Education
- Ph.D. in Electrical and Electronic Engineering, RMIT University, Vietnam (July 2025 – Present)
- M.S. in Computer Science (Data Science), University of Washington, Seattle, WA (Sep 2022 – Jun 2024)
- B.S. in Computer Science (Data Science), University of Washington, Seattle, WA (Sep 2020 – Jun 2022)
- A.S. in Computer Science, Seattle Central College, Seattle, WA (Jan 2019 – Jun 2020)
Work experience
Visiting Lecturer, Asia University, Ho Chi Minh City, Vietnam (Sep 2025 – Present)
Visiting Lecturer, FPT University, Ho Chi Minh City, Vietnam (May 2025 – Present)
Lecturer, Swinburne University of Technology, Ho Chi Minh City, Vietnam (Aug 2024 – Present)
Machine Learning Research Intern, Lawrence Livermore National Laboratory, Livermore, CA (Sep 2023 – Mar 2024)
Database Research Intern, Sandia National Laboratories, Livermore, CA (Jun 2023 – Aug 2023)
Graduate Teaching Assistant, University of Washington, Seattle, WA (Sep 2022 – Jun 2024)
Deep Learning Research Assistant, Intel Vietnam / RMIT University, Ho Chi Minh City, Vietnam (Jul 2022 – Nov 2022)
Research Assistant, InfoSeeking Lab, Seattle, WA (Feb 2022 – Dec 2022)
Undergraduate Teaching Assistant, University of Washington, Seattle, WA (Oct 2021 – Dec 2021)
Teaching Assistant, Seattle Central College, Seattle, WA (Oct 2019 – Dec 2020)
Skills
- Programming: Python, Java, JavaScript, C, C#, C++, SQL, SQLite
- Frameworks & Tools: PyTorch, TensorFlow, SciPy, Scikit-learn, Pandas, NumPy, PySpark, Matplotlib, Dash, OpenCV, Hadoop, Kafka, Tableau, d3.js, p5.js, KNIME
Publications
TERA-RAG: Temporal and Epistemic Reliability for Multi-Agent Debate
H. N. Truong, T. L. T. Nguyen, Q. V. H. Nguyen, T. P. T. Tran, M. A. Hoang and T. K. Dang, TERA-RAG: Temporal and Epistemic Reliability for Multi-Agent Debate, 2026 23rd International Joint Conference on Computer Science and Software Engineering (JCSSE), Bangkok, Thailand, 2026, pp. 237-242, doi: 10.1109/JCSSE68839.2026.11596782.
MacroVision: A Two-Stage Localization and Fine-Grained Classification Pipeline for High-Cardinality Food Ingredient Recognition
V. K. Han, N. B. T. Pham and M. A. Hoang, MacroVision: A Two-Stage Localization and Fine-Grained Classification Pipeline for High-Cardinality Food Ingredient Recognition, 2026 23rd International Joint Conference on Computer Science and Software Engineering (JCSSE), Bangkok, Thailand, 2026, pp. 115-120, doi: 10.1109/JCSSE68839.2026.11596987.
AP-ProtoSAM: Enhancing ProtoSAM with Mask-Aware Prototypes and Adaptive Prompting for One-Shot Segmentation
K. V. Nguyen, T. T. Bui, M. A. Hoang and K. Nguyen-Vinh, AP-ProtoSAM: Enhancing ProtoSAM with Mask-Aware Prototypes and Adaptive Prompting for One-Shot Segmentation, 2026 23rd International Joint Conference on Computer Science and Software Engineering (JCSSE), Bangkok, Thailand, 2026, pp. 219-224, doi: 10.1109/JCSSE68839.2026.11597071.
A Modified Fusion Trend Extraction with Attention Model for Industrial Systems Forecasting
M. A. Hoang, H. L. M. Phan, N. V. T. Nguyen, N. Nguyen-Quang, R. Gono, and K. Nguyen-Vinh, A Modified Fusion Trend Extraction with Attention Model for Industrial Systems Forecasting, Discovered Applied Science, doi: 10.1007/s42452-026-08766-z.
