Kun Qian

Orcid: 0000-0002-9063-102X

Affiliations:
  • University of Texas at Austin, Department of Civil, Architectural, and Environmental Engineering, Austin, TX, USA


According to our database1, Kun Qian authored at least 15 papers between 2019 and 2026.

Collaborative distances:

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Multiagent Online Source Seeking Against Nonstochastic Disturbances.
IEEE Trans. Autom. Control., June, 2026

PAVE: A Cognitive Architecture for Legitimate Violation in Generative Agent Societies.
CoRR, May, 2026

EgoTraj: Real-World Egocentric Human Trajectory Dataset for Multimodal Prediction.
CoRR, May, 2026

2024
Unleashing the Power of LLMs as Multi-Modal Encoders for Text and Graph-Structured Data.
CoRR, 2024

Covering a Graph with Dense Subgraph Families, via Triangle-Rich Sets.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
Multiagent Online Source Seeking Using Bandit Algorithm.
IEEE Trans. Autom. Control., May, 2023

Learning to Seek: Multi-Agent Online Source Seeking Against Non-Stochastic Disturbances.
CoRR, 2023

ForeSeer: Product Aspect Forecasting Using Temporal Graph Embedding.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Parallelized Active Information Gathering Using Multisensor Network for Environment Monitoring.
IEEE Trans. Control. Syst. Technol., 2022

Jacobi-Style Iteration for Distributed Submodular Maximization.
IEEE Trans. Autom. Control., 2022

2021
Multi-Robot Dynamical Source Seeking in Unknown Environments.
CoRR, 2021

Multi-Robot Dynamical Source Seeking in Unknown Environments.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020
Real-time mobile sensor management framework for city-scale environmental monitoring.
J. Comput. Sci., 2020

Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Physics Informed Data Driven model for Flood Prediction: Application of Deep Learning in prediction of urban flood development.
CoRR, 2019


  Loading...