I am pursuing my second Ph.D. degree at College of Information Sciences and Technology, Pennsylvania State University, supervised by Prof. Dongwon Lee. I received a Ph.D. degree in Computer Applied Technology at School of Computer and Control Engineering, University of Chinese Academy Sciences in 2018, supervised by Prof. Yong Shi and Prof. Philip S. Yu. Before that, I received my Bachelor degree in Software Engineering from Beijing Institute of Technology in June, 2013.

Research Interest

• AI in Cybersecurity: misinformation detection, fraud detection

• Healthcare: rare disease detection from EHR data

• Multi-modal: cross-modal retrieval, multi-modal embedding

FAQ (if you're interested)

1. How did you get into college at age 14?
   Short version: I was admitted to the Experimental Class for Exceptionally Gifted Children in Beijing No. 8 High School when I was 10 years old (acceptance rate<2%). Here's the introduction page (in Chinese). After 4 years of study, I went to college at age 14.
   Long version: See Section 6.1 in "Beijing Model of Gifted Education and Talent Development".
2. Why do you pursue another PhD degree?
   Because there is still a lot for me to learn and improve when I was graduated. And I want to embrace more possibilities in life.

Contact

You may reach out to me if you have a question about my research or you come from an underrepresented group and are interested in studying computer science. I'd be happy to help.

• Aug. 2018 – Present
  PIKE research group @ PSU, Research Assistant
  Research Topic: Misinformation detection.
  Supervisor: Prof. Dongwon Lee

  
  

• May. 2021 – Aug. 2021
  Amazon Search team (A9) @ Amazon, Applied Scientist Intern
  Research Topic: Active Learning on Graphs.
  Supervisor: Dr. Xianfeng Tang, Dr. Sumeet Katariya and Dr. Nikhil Rao

  
  

• Jun. 2020 – Sep. 2020
  AI Integrity team @ Facebook AI, Research Intern
  Research Topic: Multi-task leaning.
  Supervisor: Dr. Aaron Jaech and Dr. Hao Ma

  
  

• May. 2019 – Aug. 2019
  Analytics Center of Excellence @ IQVIA, Machine Learning Intern
  Research Topic: Rare disease detection from patient electronic health data.
  Supervisor: Dr. Cao (Danica) Xiao

  
  

• Sep. 2013 – June. 2018
  Research Center on Fictitious Economy & Data Science @ CAS, Research Assistant
  Research Topic: Weakly labeled learning with applications to computer vision.
  Supervisor: Prof. Yong Shi

  
  

• Oct. 2016 – Oct. 2017
  Big Data and Social Computing Lab @ UIC, Student Intern
  Research Topic: Heterogeneous data fusion and multi-view learning with applications to computer vision.
  Supervisor: Prof. Philip S. Yu

  
  

Conference Papers

• ALLIE: Active Learning on Large-scale Imbalanced Graphs
  Limeng Cui, Xianfeng Tang, Sumeet Katariya, Nikhil Rao, Pallav Agrawal, Karthik Subbian, Dongwon Lee
  The Web Conference (WWW), 2022

  
  

• DETERRENT: Knowledge Guided Graph Attention Network for Detecting Healthcare Misinformation
  Limeng Cui, Haeseung Seo, Maryam Tabar, Fenglong Ma, Suhang Wang, Dongwon Lee
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020 [Code][Video]

  
  

• CONAN: Complementary Pattern Augmentation for Rare Disease Detection
  Limeng Cui, Siddharth Biswal, Lucas Glass, Greg Lever, Jimeng Sun, Cao Xiao
  AAAI Conference on Artificial Intelligence (AAAI), 2020 [Paper][Code][Video]

  
  

• SAME: Sentiment-Aware Multi-modal Embedding for Detecting Fake News
  Limeng Cui, Suhang Wang, Dongwon Lee
  IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2019 [Code]

  
  

• dEFEND: Explainable Fake News Detection
  Kai Shu, Limeng Cui, Suhang Wang, Dongwon Lee, Huan Liu
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019 [Code]

  
  

• Multi-view Fusion through Cross-modal Retrieval
  Limeng Cui, Zhensong Chen, Jiawei Zhang, Lifang He, Yong Shi, Philip S. Yu
  IEEE International Conferenceon Image Processing (ICIP), 2018 [Code]

  
  

• Multi-view Collective Tensor Decomposition for Cross-modal Hashing (Oral)
  Limeng Cui, Zhensong Chen, Jiawei Zhang, Lifang He, Yong Shi, Philip S. Yu
  ACM International Conference on Multimedia Retrieval (ICMR), 2018 [Code]

  
  

• Real Time Social Attitude Expression Prediction
  Jiawei Zhang, Philip S. Yu, Charu C. Aggarwal, Limeng Cui
  BigData Congress, 2017

