ASU Ira A. Fulton Schools of Engineering
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Lu Cheng CV


Incoming Assistant Professor in Computer Science, University of Illinois Chicago (UIC)
Email: lcheng35 (at) asu (dot) edu
Phone: (518) 833-2246
Office: 561AB, Brickyard Engineering,
699 S Mill Ave, Tempe, AZ 85281

Research Interests

Socially Responsible AI,
Data Mining, Causal Learning,
AI for Good, Social Computing

Education

  • Ph.D. in Computer Science, 2022
    Arizona State University

  • M.Eng. in Industrial Engineering, 2017
    Rensselaer Polytechnic Institute

  • B.Eng. in Systems Engineering, 2015
    Huazhong University of Science & Technology


About Me

Lu Cheng will be a tenure-track Assistant Professor in the Department of Computer Science at University of Illinois Chicago (UIC) starting in Fall 2022. Lu received her PhD degree in Computer Science at Arizona State University (ASU) in 2022 advised by Dr. Huan Liu, M.Eng. degree in Industrial Engineering at Rensselaer Polytechnique Institute (RPI), and B.Eng. degree in Industrial Engineering at Huazhong University of Science & Technology (HUST). Her research interests are broadly in data mining and machine learning, with a particular focus on socially responsible AI, social computing, causal machine learning, and AI for social good.

I am actively looking for self-motivated students (PhD/Master/Undergraduate/Intern) to conduct research in socially responsible AI (fairness, interpretability/explainability, privacy, robustness, domain generalization), causal machine learning, and social media mining. Interested students please feel free to send me an email at lucheng.recuit@gmail.com with your CV and transcript.

Tutorials

  1. Socially Responsible AI for Data Mining: Theories and Practice [slides]
    Lu Cheng, Fred Morstatter, H. V. Jagadish, and Huan Liu
    SDM 2022.
  2. Socially Responsible AI Algorithms: Issues, Purposes, and Challenges [slides]
    Lu Cheng, Fred Morstatter, and Huan Liu
    SBP-BRiMS. 2021.

Invited Talks & Panels

  1. Advancing Cyberbullying Detection with Psychological Insights and Complex Media Data
    AI For Mankind 2022
  2. Causal Understanding of Fake News Dissemination on Social Media
    Tsinghua University AI TIME 2021
  3. Combating Cyberbullying and Disinformation on Social Media: The Roles of Socially Responsible AI
    PhD Research Talk at IJCAI MAISoN 2021
  4. Socially Responsible AI Algorithms: Issues, Purposes, and Challenges
    NSF REU Program at University of North Texas 2021
  5. My experience of publishing the first research papers
    DMML Group Meeting 2021

