Welcome to computational data science Wiki page. We are a multi-disciplinary group at McCombs. We meet biweekly to discuss recent papers on computational data science and applied machine learning. In this Wiki page, we share information about our schedules, group members and other resources (e.g., relevant online seminars, grant opportunities, and conferences). 

Meeting 

Time: 4:30 – 5:30 pm CST Friday (bi-weekly). 
Zoom link: https://utexas.zoom.us/j/92071650227

Schedules

• 11/26 or 12/11: Liu, Liu, Daria Dzyabura, and Natalie Mizik. "Visual listening in: Extracting brand image portrayed on social media." Marketing Science. 2020. Link. 
• 11/13: Leng Y., Dong X.W., Wu J.F., Pentland, A. Learning quadratic games on networks. ICML 2020. 
• 10/26: H. Anahideh and A. Asudeh. Fair active learning. arXiv:2001.01796 [cs.LG], 2020. Link.
• 10/12: Dong W., M Saar-Tsechansky, T Geva, On Data-Driven Inference of Experts’ Decision Qualities: New Problems & Algorithms. WITS 2019. 
• 10/5: Gao, R., & Saar-Tsechansky, M. (2020). Cost-Accuracy Aware Adaptive Labeling for Active Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 34(03), 2569-2576. Link.
• 9/28: De-Arteaga M., et al. Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. FAccT 2019. Link.
• 9/14: Introduction to algorithmic fairness (Maria De-Arteaga). 
• 9/9: Maytal, Maria and Yan share their research interests. 

People 

Resources 

Other online seminars 

• UT Explainable AI (XAI) group meeting: https://www.cs.utexas.edu/~ml/xai/

Funding opportunities 

• NSF National Artificial Intelligence (AI) Research Institutes: https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505686
• Facebook Fellowship: https://research.fb.com/fellowship/

Subscribe to us

https://groups.google.com/g/ut-computational-data-science