AVAILABLE FOR SELECT COLLABORATIONS

01 — ENGINEER / RESEARCHER

Building intelligence for
complex systems.

I’m Nguyen Quoc Anh, an AI Engineer II and applied researcher. I turn ambiguous operational problems into dependable agentic workflows, computer-vision products, and rigorous financial forecasting research.

AI Engineer II
Hitachi Digital Services
3+ years
Industry experience
10+
Predictive-model projects
13+
National media features
Nguyen Quoc Anh, AI Engineer II and applied AI researcher
CURRENT ROLEAI Engineer IIHITACHI DIGITAL SERVICES
10.776 / 106.700
HCMC, VN
AGENTIC AI✦RAG SYSTEMS✦COMPUTER VISION✦QUANT RESEARCH✦AGENTIC AI✦RAG SYSTEMS✦
02 / PRACTICE

THE OPERATING PRINCIPLE

Research discipline.
Production instinct.

I work at the boundary between experimental models and systems people can actually use. That means designing for evaluation, reliability, and the human workflow—not just an impressive demo.

Read the research record →
03 / EXPERIENCE

WHERE I BUILD

From research question
to deployed system.

NOV 2025 — NOW

AI/ML Engineer II

Hitachi Digital Services

Project leader for agentic AI delivery, document intelligence, and on-premise workflow automation.

  • Lead an agentic platform with Azure OpenAI, AGNO, Claude Agent SDK, Qdrant, Redis, and PostgreSQL.
  • Delivered Excel-to-Markdown standardization for a Japan on-site engagement using GPT-5.2, Docling, MinerU, and LLM-as-judge evaluation.
  • Sub-led factory document workflows with Dify, Milvus RAG, REST/OpenAPI, and on-premise deployment guidance.
OCT 2024 — NOV 2025

AI/ML Engineer

Hitachi Digital Services

Built multi-agent planning and edge computer-vision systems across transportation and logistics.

  • Developed rail-planning agents with LangChain, LangGraph, FastAPI, FAISS, PostgreSQL ETL, and scheduling optimisation.
  • Trained YOLOv8 models for HoloLens 2 guidance; packaged ONNX/Sentis inference with CVAT-based data operations.
SEP 2024 — NOV 2025

Founder & Research Lead

The Neurone Group

Built a cross-disciplinary applied-AI hub connecting investment-oriented products, research, and publication.

  • Directed forecasting research across Transformer, neural ODE, and cryptosystem projects for financial and IoT applications.
  • Guided applied computer-science work from research design through publication and product framing.
AUG 2023 — OCT 2024

Undergraduate AI/ML Researcher

RMIT University Vietnam

Built quantitative models and research data pipelines spanning market forecasting, health data, and cybersecurity.

  • Developed S&P 500 models using phase-space reconstruction and attention mechanisms.
  • Managed Python ETL for 2M+ irregular observations; contributed to federated IoT security experiments and two CORE publications.
04 / SELECTED SYSTEMS

APPLIED RESEARCH

Models with a
reason to exist.

A selection of research and implementation work across market intelligence, visual recognition, and temporal modelling.

CryptMAGE model visualization

02 / VISION TRANSFORMER

CryptMAGE

Market images → signal recognitionOpen studio ↗
05 / ACADEMIC RECORD

SELECTED PUBLICATIONS

A research program
in motion.

Google Scholar ↗

Publication list aligned with the current portfolio record. Follow Scholar for citation activity and complete indexing.

06selected publications
2024—26active record
AI × Financeprimary research axis
TRANSFORMERSTIME SERIESNEURAL ODECYBERSECURITY
2026

JOURNAL · Q1

LiteFormer: A lightweight encoder-only Transformer for efficient financial time series forecasting across global stock indices

Anh, Phat, Son, Nhan, Phien, Tuan & Kim · Engineering Applications of Artificial Intelligence

↗
2026

JOURNAL · Q1

ChanFormer: An encoder-only channel-wise Transformer for multi-asset financial time series forecasting

Trung, Anh, Son, Phien, Tuan, Thuan, Chan & Khoa · Computers and Electrical Engineering

↗
2026

CONFERENCE · CORE A

SLIE: A Secure and Lightweight Cryptosystem for Data Sharing in IoT Healthcare Services

Son, Anh, Phat, Tuan & Nghiem · ICSOC 2025 Proceedings

↗
2025

JOURNAL · Q2

CLAM: A Synergistic Deep Learning Model for Multi-Step Stock Trend Forecasting

Anh & Hy · Intelligenza Artificiale

↗
2024

CONFERENCE · CORE A

Phase Space Reconstructed Neural Ordinary Differential Equations Model for Stock Price Forecasting

Anh, Son & Hieu · PACIS 2024 Proceedings

↗
2024

CONFERENCE · CORE B

Transforming Stock Price Forecasting: Deep Learning Architectures and Strategic Feature Engineering

Anh & Son · MDAI 2024 Proceedings

↗
06 / ACHIEVEMENTS

RECOGNITION & REACH

Work that travels.

07 / CONTACT

LET’S BUILD SOMETHING REAL

Have a difficult
problem in mind?

Open to thoughtful collaborations in applied AI, research engineering, and intelligent systems.