Publications

Arxiv and Preprints
  1. A Survey on Echo Chambers on Social Media: Description, Detection and Mitigation [pdf]
    Faisal Alatawi, Lu Cheng, Anique Tahir, Mansooreh Karami, Bohan Jiang, Tyler Black, Huan Liu
    ArXiv. 2021.
Accepted papers
  1. Bias Mitigation for Toxicity Detection via Sequential Decisions [pdf]
    Lu Cheng, Ahmadreza Mosallanezhad, Yasin Silva, Deborah Hall, and Huan Liu
    In the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). Madrid. July 11-15, 2022.
  2. Evaluation Methods and Measures for Causal Learning Algorithms [pdf]
    Lu Cheng, Ruocheng Guo, Raha Moraffah, Paras Sheth, K. Selcuk Candan, and Huan Liu
    In IEEE Transactions on Artificial Intelligence (TAI). 2022.
  3. Learning Privacy-Preserving Graph Convolutional Network with Partially Observed Sensitive Attributes [pdf] [code]
    Hui Hu, Lu Cheng, Jayden Parker Vap, and Mike Borowczak
    In Proceedings of the ACM 2022 International World Wide Web Conferences (TheWebConf). Lyon, France. April 25-29. 2022.
  4. Causal Mediation Analysis with Hidden Confounders [pdf]
    Lu Cheng, Ruocheng Guo, and Huan Liu
    In Proceedings of the 2022 ACM International Conference on Web Search and Data Mining (WSDM). Online Virtual Event. Feb. 21-25. 2022.
  5. Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies [pdf]
    Lu Cheng, Ruocheng Guo, and Huan Liu
    In Proceedings of the 2022 ACM International Conference on Web Search and Data Mining (WSDM). Online Virtual Event. Feb. 21-25. 2022.
  6. Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication [pdf] [data]
    Lu Cheng, Ruocheng Guo, Kasim Selcuk Candan, and Huan Liu
    In Proceedings of the 16th International AAAI Conference on Web and Social Media (ICWSM). Atlanta, Georgia. June 6-9. 2022.
  7. Learning Shared Mobility-aware Knowledge for Multiple Urban Travel Demands [pdf]
    Qianru Wang, Bin Guo; Yi Ouyang, Lu Cheng, Liang Wang, Zhiwen Yu, and Huan Liu
    IEEE Internet of Things Journal. 2021.
  8. Mechanisms and Attributes of Echo Chambers in Social Media [pdf]
    Bohan Jiang, Mansooreh Karami, Lu Cheng, Tyler Black, and Huan Liu
    SBP-BRiMS Working Paper. 2021.
  9. Socially Responsible AI Algorithms: Issues, Purposes, and Challenges [pdf]
    Lu Cheng, Kush R. Varshney, and Huan Liu
    Journal of Artificial Intelligence Research. 2021.
  10. Causal Understanding of Fake News Dissemination on Social Media [pdf] [code]
    Lu Cheng, Ruocheng Guo, Kai Shu, and Huan Liu
    In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’21). Online Virtual Event. August 14-18, 2021.
  11. Mitigating Bias in Session-based Cyberbullying Detection: A Non-Compromising Approach [pdf] [code]
    Lu Cheng*, Ahmadreza Mosallanezhad*, Yasin Silva, Deborah Hall, and Huan Liu
    In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL), Bangkok, Thailand. August 1-6, 2021.
  12. Causal Learning for Socially Responsible AI [pdf]
    Lu Cheng, Ahmadreza Mosallanezhad*, Paras Sheth*, and Huan Liu
    In Proceedings of the 2021 International Joint Conferences on Artificial Intelligence (IJCAI2021), August 21-26, Montreal, Canada.
  13. Automated Meta-Analysis in Medical Research: A Causal Learning Perspective [poster]
    Lu Cheng, Dmitriy Katz-rogozhnikov, Ioana Baldini, and Kush R. Varshney
    In the 2021 ACM Conference on Health, Inference, and Learning Workshop. April 8-9, 2021.
  14. Improving Cyberbullying Detection with User Interaction [pdf] [code]
    Suyu Ge, Lu Cheng, and Huan Liu
    In Proceedings of the 2021 International World Wide Web Conference, Ljubljana, Slovenia. April 19-23, 2021.
  15. Modeling Temporal Patterns of Cyberbullying Detection with Hierarchical Attention Networks [pdf] [code]
    Lu Cheng, Ruocheng Guo, Yasin Silva, Deborah Hall, and Huan Liu
    ACM/IMS Transactions on Data Science. 2021.
  16. Long-Term Effect Estimation with Surrogate Representation [pdf] [code]
    Lu Cheng, Ruocheng Guo, and Huan Liu
    In Proceedings of the 2021 ACM International Conference on Web Search and Data Mining (WSDM), Online, March 08-12, 2021.
  17. Session-based Cyberbullying Detection: Problems and Challenges [pdf]
    Lu Cheng, Yasin Silva, Deborah Hall, and Huan Liu
    IEEE Internet Computing, Special Issue on Cyber-Social Health: Promoting Good and Countering Harm on Social Media, 2021