  
  

• Inverse extreme learning machine for learning with label proportions
  Limeng Cui, Jiawei Zhang, Zhensong Chen, Yong Shi, Philip S. Yu
  IEEE International Conference on Big Data (BigData), 2017 [Code]

  
  

• BL-ECD: Broad Learning based Enterprise Community Detection via Hierarchical Structure Fusion
  Jiawei Zhang, Limeng Cui, Philip S. Yu, Yuanhua Lv
  ACM International Conference on Information and Knowledge Management (CIKM), 2017

  
  

• BL-MNE: Emerging Heterogeneous Social Network Embedding Through Broad Learning with Aligned Autoencoder
  Jiawei Zhang, Congying Xia, Chenwei Zhang, Limeng Cui, Yanjie Fu, Philip S. Yu
  IEEE International Conference on Data Mining (ICDM), 2017

  
  

Journal Papers

• Learning from Label Proportions with Pinball Loss
  Yong Shi, Limeng Cui (Main Contributor), Zhensong Chen, Zhiquan Qi
  International Journal of Machine Learning and Cybernetics (IJMLC), 2019 [Code]

  
  

• Learning with label proportions based on nonparallel support vector machines
  Zhensong Chen, Zhiquan Qi, Bo Wang, Limeng Cui, Fan Meng, Yong Shi
  Knowledge Based Systems (KBS), 2017

  
  

• Automatic Road Crack Detection Using Random Structured Forests
  Yong Shi, Limeng Cui (Main Contributor), Zhiquan Qi, Fan Meng, Zhensong Chen
  IEEE Transactions on Intelligent Transportation Systems (T-ITS), (2016) [Code][Dataset]

  
  

Workshop and Demo Papers

• Cross-lingual COVID-19 Fake News Detection
  Jiangshu Du, Yingtong Dou, Congying Xia, Limeng Cui, Jing Ma, Philip S. Yu
  IEEE 21th International Conference on Data Mining Workshops (ICDMW), 2021 [Paper][Dataset]

  
  

• dEFEND: An Explainable Fake News Detection System
  Limeng Cui, Kai Shu, Suhang Wang, Dongwon Lee, Huan Liu
  ACM International Conference on Information and Knowledge Management (CIKM), 2019 (Demo)

  
  

• Laplacian SVM for Learning from Label Proportions
  Limeng Cui, Zhensong Chen, Fan Meng, Yong Shi
  IEEE 16th International Conference on Data Mining Workshops (ICDMW), 2016

  
  

• Pedestrian Detection Using Privileged Information
  Zhiquan Qi, Yingjie Tian, Lingfeng Niu, Fan Meng, Limeng Cui, Yong Shi
  IEEE 16th International Conference on Data Mining Workshops (ICDMW), 2015

  
  

• A hierarchy method based on LDA and SVM for news classification
  Limeng Cui, Fan Meng, Yong Shi, Minqiang Li, An Liu
  IEEE 16th International Conference on Data Mining Workshops (ICDMW), 2014

  
  

Miscellaneous

• CoAID: COVID-19 Healthcare Misinformation Dataset
  Limeng Cui, Dongwon Lee
  arXiv preprint, 2020 [Paper][Dataset]

  
  

• Warning Signs in Communicating the Machine Learning Detection Results of Misinformation with Individuals
  Limeng Cui
  arXiv preprint, 2019 [Paper][Supplementary]

  
  

• On Learning from Heterogeneous Data
  Limeng Cui
  PhD Dissertation, 2018 [Thesis][Proposal][Midterm][Defense]

  
  

• WiCyS Student Scholarship, 2022
• WiCyS Student Scholarship and Travel Stipend Award, 2021
• CRA-W Grad Cohort for Women, 2021
• KDD Student Registration Award, 2020
• GHC Student Scholarship, 2020
• IST Student Travel Award, 2020 Spring
• WiCyS Student Scholarship and Amazon AWS Travel Stipend Award, 2020
• AAAI Student Scholarship, 2020
• IST Student Travel Award, 2019 Fall
• KDD Student Travel Award, 2019
• CRA-W Grad Cohort for Women Travel Support, 2019
• Robert W. Graham Endowed Graduate Fellowship, 2018
• Scholarship of China Scholarship Council, 2016
• Outstanding student of UCAS, 2014
• Second Prize, Scholarship of BIT, 2013
• Honorable Mention, American Mathematical Contest in Modeling, 2012
• Second Prize, Scholarship of BIT, 2012

• Secretary, Gifted Class Alumni Association (GCAA), 2020 – Present
• Student at Large, Chinese Student Council (CSC) at Penn State, 2020 – Present