Research output per year
Research output per year
Personal profile
About
Professor Lanyu Shang earned her Ph.D. in information sciences from the University of Illinois Urbana-Champaign. Prior to this, she received an M.S. in Data Science from New York University and a B.S. in Applied Mathematics from the University of California, Los Angeles. Her research interest lies in human-centric AI, human-AI collaboration, social media analysis, AI for social good, and applied AI. Her work has been published in top venues in data mining and machine learning/AI, such as The WebConf, ICWSM, AAAI, IJCAI, and IEEE Big Data. She is also the recipient of the Best Paper Award at ACM/IEEE ASONAM 2022, the Best Paper Honorable Mention at IEEE SmartComp 2022, the Outstanding Graduate Student Teaching Award from the University of Notre Dame, and the N2Women Young Researcher Fellowship.
Education/Academic qualification
Data Sciences, M.S., New York University
Applied Mathematics, B.S., University of California Los Angeles
Information Sciences, Ph.D., University of Illinois Urbana-Champaign
Disciplines
- Computer Sciences
-
Bidirectional Human-AI Collaboration for Equitable Student Performance Prediction via Deep Uncertainty Learning
Zong, R., Zhang, Y., Shang, L., Stinar, F., Bosch, N. & Wang, D., 2025, Proceedings of the 34th International Joint Conference on Artificial Intelligence, IJCAI 2025. Kwok, J. (ed.). International Joint Conferences on Artificial Intelligence, p. 10026-10034 9 p. (IJCAI International Joint Conference on Artificial Intelligence).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
-
ClimateMiSt: Climate Change Misinformation and Stance Detection Dataset
Choi, Y. J., Wang, D. & Shang, L., 2025, Social Networks Analysis and Mining - 16th International Conference, ASONAM 2024, Proceedings. Aiello, L. M., Chakraborty, T. & Gaito, S. (eds.). Springer Science and Business Media Deutschland GmbH, p. 321-330 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 15212 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
-
Combining Group Contribution Method and Semisupervised Learning to Build Machine Learning Models for Predicting Hydroxyl Radical Rate Constants of Water Contaminants
Liu, Z., Huang, K., Yue, Z., Han, A. Y., Wang, D., Zhang, H. & Shang, L., Jan 14 2025, In: Environmental Science and Technology. 59, 1, p. 857-868 12 p.Research output: Contribution to journal › Article › peer-review
-
Designing Effective AI Explanations for Misinformation Detection: A Comparative Study of Content, Social, and Combined Explanations
Gong, Y., Liu, Y., Shang, L., Wei, N. & Wang, D., Oct 16 2025, In: Proceedings of the ACM on Human-Computer Interaction. 9, 7, CSCW396.Research output: Contribution to journal › Article › peer-review
Open Access -
MultiTec: A Data-Driven Multimodal Short Video Detection Framework for Healthcare Misinformation on TikTok
Zhang, Y., Deng, Y., Wang, D. & Shang, L., 2025, In: IEEE Transactions on Big Data. 11, 5, p. 2471-2488 18 p.Research output: Contribution to journal › Article › peer-review
Open Access
Press/Media
-
New book provides roadmap for designing human-centered AI systems
9/25/25 → 9/28/25
2 items of Media coverage
Press/Media: Research
-
New Publication Offers Blueprint for Creating Human-Centric AI Systems
9/25/25
2 items of Media coverage
Press/Media: Research
-
Developing Human-Centric AI Models to Understand Social Impact of Environmental Hazards and Health Crisis Misinformation
12/5/24
1 item of Media coverage
Press/Media: Research
-
New approach to detect misinformation in an emergent health domain on social media
12/13/22
1 item of Media coverage
Press/Media: Research
-
Research project to detect misinformation in emergent health domains
12/12/22
1 item of Media coverage
Press/Media: Research