  18. Unsupervised Cyberbullying Detection via Time-Informed Gaussian Mixture Model [pdf] [code]
    Lu Cheng, Kai Shu, Siqi Wu, Yasin N. Silva, Deborah Hall, and Huan Liu
    In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM'20), Oct. 19-23, 2020, Online.
  19. BullyBlocker: Integrating Data, Computer, and Psychological Science to Identify Cyberbullying on Social Media [poster]
    Brittany Wheeler, Lu Cheng, Deborah Hall, and Yasin N. Silva
    In 2020 Women in Statistics and Data Science Conference (WSDS'20), Oct. 01-03, 2020, Pittsburgh Marriott City Center, Pittsburgh, PA, USA.
  20. A Survey of Learning Causality with Data: Problems and Methods [pdf]
    Ruocheng Guo, Lu Cheng, Jundong Li, P. Richard Hahn, and Huan Liu
    In ACM Computing Surveys (CSUR'20).
  21. Representation Learning for Imbalanced Cross-Domain Classification [pdf]
    Lu Cheng, Ruocheng Guo, K.S. Candan, and Huan Liu
    In Proceedings of the 2020 SIAM International Conferene on Data Mining (SDM'20), May 07-09, 2020, Cincinnati, Ohio, USA.
  22. Tracking Disaster Footprints with Social Stream Data [pdf]
    Lu Cheng, Jundong Li, K.S. Candan, and Huan Liu
    In Proceedings of 34th AAAI Conference on Artificial Intelligence (AAAI'20), Feb. 07-12, 2020, New York, New York, USA.
  23. A Practical Data Repository for Causal Learning with Big Data [pdf] [slides]
    Lu Cheng, Ruocheng Guo*, Raha Moraffah*, K.S. Candan, Adrienne Raglin, and Huan Liu
    In Proceedings of the 2019 BenchCouncil International Symposium on Benchmarking, Measuring and Optimizing (Bench'19), Nov. 14-16, 2019, Denver, Colorado, USA.
  24. PI-Bully: Personalized Cyberbullying Detection with Peer Influence [pdf]
    Lu Cheng, Jundong Li, Yasin N. Silva, Deborah Hall, and Huan Liu
    In Proceedings of the 2019 International Joint Conferences on Artificial Intelligence (IJCAI2019), Aug. 10-16, Macao, China.
  25. Robust Cyberbullying Detection with Causal Interpretation [pdf] [slides]
    Lu Cheng, Ruocheng Guo, and Huan Liu
    In Proceedings of the WWW'19 CyberSafety Workshop, May 13-17, San Francisco, U.S.
  26. Hierarchical Attention Networks for Cyberbullying Detection on the Instagram Social Network [pdf] [slides] [media coverage]
    Lu Cheng, Ruocheng Guo, Yasin N. Silva, Deborah Hall, and Huan Liu
    In Proceedings of the 2019 SIAM International Conferene on Data Mining (SDM19), Calgary, Cananda, May 2-4, 2019
  27. XBully: Cyberbullying Detection within a Multi-Modal Context. [pdf]
    Lu Cheng, Jundong Li, Yasin N. Silva, Deborah Hall, and Huan Liu
    In Proceedings of the 2019 ACM International Conference on Web Search and Data Mining (WSDM), Melbourne, Australia, Feb 11-15, 2019
  28. Personazlied Learning for Cyberbullying Detection [pdf]
    Lu Cheng, Yasin N. Silva, Deborah Hall, and Huan Liu
    SBP-BRiMS Doctoral Consortium, 2018.
  29. A Multi-objective Immune Genetic Algorithm for Project Scheduling on Multi-skill Resources
    Lu Cheng, Guangrui Liao, Zhenyuan Liu
    Applied Mechanics and Materials. 2014, Vol. 719-720, p1268-1274. 7p.
Peer-reviewed Posters (with poster papers or abstracts)
  1. BullyBlocker: Integrating Data, Computer, and Psychological Science to Identify Cyberbullying on Social Media
    B. Wheeler, L. Cheng, D. Hall, and Y. N. Silva
    The 2020 Women in Statistics and Data Science Conference (WSDS), 2020.
  2. An interdisciplinary investigation of temporal aspects of cyberbullying on Instagram
    W. Yang, L. Cheng, K. Schodt, C. Shao, D. Hall, and Y. N. Silva
    The Annual Meeting of the Society for Personality & Social Psychology (SPSP), Portland, OR, USA, 2019.
  3. An Interdisciplinary Investigation of Temporal Aspects of Cyberbullying
    L. Jiang, A. Trow, V. Delgadillo, C. Sanchez, L. Cheng, Y. Silva, D. Hall.
    The Western Psychological Association (WPA) Convention, Portland, OR, USA, 2018.
  4. BullyBlocker: Detecting Cyberbullying Victimization Risk through an Interdisciplinary Identification Model
    A. Trow, L. Jiang, L. Cheng, C. Sanchez, V. Delgadillo, D. Hall, Y. Silva.
    The Western Psychological Association (WPA) Convention, Portland, OR, USA, 2018.

Work Experience

Services

Conference Organizer

Senior Program Committee

Conference Program Committee

Conference External Reviewer

Journal Reviewer

Book Proposal Reviewer

Mentoring

Group Member

Volunteer

Honors

Extracurricular Activity

Running, Badminton, Cooking, Movies