Tuan Loc

Bio

I am a graduate researcher whose work sits at the intersection of applied machine learning and systems security. My path into AI started with classical intrusion-detection systems, which led me to ask a harder question: how do we build learning systems that stay accurate and private when data cannot leave the edge? That question now anchors most of my research — spanning federated learning for cross-hospital diagnostics, continual learning for evolving threat landscapes, and TinyML for on-device anomaly detection. Alongside original research, I maintain a public practice of reproducing landmark papers end-to-end (ResNet, ViT, FedAvg, LoRA, CLIP, and others) as a way of internalizing methods deeply enough to extend them responsibly. I write regularly about what I learn, both the results and the failures.

Research Philosophy

I believe the best research habits are built the same way as good engineering habits: reproduce before you innovate, measure before you claim, and write things down clearly enough that a stranger — or you, in six months — can rebuild your result from scratch. Every paper reproduction on this site follows that discipline: a documented motivation, an honest comparison against the original numbers, and a section on what didn't work.

Education & Experience

Timeline

1. 2024 — Present

   PhD Track Researcher, AI Security & Health Lab

   University of Technology, Ho Chi Minh City

   Researching federated and continual learning methods for intrusion detection and clinical diagnostic models under data-scarcity and privacy constraints.

2. 2023 — 2024

   Research Assistant, Applied ML Group

   University of Technology, Ho Chi Minh City

   Built baseline pipelines for network traffic classification using deep learning; co-authored a workshop paper on adversarial robustness of NIDS models.

3. 2022

   B.Eng. Computer Science, Summa Cum Laude

   University of Technology, Ho Chi Minh City

   Thesis: "Lightweight Convolutional Architectures for On-Device Malware Detection." Graduated top of cohort.

4. 2021

   ML Engineering Intern

   CyberShield Vietnam

   Shipped a production anomaly-detection microservice for SOC alert triage, reducing analyst triage time by 35%.

5. 2020

   Started Independent Paper Reproduction Practice

   Personal Research Log

   Began systematically reproducing landmark deep learning papers from scratch as a deliberate-practice discipline.