Caihua Shan

I'm now looking for prospective student interns (more than 3 months) to work together on graph neural networks. Please drop me an email with your resume if you are interested.

Short Bio:

I am currently a researcher in Microsoft Research Asia. I received my Ph.D. degree from the University of Hong Kong supervised by Dr. Reynold Cheng and Prof. Nikos Mamoulis in Jan 2020. I obtained my B.S. degree from Zhejiang University in June 2015.

Research Interests:

• Learning-based database and data mining

• Graph neural network and its applications

Publications:

• Xiaodong Li, Reynold Cheng, Kevin Chang, Caihua Shan, Chenhao Ma, Hongtai Cao, "On Analyzing Graphs with Motif-Paths", VLDB 2021

• Xiang Li, Ben Kao, Caihua Shan, Dawei Yin, Martin Ester, "CAST: A Correlation-based Adaptive Spectral Clustering Algorithm on Multi-scale Data", KDD 2020

• Caihua Shan, Leong Hou U, Nikos Mamoulis, Reynold Cheng, "A Toolkit for Managing Multiple Crowdsourced Top-K Queries", CIKM Demo 2020

• Caihua Shan, Nikos Mamoulis, Reynold Cheng, Guoliang Li, Xiang Li, Yuqiu Qian, "An End-to-End Deep RL Framework for Task Arrangement in Crowdsourcing Platforms", ICDE 2020

• Caihua Shan, Leong Hou U, Nikos Mamoulis, Reynold Cheng, Xiang Li, "A General Early-Stopping Module for Crowdsourced Ranking", DASFAA 2020

• Caihua Shan, Nikos Mamoulis, Guoliang Li, Reynold Cheng, Zhipeng Huang, Yudian Zheng, "A Crowdsourcing Framework for Collecting Tabular Data", TKDE 2019

• Caihua Shan, Nikos Mamoulis, Guoliang Li, Reynold Cheng, Zhipeng Huang, Yudian Zheng, "T-Crowd: Effective Crowdsourcing for Tabular Data", ICDE 2018

• Yudian Zheng, Guoliang Li, Yuanbing Li, Caihua Shan, Reynold Cheng, "Truth Inference in Crowdsourcing: Is the Problem Solved?", VLDB 2017

Manuscript:

• Danhao Ding, Xiang Li, Caihua Shan, Nikos Mamoulis, Ben Kao, Yizhou Sun, "Semi-supervised Classification in Heterogeneous Information Networks with Graph Convolution"

• Xiang Li, Danhao Ding, Ben Kao, Caihua Shan, Zhaochun Ren, "A Hierarchical and Joint Generative Model for Attributed Network Embedding"

Academic Service:

• Program Committee: WISE2019

• Invited Reviewer: TKDE, KAIS

• Invited External Reviewer: ICDE2020, DASFAA2020, CIKM2019, KDD2019, DASFAA2018, SUM2018, SSTD2019, CIKM2018, SIGSPATIAL2016, HCOMP2016, DASFAA2016

Last update: 25 Mar, 2021