Jilin Hu is a tenure-track Assistant Professor in Department of Computer Science at Aalborg University. Prior to that, he was a Research Assocaite at Inception Institute of Artificial Intelligence (UAE) under the supervision of Prof. Jianbing Shen. He obtained the Ph.D. degree from Aalborg Unviersity in 2019, under the supervision of Prof. Christian S. Jensen and Prof. Bin Yang. From Oct. 2017 to April. 2018, he visited University of California, Berkeley under the supervision of Prof. Alexandre Bayen.
Research interest: Spatio-Temporal Data Management, Traffic Data Analysis, Graph Neural Network
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|May 11, 2022||Our paper “Evolutionary Clustering of Streaming Trajectories” receives ICDE 2022 Best Paper Award!|
|Mar 28, 2022||One paper is accepted by CVPR 2022!|
|Mar 23, 2022||Two papers are accepted by ICDE 2022!|
|Mar 7, 2022||One paper is accepted by Informations Sciences!|
(# Corresponding Author)
ICDEWeakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning - Extended Version2022
AAAIHyperverlet: A Symplectic Hypersolver for Hamiltonian Systems2022
IJCAIUnsupervised Path Representation Learning with Curriculum Negative SamplingIn Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI 2021, Virtual Event / Montreal, Canada, 19-27 August 2021 2021
ICDEStochastic Origin-Destination Matrix Forecasting Using Dual-Stage Graph Convolutional, Recurrent Neural NetworksIn 36th IEEE International Conference on Data Engineering, ICDE, Dallas, TX, USA, April 20-24 2020
ICDEStochastic Weight Completion for Road Networks Using Graph Convolutional NetworksIn 35th IEEE International Conference on Data Engineering, ICDE, Macao, China, April 8-11 2019
ISsResidual memory inference network for regression tracking with weighted gradient harmonized lossInformation Sciences 2022
GeoInformaticaEnabling time-dependent uncertain eco-weights for road networksGeoInformatica 2017
VLDBJRisk-aware path selection with time-varying, uncertain travel costs: a time series approachVLDB J. 2018