AI Engineer · Deep Learning Researcher · Quant Researcher

AI systems for markets, machines, and decisions.

I design and ship GenAI agents, computer vision pipelines, and deep learning models for financial forecasting. My work connects production engineering with published research in neural ODEs, attention models, and chaotic time series.

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AI/ML EngineerHitachi Digital Services
6 publicationsAI, finance, and society
43 reviewsPeer review contributions

About

Research-grade thinking with production-grade delivery.

Nguyen Quoc Anh is completing a Bachelor of Business in Economics and Finance at RMIT Vietnam while working as an AI/ML Engineer. He builds applied systems across GenAI, computer vision, and quantitative forecasting, with a research record spanning financial deep learning, phase space reconstruction, and societal time series.

Deep Learning Chaos Theory Algorithmic Trading Time Series Generative AI Computer Vision

Experience

Work across enterprise AI, applied research, and human-centered data collection.

Bachelor of Business in Economics and Finance, RMIT Vietnam, expected 2026.

Oct 2024 - Present Hitachi Digital Services

AI/ML Engineer

Built LLM-based multi-agent systems for high-speed rail planning with Llama 3.3, Qwen 2.5, and Azure OpenAI.
Developed Text-to-SQL agents with LangChain, LangGraph, PostgreSQL ETL, FastAPI delivery, and FAISS-backed retrieval.
Trained and deployed YOLOv8-11n computer vision models for HoloLens v2 factory workflows.

Sep 2024 - Oct 2024 Tech Mahindra

Research Associate

Conducted a 1,000-participant user study for unreleased smart devices across 50+ test protocols.
Maintained customer-facing research operations while protecting vendor privacy and data quality.

Mar 2023 - Aug 2024 RMIT Vietnam

AI/ML Researcher

Developed deep learning models for S&P 500 forecasting with phase space reconstruction and attention mechanisms.
Managed ETL for 2M+ irregular observations from PhysioNet and YFinance using Python.
Built cryptographic algorithms and federated environments for IoT cybersecurity research.

Selected Projects

Applied AI projects with measurable performance and research outputs.

Stock Trend Prediction

CLAM: Stacked CNN-LSTM-AM Model

Built a Conv1D, LSTM, and attention architecture for multi-step stock trend forecasting, improving MAE and RMSE by 90% and capturing 75% of out-of-sample trends.

Lightning Studio Paper

Vision Transformer

CryptMAGE

Converted intraday cryptocurrency time series into image sequences with engineered metadata, reaching 95% accuracy, 91% AUROC, and 90% AUPRC.

Lightning Studio

Neural ODE

PSR-NODE

Designed 3D phase space representations with neural ODEs and time-series validation, reducing MAE and RMSE by 70% against LSTM, Transformer, and SVR baselines.

Publication Presentation

Financial Forecasting

CNN-BiLSTM-GRU

Created a hybrid deep learning model for Target, Amazon, and Walmart stock forecasting, reducing MAE by 37.2% and RMSE by 35.1%.

Publication

Publications

Peer-reviewed and public scholarship.

Financial machine learning, interpretable forecasting, and technology-society commentary.

Journal · 2025

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

Authors: Nguyen A and Truong H

Venue: Intelligenza Artificiale, Q2, 19(1):1-14.

DOI: 10.1177/17248035251322877

Conference · 2024

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

Authors: Nguyen A, Ha S, and Thai H

Venue: PACIS 2024 Proceedings, CORE A, 1(1):1-17.

Paper

Conference · 2024

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

Authors: Nguyen A and Ha S

Venue: MDAI 2024 Proceedings, CORE B, 1(14986):1-14.

DOI: 10.1007/978-3-031-68208-7_20

Preprint · 2024

LiteFormer: An Encoder-Only Multi-Head Attention Transformer for Financial Time Series Forecasting

Authors: Nguyen A, Ha S, and Phien N

Venue: SSRN Electronic Journal, 2024.

DOI: 10.2139/ssrn.4729648

Conference · 2023

Long Short-Term Memory Architectures for Sustainable Economic Prosperity

Author: Nguyen A

Venue: ICYREB 2023 Proceedings, UEH Publishing House, Vol. 2, pp. 83-94.

DOI: 10.5281/zenodo.11081926

Public Scholarship · 2024

Con người thời kỳ 5.0: Ta tiêu đời từ phút giây mất mạng?

Author: Anh N

Venue: Sponsored public article and YouTube feature with Spiderum Official.

Podcast Article

Recognition

Awards, speaking, and reviewer service.

2024-2026

Invited Peer Reviewer

IEEE Transactions on Industrial Informatics, Computers & Electrical Engineering, Humanities & Social Sciences Communications, Engineering Applications of Artificial Intelligence, ICPR, Annals of Operations Research, and IEEE Access.

2024