People

The team behind Agentivium AI.

Agentivium AI is led by a research lead, advised by faculty, and supported by student researchers working across agent-native systems and real-world testbeds.

Leadership

Hoang Le Hai Thanh

Hoang Le Hai Thanh

Research LeadAgentivium AI, Ho Chi Minh City University of Technology

Founder and Research Lead of Agentivium AI. Focused on building the scientific and engineering foundations of agent-native intelligent infrastructure for the 5.0 era.

Research Interests

Agent-native infrastructureMulti-agent orchestrationTrustworthy agentic systemsAutonomous execution

Advisor

Assoc.Prof. Nam Thoai

Assoc.Prof. Nam Thoai

Faculty Advisor

Associate Professor at HCMUT. Founder and director of the High-Performance Computing Lab, researching High-Performance Computing, Big Data Analytics, Artificial Intelligence, Cloud computing, and network protocols.

Research Interests

High-Performance ComputingBig Data AnalyticsArtificial IntelligenceCloud Computing

Student Research Leads

Nguyen Tuan Huy

Nguyen Tuan Huy

Student Research Lead

Focuses on designing local control memory architectures for Orchestrator Agents in Multi-Agent Systems. His research aims to improve agent coordination by treating memory not just as a shared data store, but as a dynamic control substrate. This memory directly supports the orchestrator in making intelligent scheduling decisions, selecting context, enforcing access controls, and adapting based on execution history across task episodes.

Research Interests

Multi-Agent OrchestrationAgentic Memory ArchitecturesAdaptive SchedulingProcedural Control Systems

Project

Local Control Memory for MAS Orchestrators
Nguyen Phuc Nhan

Nguyen Phuc Nhan

Student Research Lead

Focuses on runtime optimization for multi-agent execution across distributed clusters. His research addresses how the runtime should intelligently spawn, place, scale, or cancel sub-agents to simultaneously optimize answer quality, latency, and execution cost, while strictly respecting shared-context constraints and reduction needs of agent workflows.

Research Interests

Distributed Agent RuntimesScalable Multi-Agent ExecutionCluster Resource OptimizationWorkflow Scheduling

Project

Distributed Runtime for Multi-Agent Workflows

Alumni

Alumni will be listed here as the research program matures.

Join the Team

Interested in agent-native infrastructure research?