July 13, 2021 Engineering trio receives data science grants for machine learning, crowdsourcing research Written By: Staff Departments: Electrical & Computer Engineering|Industrial & Systems Engineering Categories Awards College of Engineering faculty members Laura Albert, Ramya Vinayak and Dimitris Papailiopoulos have earned grants for data science research projects through the third round of the American Family Funding Initiative at the University of Wisconsin-Madison. Albert, the David H. Gustafson Chair of the Department of Industrial and Systems Engineering and Harvey D. Spangler Faculty Scholar, is principal investigator for a project applying machine learning tools to the insurance industry. She will use an optimization modeling framework to prescribe innovative, dynamic workflow routing decisions, balance the workload across claims agents, improve client satisfaction and control costs. Vinayak, an assistant professor of electrical and computer engineering, is principal investigator for an effort aiming to increase understanding of how the ability of humans to learn and retain new concepts affects the quality and cost of crowdsourced data. Crowdsourcing is a popular way to collect labeled training data for supervised machine learning. Papailiopoulos, an assistant professor of electrical and computer engineering, is co-principal investigator for a project to develop tools that can automate and accelerate the time-intensive processes of training and fine-tuning machine learning models by intelligently reusing past computations. Shivaram Venkataraman, an assistant professor of computer sciences, is principal investigator for the collaboration. American Family Insurance has partnered with UW-Madison through the American Family Insurance Data Science Institute to offer grants of $75,000-150,000 for data science research at the university. Since its inception in spring 2020, the initiative has awarded nearly $3 million to 21 teams of faculty and collaborators. College of Engineering researchers also received grants in the first and second rounds of the initiative.