Machine learning competitions are held with mission-driven organizations to drive change through data science and engineering
DrivenData, host of the U.S.-U.K. PETs Prize Challenges, announced its winners this past week with privacy researchers at the Rutgers Institute for Data Science, Learning and Applications (I-DSlA) taking first place. DrivenData hosts online modeling competitions to promote cutting-edge practices in data science and the use of crowdsourcing to tackle global social challenges.
The Rutgers I-DSLA team are part of a global community of data scientists who collectively seek the best statistical model for difficult predictive problems that have a social impact. Teams typically compete over a period of a few months on a range of projects in the areas of international development, health, education, research and conservation, and public services.
This year’s competition with a $100,000 first place prize focused on advancing “privacy-preserving federated learning solutions that provide end-to-end privacy and security protections, while harnessing the potential of AI for overcoming significant global challenges.”
The winning Rutgers team included:
- Hafiz Asif: a postdoc at I-DSLA, having received his Ph.D. from Rutgers University. His research focuses on developing SAFE (secure & private, auditable, fair, and equitable) theoretical approaches and practical frameworks to leverage the power of data to solve real-world problems,
- Sitao Min: currently pursuing his Ph.D. at Rutgers University, focusing on developing methods for privacy- and fairness preserving data analysis in federated data settings,
- Xinyue Wang: currently pursuing her Ph.D. at Rutgers University, focusing on developing privacy-preserving methods to generate high-fidelity synthetic data and analyze genomic data, and
- Jaideep Vaidya: a Distinguished Professor at Rutgers University and Director of I-DSLA. His general area of research is in privacy, security, data management, and data analytics, especially at their intersection. He is an IEEE and AAAS Fellow and ACM Distinguished Scientist.
DrivenData’s online machine learning competitions are held in collaboration with mission-driven organizations that contribute to driving change through data science and engineering. The company has a number of popular open-source projects for the data science community and prize-winning solutions from past competitions have been shared openly on GitHub for the benefit of everyone who wants to learn and build from.
To learn more about DrivenData’s U.S. PETS Prize Challenge visit: Meet the Final Winners of the U.S. PETs Prize Challenge – DrivenData Labs