EfficientSkinTrans: Enhancing Dermatological Analysis Through a Hybrid ViT Network
M. A. Hoang, H. L. M. Phan, N. N. Vo and K. Nguyen-Vinh, EfficientSkinTrans: Enhancing Dermatological Analysis Through a Hybrid ViT Network, 2026 IEEE 16th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2026, pp. 0676-0682, doi: 10.1109/CCWC67433.2026.11393864.
AI-Driven Methods for Eliminating Harmonic Oscillations in Inverter-Connected Systems
K. Nguyen-Vinh, M. Hoang and R. Goňo, AI-Driven Methods for Eliminating Harmonic Oscillations in Inverter-Connected Systems: Review and Proposed Solution, 2025 7th International Conference on Electrical, Control and Instrumentation Engineering (ICECIE), Pattaya City, Thailand, 2025, pp. 5-13, doi: 10.1109/ICECIE66637.2025.11363838.
AI-Based Energy Forecasting for Net Zero Smart Cities
M. Hoang, K. Nguyen-Vinh and M. -T. Vo, AI-based Energy Forecasting for Net Zero Smart Cities, 2025 7th International Conference on Electrical, Control and Instrumentation Engineering (ICECIE), Pattaya City, Thailand, 2025, pp. 282-289, doi: 10.1109/ICECIE66637.2025.11363824.
Forecasting Urban Energy for Net-Zero Smart Cities: A Hybrid Attention-based Approach
M. A. Hoang, T. D. T. Hoang, T. P. Phan, and K. Nguyen-Vinh, Forecasting Urban Energy for Net-Zero Smart Cities: A Hybrid Attention-based Approach, in Proceedings of the FPT International Conference on Emerging Trends in Computing 2025 (FETC 2025): AI Solution for Developing Countries. Cantho, Vietnam: Bach Khoa Publishing House, 2025, pp. 365–379, ISBN: 978-632-609-823-5.
DenseTransXR: A Hybrid Transformer-Based Approach for Chest X-ray Abnormality and Emerging Disease Detection
M. A. Hoang and H. L. M. Phan, DenseTransXR: A Hybrid Transformer-Based Approach for Chest X-ray Abnormality and Emerging Disease Detection, in Proceedings of the FPT International Conference on Emerging Trends in Computing 2025 (FETC 2025): AI Solution for Developing Countries. Cantho, Vietnam: Bach Khoa Publishing House, 2025, pp. 233–247, ISBN: 978-632-609-823-5.
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review
S. Verma, V. Boonsanong, M. Hoang, K. Hines, J. Dickerson, and C. Shah, Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review, ACM Computing Surveys, vol. 56, no. 12, Art. no. 312, pp. 1–42, Dec. 2024, doi: 10.1145/3677119.
Case Study: Utilising of Deep Learning Models for Fault Detection and Diagnosis of Photovoltaic Modules to Improve Solar Energy Constructions’ O&M Activities Quality
K. Nguyen-Vinh, Q. N. Vo-Huynh, K. Nguyen-Minh, M. Hoang, and S. Rangaraju, Case Study: Utilising of Deep Learning Models for Fault Detection and Diagnosis of Photovoltaic Modules to Improve Solar Energy Constructions’ O&M Activities Quality, in Information Systems Research in Vietnam, Volume 2, Singapore: Springer, 2024, doi: 10.1007/978-981-99-4792-8_5.
Deep Learning Models for Fault Detection and Diagnosis in Photovoltaic Modules Manufacture
K. Nguyen-Vinh, Q. -N. Vo-Huynh, M. Hoang and K. Nguyen-Minh, Deep Learning Models for Fault Detection and Diagnosis in Photovoltaic Modules Manufacture, 2023 IEEE Conference on Artificial Intelligence (CAI), Santa Clara, CA, USA, 2023, pp. 201-202, doi: 10.1109/CAI54212.2023.00095.