Sang Truong · Senior AI Engineer · Applied AI Systems

I build AI systems that survive contact with reality.

Senior AI engineer and technical lead with 8+ years of professional AI/software engineering experience spanning agents and knowledge systems, computer vision and video, quantitative ML, speech, edge inference, and production software. I work end to end: from research and data contracts to application architecture, deployment, evaluation, reliability, and stakeholder acceptance.

Ho Chi Minh City, Vietnam · GitHub @sangtrx

View flagship systems Technical depth Résumé
Current roleHead of Artificial IntelligenceProfessional AI / software experience8+ yearsGraduate degreeMS Computer Engineering · 4.0/4.0ResearchIJCV · AAAI Oral · IEEE JBHI · Poultry Science

Technical depth

One engineer. Four deep system domains.

The headline stays simple. The depth comes from owning the hard boundaries: model versus truth, research versus runtime, camera versus evidence, implementation versus acceptance.

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

Flagship systems

High signal. Deliberately low disclosure.

The case studies expose the engineering decisions a technical interviewer needs to judge depth — authority, state, evidence, causality, failure, deployment — while withholding private corpus, strategy, credentials, topology, runbooks, and internal identifiers.

Case study2026

AI Architect / Lead Builder · EPIC TECHNOLOGY

Clinical AI for a Traditional Medicine Hospital

EPIC TECHNOLOGY · Clinical AI & Decision Support

A clinician-facing AI system for knowledge lookup, interaction analysis, prescription review, and grounded Q&A. The public case study shows the engineering boundary and safety model while intentionally withholding private corpus, deployment, and implementation detail.

Governed knowledgeDurable application stateExplicit clinical authority
Clinical AIAgentsRAGFastAPIPostgreSQLOn-prem
Open case study
Case studyJun 2026 — Present

Independent AI/Quant Side Project · Solo Builder

Curren

Independent quantitative intelligence & trading-systems project

A solo-built quantitative research and systems platform connecting point-in-time evidence, reproducible evaluation, shared research/runtime semantics, guarded operational state, and a sanitized public verification surface — without publishing strategy internals.

Point-in-time evidenceResearch/runtime parityRead-only public surface
Quant ResearchRustPythonPIT DataTrading SystemsMCP
Open case study
Case study2025 — Present

AI / Computer Vision Systems Lead · EPIC TECHNOLOGY

Production Multi-Camera Video Intelligence

EPIC TECHNOLOGY · Computer Vision & Physical-World AI

The challenge beyond object detection: making heterogeneous cameras source-qualified, fresh, observable and recoverable, then connecting perception to trusted events and evidence on constrained hardware.

Source identity and freshnessTemporal detection and evidenceBounded recovery
Video AIComputer VisionYOLOALPRTrackingMedia pipelines
Open case study
Case study2024 — 2025

AI Engineer · FPT Software

Enterprise Conversational AI

FPT Software · Team-built agent systems

My primary work was designing prompts, graph-node logic and AI tools within a broader enterprise agent platform: conversation state, retrieval, safety and service failure boundaries.

AI graph/node logicPrompts and toolsSystem-state boundaries
Enterprise AIAgentsLangGraphAzure OpenAIRAG
Open case study
Case study2024 — 2025

AI Engineer · FPT Software

Interview & Voice AI Systems

FPT Software · Conversation, speech & evaluation

Speech-enabled interview workflows integrating browser interaction, stateful scenarios, asynchronous AI services and evaluation, with explicit system-versus-personal ownership boundaries.

Voice interactionConversation/scenario stateAsync evaluation
Voice AIAzure SpeechNext.jsPythonInterview AI
Open case study

Selected system boundaries

Enough detail to prove depth. Not enough to leak the playbook.

These are intentionally abstracted architecture cuts: ownership, state, evidence, and failure boundaries are visible; sensitive implementation and operational details stay private.

Clinical AI

Governed clinical intelligence

EPIC TECHNOLOGY · AI Architect / Lead Builder

Clinician workflow AI reasoning Governed evidence Clinical authority

Shows the authority boundary, not the private corpus, prompts, infrastructure, or deployment topology.

Read the public case study

Physical-world AI

Video intelligence under real constraints

EPIC TECHNOLOGY · AI / Computer Vision Systems Lead

Media sources Perception Temporal state Evidence & recovery

The public view keeps vendor details, camera topology, credentials, and operational runbooks private.

Quant systems

Research discipline → guarded runtime

Independent side project · Solo Builder

PIT evidence Evaluation Runtime state Public verification

Strategy parameters, private data sources, execution controls, and trading authority are intentionally excluded.

Read the public case study

Research

Methods that survive beyond a paper

University of Arkansas · Applied Research

Research question Representation Evaluation Target hardware

Peer-reviewed work and deployment constraints are public; proprietary datasets and unsupported production claims are not.

System portfolio

The work is broader than two case studies.

Selected work across healthcare, education, enterprise agents, physical-world AI, quantitative systems, and research. Client/employer ownership stays explicit; sensitive implementation stays private.

