Jieting Lian

New York University

Papers

1

Total Citations

17

H-Index

1

About

Dr. Jieting Lian is a leading researcher at the intersection of robotics and artificial intelligence, with a primary focus on developing intelligent navigation and obstacle avoidance systems for dynamic environments. Her most impactful work introduces a novel deep reinforcement learning algorithm specifically designed for mobile robots operating in complex warehouse settings. By enhancing the value function network to account for pedestrian interactions, Dr. Lian’s approach enables robots to learn the relative importance of current and historical states, significantly improving real-time decision-making and safety. This pioneering contribution, detailed in her highly cited 2024 paper, has already garnered 17 citations, reflecting its immediate relevance to the logistics and automation sectors. Dr. Lian’s research not only advances the theoretical foundations of reinforcement learning but also offers practical solutions for the growing demand for autonomous material handling. Her work is essential reading for students and engineers seeking to bridge the gap between algorithmic innovation and real-world robotic applications in crowded, industrial spaces.

Research Focus

Key Achievements

1
H-Index
1
Papers
17
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments
17 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: New York University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago