Build useful things
Prototype fast, test with real workflows, and keep the product goal visible.
Technical Profile
AI engineer from Vietnam.
I am Huynh Cao Tuan Kiet, a Computer Science student in Ho Chi Minh City focused on AI systems, product engineering, and deep learning for perception.
Uploaded CV
Huynh Cao Tuan Kiet CV
CV_HuynhCaoTuanKiet.pdf / Updated 2026-05-25 00:53
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Who I Am
I like turning technical ideas into working systems.
My work sits between AI research, software engineering, and product taste. I care about systems that are useful, understandable, and fast enough to survive outside a demo.
Explain the system
Good engineering includes clear reasoning, tradeoffs, and technical writing.
Compound in public
Projects, notes, and research create public proof of intelligence over time.
Techstack
Tools and research areas I work with.
AI Engineering
LLM agents, RAG, LLM evaluation, Speech Recognition, PyTorch, Scikit-learn, NumPy, OpenAI APIs.
Software Engineering
Next.js, React, FastAPI, REST APIs, TypeScript, JavaScript, Tailwind CSS, PostgreSQL, MongoDB, SQLite, Docker, Azure.
Research Areas
Computer Vision, Multi-Agent Systems, Reinforcement Learning, LiDAR semantic segmentation.
Timeline
Research engineer path.
2022
HCMUS
Started the Computer Science journey at University of Science, VNU-HCM.
Built the academic base in algorithms, databases, computer systems, probability, statistics, and linear algebra.
2023
Software Foundation
Backend, algorithms, Linux, and full-stack fundamentals.
Expanded from coursework into practical systems work with databases, APIs, web development, and team projects.
2024
Competitions & Research
Academic contests, machine learning, and deep learning fundamentals.
Competed in university CS contests while deepening NLP, CV, graph neural networks, and ML research foundations.
2025
Neurond AI
AI engineering internship and probation on internal AI systems.
Built LLM chatbot workflows with Next.js, OpenAI APIs, AI SDK, PostgreSQL, Azure AI Foundry, speech prototypes, and evaluation loops.
2025
LiDAR Research
3D perception and real-time segmentation for autonomous driving.
Training and evaluating models on SemanticKITTI and nuScenes with mIoU, per-class IoU, latency, FPS, and resource-constrained inference metrics.
2026
KES Paper + Graduation
First-author RangeViM paper and expected CS graduation.
RangeViM targets full-resolution range-view LiDAR segmentation with a lightweight hybrid Vision Mamba backbone.
