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

SkinXViT: A Novel Explainable Hybrid ViT Approach for Skin Lesion Diagnosis

Embedding Rule-Based Augmented Reality Scaffolding in Experiential Learning Cycles: An SEM Study of Student Engagement in Lab-Based STEM

IP102-TailDet: A budget-aware tail completion benchmark for long-tailed insect pest detection

Transforming Environmental Knowledge Into Business Opportunity through Circular Economy Practices Mediation

TERA-RAG: Temporal and Epistemic Reliability for Multi-Agent Debate

MacroVision: A Two-Stage Localization and Fine-Grained Classification Pipeline for High-Cardinality Food Ingredient Recognition

AP-ProtoSAM: Enhancing ProtoSAM with Mask-Aware Prototypes and Adaptive Prompting for One-Shot Segmentation

A Modified Fusion Trend Extraction with Attention Model for Industrial Systems Forecasting

EfficientSkinTrans: Enhancing Dermatological Analysis Through a Hybrid ViT Network

AI-Driven Methods for Eliminating Harmonic Oscillations in Inverter-Connected Systems

AI-Based Energy Forecasting for Net Zero Smart Cities

Forecasting Urban Energy for Net-Zero Smart Cities: A Hybrid Attention-based Approach

DenseTransXR: A Hybrid Transformer-Based Approach for Chest X-ray Abnormality and Emerging Disease Detection

Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review

Case Study: Utilising of Deep Learning Models for Fault Detection and Diagnosis of Photovoltaic Modules to Improve Solar Energy Constructions’ O&M Activities Quality

Deep Learning Models for Fault Detection and Diagnosis in Photovoltaic Modules Manufacture

Teaching

Swinburne University of Technology

Asia University

FPT University

RMIT University

University of Washington