🔬 Research Summary by Bang An, a Ph.D. student at the University of Maryland, College Park, specializing in trustworthy machine learning. [Original paper by Bang An, Zora Che, Mucong Ding, and Furong … [Read more...] about Transferring Fairness under Distribution Shifts via Fair Consistency Regularization
Technical Methods
Towards Environmentally Equitable AI via Geographical Load Balancing
🔬 Research Summary by Pengfei Li and Shaolei Ren Pengfei Li is a Ph.D. candidate in computer science and engineering at the University of California, Riverside. Shaolei Ren is an associate professor in … [Read more...] about Towards Environmentally Equitable AI via Geographical Load Balancing
Fairness Uncertainty Quantification: How certain are you that the model is fair?
🔬 Research Summary by Abhishek Roy, a post-doc at Halıcıoğlu Data Science Institute, UC San Diego [Original paper by Abhishek Roy and Prasant Mohapatra] Overview: Designing fair Machine Learning (ML) … [Read more...] about Fairness Uncertainty Quantification: How certain are you that the model is fair?
On the Impact of Machine Learning Randomness on Group Fairness
🔬 Research Summary by Prakhar Ganesh, incoming Ph.D. student at the University of Montreal and Mila; interested in studying the learning dynamics of neural networks at the intersection of fairness, robustness, privacy, … [Read more...] about On the Impact of Machine Learning Randomness on Group Fairness
Technological trajectories as an outcome of the structure-agency interplay at the national level: Insights from emerging varieties of AI
🔬 Research Summary by Dr. Cristian Gherhes, Founder & CEO of Lexverify and Visiting Fellow at Oxford Brookes University. [Original paper by Cristian Gherhes, Zhen Yu, Tim Vorley, and Lan Xue] Overview: … [Read more...] about Technological trajectories as an outcome of the structure-agency interplay at the national level: Insights from emerging varieties of AI