Qiangxing Tian

Westlake University, Hangzhou City University

Papers

Total Citations

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About

Qiangxing Tian is a rising researcher at the intersection of artificial intelligence and human-machine interaction, with key contributions in deep reinforcement learning and wearable sensing technology. His work primarily focuses on skill discovery and transfer in reinforcement learning, where he has developed novel approaches to enable agents to learn and combine primitive skills without extrinsic rewards. His 2020 paper "Independent Skill Transfer for Deep Reinforcement Learning" (10 citations) introduced methods for transferring diverse primitive skills learned through entropy-based intrinsic rewards, addressing a fundamental challenge in high-level skill acquisition. Building on this, his 2021 work "Unsupervised Discovery of Transitional Skills for Deep Reinforcement Learning" (7 citations) tackled the critical problem of smooth skill transitions when using multiple consecutive skills for task completion. Most recently, Tian has expanded into hardware innovation with "A Self-Powered Smart Glove Based on Triboelectric Sensing for Real-Time Gesture Recognition and Control" (2025, 2 citations), presenting a novel, self-powered human-machine interface that overcomes limitations of complex fabrication and external power dependency. This work demonstrates his ability to bridge algorithmic advances with practical applications, offering promising directions for virtual interaction and robotic control.