Vietnam National University Ho Chi Minh City sets aside 1.875 trillion dong for AI, chips and robotics

Vietnam National University Ho Chi Minh City is committing 1.875 trillion dong to a race for strategic technologies, with artificial intelligence, semiconductor chips, robotics and quantum technology among its leading priorities.

The university’s roadmap runs through 2030 and beyond. It covers 10 technology groups: digital technology, AI and data; semiconductor chips and integrated circuits; robotics and automation; aviation, space and the low-altitude economy; biotechnology; biomedicine and healthcare; advanced materials; energy and the environment; quantum technology; and high-speed and urban rail.

In AI and data, early work will focus on healthcare, education, public administration, big data and traceability. By 2030, the university aims to develop multimodal AI, Vietnamese large language models, digital twins and AI for smart manufacturing, with a longer-term goal of sovereign AI and a national data ecosystem.

Semiconductor research will include shared infrastructure, Edge AI chips, chips for the Internet of Things and unmanned aerial vehicles, and very-high-frequency signals. The roadmap then moves toward RISC-V, photonic chips, radar, electronic warfare and advanced packaging, before targeting high-performance chips, 6G and aerospace applications.

Robotics research will begin with service robots and collaborative robots, then expand to industrial robots and autonomous systems. Aerospace work will cover UAVs, GPS-free positioning, flight control, radar and chips, followed by Earth observation, environmental monitoring and satellite technology. Biotechnology priorities include microorganisms, enzymes and biological products, later expanding to synthetic biology, cell technology, vaccines, gene editing and new medicines. Biomedical research will include molecular diagnostics and AI-assisted diagnosis, followed by organoids, 3D bioprinting, regenerative medicine and precision medicine.

The university expects the program to generate a substantial research portfolio. In 2026, it plans 63 projects in digital technology and AI, 54 in biology and microbiology, 50 in energy and materials, 10 in robotics and automation, eight in semiconductor chips, and eight in cybersecurity and quantum technology. The number of digital technology and AI projects is expected to rise to 72 in 2027. Approved programs already include AI in healthcare and public administration, as well as biotechnology research.