About Me
My name is Minh Anh Hoang. I am currently a Ph.D. student in Electrical and Electronic Engineering at RMIT University, advised by Dr. Khuong Nguyen-Vinh. I am also a Lecturer in Computer Science and Machine Learning at Swinburne University of Technology, Ho Chi Minh City, Vietnam.
My research interests include Computer Vision, Explainable AI, Medical AI, and AI applications in Renewable Energy and Sustainable Engineering. My recent work spans some areas, including:
- Computer Vision & Multimodal Learning
- Explainable AI
- Time-Series Forecasting & Intelligent Energy Systems
- Renewable Energy & Sustainable Engineering
- Generative AI, RAG & Multi-Agent Systems
- Medical Imaging & Healthcare AI
- AI for Education
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 (September 2022 – June 2024)
- B.S. in Computer Science (Data Science), University of Washington, Seattle, WA (September 2020 – June 2022)
- A.S. in Computer Science, Seattle Central College, Seattle, WA (January 2019 – June 2020)
Academic & Professional Experience
Current Academic Positions and Teaching Experience
- Lecturer, Swinburne University of Technology, Ho Chi Minh City, Vietnam (August 2024 – Present)
- Visiting Lecturer, Asia University, Ho Chi Minh City, Vietnam (September 2025 – December 2025)
- Visiting Lecturer, FPT University, Ho Chi Minh City, Vietnam (May 2025 – September 2025)
- Graduate Teaching Assistant, University of Washington, Seattle, WA (September 2022 – June 2024)
- Undergraduate Teaching Assistant, University of Washington, Seattle, WA (October 2021 – December 2021)
- Teaching Assistant, Seattle Central College, Seattle, WA (October 2019 – December 2020)
My teaching focuses primarily on Artificial Intelligence, Machine Learning, Data Science, and Intelligent Systems, with an emphasis on connecting theoretical concepts with research and practical applications. During my time at the University of Washington, I supported courses in Machine Learning, Computer Vision, and Statistics, including CSE 446/546, CSE 455, and STAT 220.
Research & Industry Experience
- Machine Learning Research Intern, Lawrence Livermore National Laboratory, Livermore, CA (September 2023 – March 2024)
- Database Research Intern, Sandia National Laboratories, Livermore, CA (June 2023 – August 2023)
- Deep Learning Research Assistant, Intel Vietnam / RMIT University, Ho Chi Minh City, Vietnam (July 2022 – November 2022)
- Research Assistant, InfoSeeking Lab, Seattle, WA (February 2022 – December 2022)
At Lawrence Livermore National Laboratory, I integrated Vision-Language Models, including BLIP-2 and InstructBLIP, for vehicle classification in research related to nuclear threat detection systems. At Sandia National Laboratories, I worked on reaction pathway databases and scientific Machine Learning automation.
Skills & Technical Expertise
- 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