Lanyu Shang

Lanyu Shang

Doctoral Student

PhD, Information Sciences, Illinois (in progress)

MS, Data Science, New York University

BS, Applied Mathematics, University of California - Los Angeles

Research focus

My research interest lies in social sensing, machine learning, natural language processing, and network science. I am particularly interested in social media based data mining and analysis, such as multimodal misinformation detection on social media and multimodal information retrieval.

Honors and Awards

  • Outstanding Graduate Student Teaching Award, University of Notre Dame, 2020
  • Student Travel Award, IEEE BigData, 2019
     

Advisor

Publications & Papers

Shang, L., Zhang, D. Y., Shen, J., Marmion, E. L., & Wang, D. (2021). CCMR: A Classic-enriched Connotation-aware Music Retrieval System on Social Media with Visual Inputs. Social Network Analysis and Mining, 11(1), 1-14.

Zhang, Y., Shang, L., Zong, R., Wang, Z., Kou, Z., & Wang, D. (2021, October). StreamCollab: A Streaming Crowd-AI Collaborative System to Smart Urban Infrastructure Monitoring in Social Sensing. In Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (Vol. 9, pp. 179-190).

Shang, L., Youn, C., Zha, Y., Zhang, Y., & Wang, D. (2021, September). KnowMeme: A Knowledge-enriched Graph Neural Network Solution to Offensive Meme Detection. In 2021 IEEE 17th International Conference on eScience (eScience) (pp. 186-195). IEEE.

Kou, Z., Zhang, Y., Shang, L., & Wang, D. (2021, June). FairCrowd: Fair Human Face Dataset Sampling via Batch-Level Crowdsourcing Bias Inference. In 2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS) (pp. 1-10). IEEE.

Kou, Z., Zhang, D. Y., Shang, L., & Wang, D. (2020, December). ExFaux: A Weakly Supervised Approach to Explainable Fauxtography Detection. In 2020 IEEE International Conference on Big Data (Big Data) (pp. 631-636). IEEE.

Shang, L., Yue, Z. D., Karim, K. S., Shen, J., & Wang, D. (2020, December). CaMR: Towards Connotation-aware Music Retrieval on Social Media with Visual Inputs. In 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 425-429). IEEE.

Shang, L., Zhang, Y., Zhang, D., & Wang, D. (2020). Fauxward: a graph neural network approach to fauxtography detection using social media comments. Social Network Analysis and Mining, 10(1), 1-16.

Shang, L., Zhang, D. Y., Wang, M., & Wang, D. (2019, December). VulnerCheck: a content-agnostic detector for online hatred-vulnerable videos. In 2019 IEEE International Conference on Big Data (Big Data) (pp. 573-582). IEEE.

Shang, L., Zhang, D. Y., Wang, M., Lai, S., & Wang, D. (2019). Towards reliable online clickbait video detection: A content-agnostic approach. Knowledge-Based Systems, 182, 104851.

Zhang, D. Y., Shang, L., Geng, B., Lai, S., Li, K., Zhu, H., ... & Wang, D. (2018, December). Fauxbuster: A content-free fauxtography detector using social media comments. In 2018 IEEE International Conference on Big Data (Big Data) (pp. 891-900). IEEE.