Research Themes

Building efficient, dependable intelligence for distributed systems.

Efficient AI Systems

Fast and fair large-language-model inference across heterogeneous edge resources, with a focus on speculative decoding and system-level efficiency.

Speculative decoding · LLM inference · Edge systems

Federated & Edge Learning

Collaborative learning under communication, privacy, and resource constraints, including communication-efficient adaptation and federated optimization.

Federated learning · Edge intelligence · Low-rank adaptation

Network Systems & Optimization

Scalable optimization for wireless and distributed systems, spanning coverage, connectivity, robust convergence, and resource-aware coordination.

Wireless networks · Distributed optimization · Resource allocation

Learning & Intelligent Agents

Predictive and multi-agent learning for dynamic environments, connecting time-series modeling, foundation models, and coordinated intelligent agents.

Prediction · Foundation models · Multi-agent learning

Research spanning algorithms, systems, and networked intelligence. QL / RESEARCH