Jie Feng

Orcid: 0000-0003-3279-7117

Affiliations:
  • Tsinghua University, Department of Electronic Engineering, BNRist, Beijing, China


According to our database1, Jie Feng authored at least 38 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Online presence:

On csauthors.net:

Bibliography

2024
History-enhanced and Uncertainty-aware Trajectory Recovery via Attentive Neural Network.
ACM Trans. Knowl. Discov. Data, April, 2024

TrajAgent: An Agent Framework for Unified Trajectory Modelling.
CoRR, 2024

AgentMove: Predicting Human Mobility Anywhere Using Large Language Model based Agentic Framework.
CoRR, 2024

UrbanWorld: An Urban World Model for 3D City Generation.
CoRR, 2024

CityBench: Evaluating the Capabilities of Large Language Model as World Model.
CoRR, 2024

Harvesting Efficient On-Demand Order Pooling from Skilled Couriers: Enhancing Graph Representation Learning for Refining Real-time Many-to-One Assignments.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

2023
GODDAG: Generating Origin-Destination Flow for New Cities Via Domain Adversarial Training.
IEEE Trans. Knowl. Data Eng., October, 2023

Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution.
ACM Trans. Knowl. Discov. Data, January, 2023

Inferring Origin-Destination Flows From Population Distribution.
IEEE Trans. Knowl. Data Eng., 2023

Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environment.
CoRR, 2023

2022
DeepMM: Deep Learning Based Map Matching With Data Augmentation.
IEEE Trans. Mob. Comput., 2022

DeepFlowGen: Intention-Aware Fine Grained Crowd Flow Generation via Deep Neural Networks.
IEEE Trans. Knowl. Data Eng., 2022

User Identity Linkage via Co-Attentive Neural Network From Heterogeneous Mobility Data.
IEEE Trans. Knowl. Data Eng., 2022

Predicting Human Mobility With Semantic Motivation via Multi-Task Attentional Recurrent Networks.
IEEE Trans. Knowl. Data Eng., 2022

Context-aware Spatial-Temporal Neural Network for Citywide Crowd Flow Prediction via Modeling Long-range Spatial Dependency.
ACM Trans. Knowl. Discov. Data, 2022

Crowd Flow Prediction for Irregular Regions with Semantic Graph Attention Network.
ACM Trans. Intell. Syst. Technol., 2022

2021
3DGCN: 3-Dimensional Dynamic Graph Convolutional Network for Citywide Crowd Flow Prediction.
ACM Trans. Knowl. Discov. Data, 2021

Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution.
CoRR, 2021

Vehicle Trajectory Recovery on Road Network Based on Traffic Camera Video Data.
Proceedings of the SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems, 2021

One-shot Transfer Learning for Population Mapping.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

AttnMove: History Enhanced Trajectory Recovery via Attentional Network.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
DeepApp: Predicting Personalized Smartphone App Usage via Context-Aware Multi-Task Learning.
ACM Trans. Intell. Syst. Technol., 2020

Semantic-aware Spatio-temporal App Usage Representation via Graph Convolutional Network.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2020

PMF: A Privacy-preserving Human Mobility Prediction Framework via Federated Learning.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2020

Learning to Simulate Human Mobility.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

A Sequential Convolution Network for Population Flow Prediction with Explicitly Correlation Modelling.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
Understanding Metropolitan Crowd Mobility via Mobile Cellular Accessing Data.
ACM Trans. Spatial Algorithms Syst., 2019

DPLink: User Identity Linkage via Deep Neural Network From Heterogeneous Mobility Data.
Proceedings of the World Wide Web Conference, 2019

Deep learning models for population flow generation from aggregated mobility data.
Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers, 2019

DeepMM: Deep Learning Based Map Matching with Data Augmentation.
Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019

Learning Phase Competition for Traffic Signal Control.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

DeepDPM: Dynamic Population Mapping via Deep Neural Network.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

DeepSTN+: Context-Aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
A Bimodal Model to Estimate Dynamic Metropolitan Population by Mobile Phone Data.
Sensors, 2018

DeepTP: An End-to-End Neural Network for Mobile Cellular Traffic Prediction.
IEEE Netw., 2018

Uniqueness in the City: Urban Morphology and Location Privacy.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2018

DeepMove: Predicting Human Mobility with Attentional Recurrent Networks.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018


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