Tianqi Li

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About

Tianqi Li is a researcher advancing the frontiers of multiagent systems and distributed sensing, with a primary focus on consensus-based multi-target tracking and autonomous control. His most-cited work, "Optimizing Consensus-based Multi-target Tracking with Multiagent Rollout Control Policies" (2021, 8 citations), introduces a pioneering distributed control strategy for robotic fleets operating under connectivity constraints. In this paper, Li develops an information-driven approach where each agent independently performs local computations using consensus-based fusion, then executes a rollout policy to optimize collective sensing value. This work addresses a critical challenge in multiagent robotics: enabling decentralized decision-making that maximizes tracking performance without requiring centralized coordination. Li's contributions are particularly significant for applications in environmental monitoring, surveillance, and search-and-rescue operations, where robust, scalable multi-target tracking is essential. By bridging consensus algorithms with rollout control policies, he provides a practical framework for deploying autonomous sensor networks in real-world scenarios. His research demonstrates how individual agent-level optimization can achieve near-global performance in complex multi-target environments, marking an important step toward truly autonomous, cooperative robotic systems.