. Ragib Hasan.
Date: May 15, 2024

11. University of Massachusetts Boston
Talk: Geometric Deep Learning for Protein Science and Drug Discovery.
Host: Prof. Albert Kao.
Date: April 11, 2024

10. VinUniversity
Talk: Graph representation learning and Deep generative models on graphs.
Host: Prof. Le Duy Dung (Andrew).
Date: December 28, 2023

9. Indiana State University
Talk: Graph representation learning and Deep generative models on graphs.
Host: Prof. Arash Rafiey.
Date: February 1, 2023

8. Virginia Commonwealth University
Talk: Graph representation learning and Deep generative models on graphs. [flyers]
Host: Prof. Thang Dinh.
Date: September 30, 2022

7. Le Quy Don Technical University (Military Technical Academy)
Talk: Graph representation learning and Deep generative models on graphs.
Host: Faculty of Information Technology.
Date: September 8, 2022

6. FPT Software
Talk: Graph representation learning and Deep generative models on graphs. [youtube]
Host: FPT AI Center.
Date: June 2, 2022

5. Vector Institute for Artificial Intelligence
Talk: Graph representation learning and Deep generative models on graphs.
Host: Prof. Pascal Poupart.
Date: April 6, 2022

4. University of California San Diego
Talk: Graph representation learning and Multiresolution machine learning.
Host: Prof. Rose Yu, Prof. Yusu Wang.
Date: February 24, 2022

3. California Institute of Technology
Talk: Graph representation learning, deep generative models on graphs and multiresolution machine learning.
Host: Prof. Anima Anandkumar.
Date: February 3, 2022

2. University of Illinois Chicago
Talk: Graph representation learning and Deep generative models on graphs [link]
Host: Department of Mathematics, Statistics, and Computer Science.
Date: January 26, 2022

1. Argonne National Laboratory
Talk: Graph representation learning, deep generative models on graphs and multiresolution machine learning [link]
Host: Dr. Stefan Wild, Dr. Emil Constantinescu.
Date: January 5, 2022

Senior Collaborators

Professional Memberships

Teaching Assistant at University of Chicago

9. CAPP 30271 - Mathematics for Computer Science and Data Analysis (Winter 2022)
8. MPCS 53112 - Advanced Data Analytics (Autumn 2021)
7. CMSC 25025 - Machine Learning & Large-Scale Data Analysis (Spring 2021)
6. CMSC 35400 - Machine Learning (Winter 2021)
5. CMSC 25025 - Machine Learning & Large-Scale Data Analysis (Spring 2019)
4. CMSC 15100 - Introduction to Computer Science I (Autumn 2018)
3. MPCS 53111 - Machine Learning (Spring 2017)
2. CMSC 25400 - Machine Learning (Winter 2017)
1. CMSC 22600 - Compilers for Computer Languages (Autumn 2016)

Scientific Discussions

Discussions in 2024: [dir]
Discussions in 2023: [dir]
Discussions in 2022: [dir]
Discussions in 2021: [dir]
Discussions in 2020: [dir]
Discussions in 2019: [dir]
Discussions in 2018: [dir]

Qualifications

Programming Languages: C/C++ , Java, Python, Matlab, Haskell, Ada, Pascal, SQL, PL/SQL, HTML/CSS.
Libraries: TensorFlow, PyTorch, STL, OpenGL, LaTeX.
Tools: Vim, Netbeans, Eclipse, Codeblocks, Dev-C++, Microsoft Visual Studio, Microsoft Office.

Contact Information

Mail: University of Alabama at Birmingham
Department of Computer Science
University Hall, Room 4149
1402 10th Ave. S.
Birmingham, AL 35294
USA
Office Telephone: (+1) 205-934-8604
Email: thy AT uab DOT edu
Web: http://people.cs.uchicago.edu/~hytruongson