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)
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.
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.
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.
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. Hanoi, Vietnam: Bach Khoa Publishing House, 2025, pp. 365–379, ISBN: 978-632-609-823-5.
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. Hanoi, Vietnam: Bach Khoa Publishing House, 2025, pp. 233–247, ISBN: 978-632-609-823-5.
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.
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.
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.