Minh Hoang

About Me

My name is Minh Hoang. I am currently a Ph.D. student in Electrical & Electronic Engineering at RMIT University and a Lecturer in Computer Science & Machine Learning at Swinburne University of Technology (Vietnam). I also teach at Asia University and FPT University as an Adjunct Lecturer.

My research interests include Computer Vision, Anomaly Detection, Medical Imaging, Explainable AI and AI Application in Renewable Energy:

• Hybrid Deep Learning models for urban energy forecasting and radiographic imaging,
• AI-driven fault detection in PV manufacturing,
• Interpretable ML, including counterfactual explanations and algorithmic recourse.

I particularly enjoy working at the intersection of AI, sustainability, and large-scale engineering systems. Over the years, I’ve gained hands-on experience deploying ML models for real-world problems through roles at Lawrence Livermore National Laboratory, Sandia National Laboratories, Intel Vietnam, and the InfoSeeking Lab at the University of Washington.

Past Experiences

I completed both my Bachelor’s and Master’s degrees in Computer Science (Data Science) at the University of Washington, Seattle. During this time, I worked as a Graduate Teaching Assistant for ML, Computer Vision, and Statistics courses (CSE 446/546, CSE 455, STAT 220).

From 2023 to 2024, I interned at Lawrence Livermore National Laboratory, where I worked on Vision-Language Models (BLIP2, InstructBLIP) for vehicle classification in nuclear threat detection systems. Earlier, at Sandia National Laboratories, I developed reaction pathway databases to support scientific ML automation.