012026

EPIC TECHNOLOGY · AI Architect / Lead Builder

Hospital Clinical AI & Decision Support

Clinician-facing lookup, interaction analysis, prescription review, and knowledge Q&A with governed evidence, citations, durable state, and explicit clinical authority boundaries.

Clinical AI · governed knowledge
022025 — Present

EPIC TECHNOLOGY · AI / Computer Vision Systems Lead

Production Multi-Camera Video Intelligence

Physical-world video AI spanning heterogeneous media sources, perception and tracking, temporal events, evidence, monitoring, and recovery under constrained hardware and vendor interfaces.

Production physical-world AI
032025 — Present

EPIC TECHNOLOGY · AI Architect / Lead Builder

AI-Powered Open edX Platform

Teacher-reviewable content generation and AI tutoring with retrieval, Vietnamese speech, real-time interaction, platform integration, browser verification, and operational delivery.

Education AI · human review
042024 — 2025

FPT Software · AI Engineer

AI4U Enterprise Conversational Agent

Team-built enterprise assistant with Azure OpenAI, retrieval and graph/tool workflows; personal contributions centered on AI prompts, nodes and tools.

Enterprise agents · RAG
052024 — 2025

FPT Software · AI Engineer (team project)

Interview & Voice AI Systems

Speech-enabled interview and transcription workflows with browser voice interaction, conversational scenarios, asynchronous AI dialogue/evaluation and backend services.

Voice & interview AI · evaluation
062021 — 2024

University of Arkansas · Applied Research

Industrial & Poultry Vision Research

Visual inspection and workstation-state research connecting perception models to bounded physical-process evidence, alongside Jetson/TensorRT/CUDA edge optimization.

Industrial CV · edge inference
07Jun 2026 — Present

Independent side project · Solo Builder

Curren Quant Intelligence & Trading Systems

Point-in-time research evidence, reproducible evaluation, shared causal semantics, durable lifecycle/risk state, guarded execution boundaries, and sanitized public verification.

Research discipline · system parity

End-to-end ownership

Beyond the model call.

The recurring pattern is taking an uncertain research or product goal and making the ownership, system state, failure modes, evaluation, operations, and acceptance boundary explicit.

Architecture & authority

Turn ambiguous requirements into clear system boundaries, data ownership, interfaces, permissions, state, and acceptance criteria.

AI, tools & knowledge

Design model, retrieval, tool, memory, and human-review paths without letting probabilistic output silently become system truth.

Backend & product

Build the software around the model: APIs, durable state, async work, streaming, integrations, product surfaces, and operational controls.

Evaluation & reliability

Separate implemented from validated, make failure modes observable, and use evidence rather than fluent output as the acceptance boundary.

Cloud, edge & deployment

Carry systems through Docker/Linux, cloud or on-prem delivery, GPU/edge constraints, monitoring, recovery, and handoff.

Research to production

Preserve causality, provenance, reproducibility, and experimental assumptions while turning research into usable systems.

Career

Research depth. Product ownership. Production constraints.

A broad engineering path across embedded vision, quantitative systems, multimodal research, enterprise agents, clinical AI, education platforms, and production video intelligence.

Jun 2025 — Present

Head of Artificial Intelligence

EPIC TECHNOLOGY

Leading hands-on architecture and delivery across clinical AI, education AI, computer vision/video intelligence, and AI platform engineering.

Jun 2024 — Present

AI Tech Lead · Part-time / Consulting

A9 IOT

Leading environmental IoT forecasting workflows from preprocessing and evaluation through inference, visualization, and stakeholder reporting.

Oct 2024 — Jun 2025

AI Engineer

FPT Software

Contributed to two FPT project families: enterprise conversational AI (primarily prompts, graph-node logic and tools) and speech-enabled interview/transcription services in team-built applications.

May 2021 — Jan 2024

Graduate Researcher / PhD Student Researcher & Teaching Assistant

University of Arkansas

Graduate research in multimodal video understanding, vision-language learning, medical time-series learning, industrial computer vision, and edge inference; completed an MS in Computer Engineering.

Full chronology, teaching, skills and honors

Research

Peer-reviewed foundations.

Work across temporal video understanding, actor/object/environment interaction modeling, vision-language learning, medical time-series representation learning, and industrial computer vision. VLTinT was selected as an AAAI 2023 Oral.

Google Scholar
2024 CarcassFormer
Simultaneous localization, segmentation, and classification of poultry carcass defects Poultry Science 2023 AOE-Net
Entity-interaction modeling with adaptive attention for temporal action proposal generation International Journal of Computer Vision 2023 VLTinT
Visual-linguistic Transformer-in-Transformer for coherent video paragraph captioning · AAAI Oral AAAI 2023 sCL-ST
Supervised contrastive learning with semantic transformations for multi-lead ECG arrhythmia classification IEEE JBHI
Research rigor is only useful in production if the system preserves the contract that made the result valid.

That means explicit authority in clinical AI, causal evidence in quantitative systems, and source/failure awareness in physical-world AI.

Senior / lead roles

Need someone who can own the whole system?

I'm interested in applied AI leadership and senior engineering roles where model capability has to become reliable software: agent platforms, computer vision/video intelligence, multimodal AI, quantitative ML, distributed AI backends, and production delivery.

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