Trong Nguyen

About

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Trong Nguyen

Associate Technical Leader
@Koïos Intelligence
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Hi 👋, I'm Trong - an AI Engineer with a deep passion for software development and how machine learning can be integrated into real-world products.

After completing my PhD in Computer Vision, I spent a year working as a postdoctoral researcher before moving into the startup environment. Since then, I've focused on building NLP systems, experimenting with applied machine learning, LLMs, and exploring scalable architectures that bridge research and production.

Over the past five years in industry, I've come to define my working motto as: work with passion, play as a team, learn from each other, and grow together. Therefore I make this blog as a space to share knowledge, document experiments, and learn openly. I hope the content here can be useful to others, and I welcome feedback or corrections so we can all improve together.

Beyond work, I'm also a 🎮 game lover (though these days, I mostly enjoy watching short moments of game streams on YouTube rather than playing myself 😅).

If you enjoy exploring new ideas, building things, or simply learning through experimentation, I'd love to connect.

My career

  • Koïos Intelligence
    Jan 2021 – Present
    Koïos Intelligence
    Associate Tech Lead - Dec 2025
    Team Leader - Aug 2022
    AI Engineer - Jan 2021

    Over the past few years, I've grown from an AI engineer into a technical leader working on production chatbot systems. I started by improving NLP models and developer tooling, reducing model training time and CI/CD pipeline execution significantly. As my role expanded, I led a cross-functional team delivering chatbot and voice-based features, while improving infrastructure with Kubernetes environments, optimized deployment pipelines, and cost-saving architecture changes.

    More recently, I've been focusing on system design and new AI capabilities of building backend services for secure insurance data access, developing a phone-based chatbot system, and prototyping features using LLMs and RAG. Alongside development and mentoring, I help maintain reliability by monitoring production systems and leading incident response when issues arise.

  • University of Montreal
    Jan 2020 – Jan 2021
    University of Montreal
    Post-doctoral Researcher
    • Designed deep neural network for detecting anomalies in surveillance videos
    • Published paper in IEEE Trans. on Neural Networks and Learning Systems
  • University of Montreal
    Sept 2015 – Dec 2019
    University of Montreal
    PhD in Computer Science
    • 3D reconstruction system consisting of a depth camera and two mirrors
    • Proposed algorithms reducing depth distortion caused by the Time-of-Flight depth estimation and mirrors
    • Performed data acquisition and gait analysis on 3D point clouds representing human walking gaits
    • Initiated side project on anomaly detection using deep learning, contributing to later published research at top-ranked ICCV conference
  • Danang University of Science and Technology
    Jul 2014 – Aug 2015
    Danang University of Science and Technology
    Research Assistant
    • Developed algorithms for recognizing static and dynamic hand gestures
    • Performed data acquisition for hand gestures in depth representation
    • Advised students working on other vision-related projects in the laboratory
  • University of Montreal
    Mar 2014 – June 2014
    University of Montreal
    Student Intern
    • Performed data acquisition for multiple walking gait types
    • Developed algorithm for gait analysis using a color camera
  • The University of Danang
    Dec 2012 – Jan 2015
    The University of Danang
    Master in Computer Science
    • Worked on typical image processing and machine learning algorithms
    • Performed human gait assessment based on sequence of 2D silhouettes
    • Built hidden Markov models representing transition of postures in gait cycle

Selected publications