About

Research-trained. Systems-minded. Production accountable.

I'm Sang Truong (@sangtrx), a senior AI engineer based in Ho Chi Minh City, Vietnam. My work spans model research, LLM/agent systems, computer vision and video intelligence, quantitative ML, distributed backends, product engineering, cloud/edge deployment, and the operational boundaries that decide whether an AI system is actually trustworthy.

Operating model

Own the path from research to acceptance.

I am most useful when a system crosses several disciplines at once: research assumptions, data contracts, model/tool behavior, backend state, user experience, infrastructure, and stakeholder acceptance. I do not treat the model as the whole product.

My current Head of AI role covers clinical AI, education AI, production computer vision/video intelligence, and AI platform engineering. Earlier work spans enterprise conversational agents, multilingual speech systems, environmental forecasting, quantitative research, multimodal/video research, and embedded computer vision.

I prefer explicit boundaries over architecture theater: which component owns facts, what data was available at decision time, what can fail, what is recoverable, what has actually been validated, and what the system deliberately does not claim.

Domain depth

Broad systems ownership, with real depth where it matters.

The résumé keeps one canonical chronology while expanding evidence by domain. These are the four recurring technical centers.

01

Applied AI · Agents · Voice · RAG

Production AI where knowledge, tools, state, safety, evaluation, and user workflows matter as much as the model call.

  • Clinical decision support with governed knowledge, citations, deterministic application authority, and explicit human/production boundaries
  • Enterprise conversational AI with retrieval, tool/model routing, memory controls, guardrails, and distributed workloads
  • Multilingual speech and real-time interaction across API, worker, and browser-facing paths

Python · FastAPI · LangGraph/LangChain · Azure OpenAI · Qdrant/Milvus/pgvector · PostgreSQL · Playwright · Celery/RabbitMQ/Redis

02

Computer Vision · Video · Edge AI

Physical-world AI spanning camera/media input, perception, tracking, temporal state, evidence, target-device inference, and recovery.

  • Production multi-camera video intelligence across heterogeneous real-world sources and operational failure modes
  • Industrial and academic vision workflows for inspection, recognition, tracking, and workstation state
  • Edge optimization with TensorRT/CUDA/Jetson plus RGB-D and embedded perception work

PyTorch · TensorFlow · OpenCV · YOLO · ALPR · Tracking · TensorRT · CUDA · ONNX Runtime · Jetson · RTSP/HLS · FFmpeg

03

Quantitative Research · Trading Systems

Research and runtime engineering built around point-in-time evidence, causal computation, disciplined evaluation, durable state, and guarded execution boundaries.

  • Curren: point-in-time research pipeline and shared research/runtime semantics without exposing strategy internals
  • Leakage-aware evaluation, reproducible data artifacts, selection controls, lifecycle/risk state, and reconciliation
  • Earlier equity, crypto, and FX research with ML ensembles, market data, cloud execution, and experiment tracking

Rust · Python · Arrow/Parquet · Polars · DuckDB · LightGBM · CatBoost · XGBoost · Scikit-learn · SciPy · Statsmodels · Optuna · NautilusTrader

04

Research · Multimodal & Temporal ML

Peer-reviewed research across temporal video understanding, vision-language learning, medical time-series representation learning, and industrial computer vision.

  • Temporal action proposal generation and interaction modeling for long untrimmed video
  • Vision-language learning and coherent video paragraph captioning, including an AAAI 2023 Oral
  • Medical time-series representation learning and industrial visual inspection research

Transformers · Contrastive Learning · PyTorch · TensorFlow · Detectron2 · MATLAB · NumPy · SciPy · Scikit-learn · Weights & Biases

How I think

Good AI systems are contracts, not demos.

Preserve authority.

Give models room to reason where useful while keeping authoritative facts, permissions, tools, and failure behavior explicit.

Preserve causality.

In research and live systems, respect what information existed at decision time. Point-in-time discipline and provenance are engineering requirements.

Preserve evidence.

Separate fluent output from the source, tool result, experiment, runtime observation, or acceptance gate that supports it.

Design for operation.

State, retries, idempotency, restart behavior, monitoring, recovery, access control, deployment and handoff are part of the product.

Optimize on target hardware.

For physical-world AI, camera/media reliability and target-device inference behavior matter more than isolated benchmark numbers.

State the boundary.

Implemented, tested, deployed, accepted, and production-ready are different claims. I keep them different.

Technical stack

Tools organized by system responsibility.

The stack is broad because the systems cross model, data, product, infrastructure, and physical-world boundaries.

Applied AI / LLM / agents

LLM/RAG/agents · LangGraph/LangChain · tool/model routing · memory/context · grounded generation · guardrails · human-review boundaries · evaluation

Retrieval & knowledge systems

Qdrant · Milvus · Pinecone · pgvector · PostgreSQL · embeddings · governed ingestion · metadata filtering · citations · provenance

Voice / real-time AI

Azure Speech · multilingual ASR · Vietnamese ASR/TTS · speech evaluation · WebSockets/SSE · AsyncIO · background processing

Computer vision / video / edge

PyTorch · TensorFlow · OpenCV · YOLO · Detectron2 · ALPR · tracking · TensorRT · ONNX Runtime · CUDA · Jetson · RGB-D · RTSP/HLS · FFmpeg

Quantitative ML & research data

Rust · Python · point-in-time data · Arrow/Parquet · Polars · DuckDB · LightGBM · CatBoost · XGBoost · Scikit-learn · SciPy · Statsmodels · Optuna · NautilusTrader

Backend & distributed systems

Python · FastAPI · REST/SSE · WebSockets · Celery · RabbitMQ · Redis · PostgreSQL · SQLite · MongoDB · MinIO/S3 · retries · idempotency · durable state

Product, cloud & delivery

Next.js · React · TypeScript/JavaScript · Open edX · Playwright · Docker · Kubernetes · Linux · systemd · Nginx · AWS · Azure

Languages

English — professional working proficiency · Vietnamese — native

Research trajectory

From temporal video reasoning to applied AI systems.

2021 → 2023

Temporal action understanding

ABN → AEI → AOE-Net: action-boundary and interaction modeling for long untrimmed video, culminating in IJCV.

2022 → 2023

Vision-language video understanding

VLCAP → VLTinT: contrastive and Transformer-based modeling for coherent video paragraph captioning; VLTinT was selected as an AAAI 2023 Oral.

2021 → 2024

Medical & industrial ML

Medical time-series representation learning plus industrial/poultry vision and target-hardware edge optimization.

Education

Research-trained engineering.

Jul 2021 — Dec 2023

Master of Science in Computer Engineering (MSCmpE) · University of Arkansas

GPA 4.0/4.0 · thesis: “Towards Multi-modal Interpretable Video Understanding” · advisor: Prof. Ngan Le.

2015 — Nov 2019

Bachelor of Engineering in Automation and Control Engineering · International University — VNU HCMC

GPA 3.50/4.00 · Very Good · Top 1% · half-tuition scholarship recipient.

Selected research

Peer-reviewed work across multiple AI domains.

Explore

See the systems, chronology and evidence.