Contact

Ngô Trung Kiên, PhD

ERA Lab · AI & Platform Architecture

Lecturer · HSB, Vietnam National University, Hanoi

Ngô Trung Kiên connects research in visible-light communication, agentic AI, and smart agriculture with ERA Lab’s AI and platform architecture work.

Contact by email All members
Portrait of Ngô Trung Kiên, PhD

Research, practice, and impact

Ngô Trung Kiên’s research spans visible-light communication, hybrid VLC/RF networks, agentic AI, and IoT for smart agriculture. Across these areas, he studies how communication and intelligent systems can work together in practical settings.

HSB describes his doctoral research at the University of Palermo, Italy, as work on intelligent management for hybrid VLC/RF networks, completed as an EU H2020 Marie Curie Fellow. The work received a Best Poster Award at ACM MobiCom 2023. HSB also identifies AGRIFARM-AI, an autonomous precision-farming platform using multi-agent reinforcement learning, among his current projects.

Research areas

  • Visible-light communication
  • Agentic systems
  • Smart agriculture
  • Hybrid VLC/RF networks
  • Massive IoT

Expertise & contributions

Best Poster Award at ACM MobiCom

Research recognition · 2023

Recognition for doctoral research on intelligent management of hybrid visible-light and radio-frequency communication networks.

Source: HSB faculty profile

AGRIFARM-AI

Applied research · Smart agriculture

An autonomous precision-farming platform that applies multi-agent reinforcement learning to agricultural systems.

Source: HSB faculty profile

EU H2020 Marie Curie Fellow

International research fellowship

Completed his PhD research at the University of Palermo, Italy, on intelligent management for hybrid VLC/RF networks.

Source: HSB faculty profile

Selected research and applied work

  1. Smart and Sustainable Agriculture: Offline Reinforcement Learning for Intelligent Handover in Hybrid VLC/RF Agricultural IoT Networks

    Conference paper · 2026

    Studies offline reinforcement learning for intelligent handover in hybrid VLC/RF agricultural IoT networks.

    View source

  2. Data driven adaptive SVC control for 110 kV substations using machine learning and edge deployment validation

    Research article · 2026

    A study applying machine learning and edge deployment validation to adaptive control in electrical substations.

    View source

Sources and contact

HSB faculty profile Google Scholar The Research Ledger kiennt@hsb.edu.vn