Scholar
Lecheng Zheng
Google Scholar ID: Lp09wUoAAAAJ
University of Illinois at Urbana-Champaign
Citations & Impact
Citations
584
H-index
12
i10-index
15
Publications
20
Co-authors
13
list available
Publications
Resume (English only)
Academic Achievements
- - Publications:
- - One paper accepted by ICDM 2025
- - Two papers accepted by CIKM 2025
- - One paper "Cluster Aware Graph Anomaly Detection" accepted @ WWW’25 as an oral presentation
- - One paper "DrGNN: Deep Residual Graph Neural Network with Contrastive Learning" accepted @ TMLR'24
- - One paper "Multi-label Sequential Sentence Classification via Large Language Model" accepted @ EMNLP’24
- - One paper "Heterogeneous Contrastive Learning for Foundation Models and Beyond" accepted @ KDD’24
- - One paper "MULAN: Multi-modal Causal Structure Learning and Root Cause Analysis for Microservice Systems" accepted @ WWW’24
- - One paper "FairGen: Towards Fair Graph Generation" accepted @ ICDE’24
- - One paper "Fairness-aware multi-view clustering" accepted @ SDM’23
- - One paper "MentorGNN: Deriving Curriculum for Pre-Training GNNs" accepted @ CIKM’22
- - One paper "Contrastive learning with complex heterogeneity" accepted @ KDD’22
- - One paper "Outlier impact characterization for time series data" accepted @ AAAI’22
- - One paper "Deep co-attention network for multi-view subspace learning" accepted @ WWW’21
- - Conference Papers:
- - Bi-NAS: The IEEE International Conference on Data Mining 2025
- - PyG-SSL: CIKM 2025
- - ClimateBench-M: CIKM 2025
Research Experience
- - NEC Search, Princeton, NJ
- - Research Intern • May 2023 - Aug 2023
- - Project: Multi-modal Root Cause Analysis
- - Achievements: One paper accepted at WWW'24 (Oral). Two in submission.
- - Main Advisors: Dr. Zhengzhang Chen and Dr. Haifeng Chen
Education
- - Ph.D.: 2019 - 2025, University of Illinois at Urbana–Champaign (UIUC), Department of Computer Science, Advisor: Prof. Jingrui He
- - B.S.: 2012 - 2016, University of Kansas, Department of Electrical Engineering and Computer Science, Advisor: Prof. Luke Huan
Background
- - Research Interests: Enhancing the trustworthiness and efficiency of machine learning algorithms, covering multi-modal fusion, multi-label/multi-task learning, missing value imputation, graph generation, bias, fairness, robustness, and transferability, graph anomaly detection, graph oversmoothing.
- - Field: Computer Science
- - Introduction: Currently a Ph.D. student at the Department of Computer Science, University of Illinois at Urbana–Champaign.
Miscellany
- - Personal Interests: Feel free to drop me an e-mail if you are interested in my research and want to discuss relevant research topics or potential collaborations
