Amy Rechkemmer
Graduate Student
Graduate Research Assistant
Joined department: Fall 2018
Education
Amy is a PhD candidate advised by Ming Yin. Her research relates to human computation, crowdsourcing, human-computer interaction, and human-AI interaction. Her work has won best paper awards at both AAAI HCOMP and ACM CHI.
Selected Publications
Amy Rechkemmer, Ming Yin. Motivating Novice Crowd Workers Through Goal Setting: An Investigation into the Effects on Complex Crowdsourcing Task Training. In Proc. of the 8th AAAI Conference on Human Computation and Crowdsourcing (HCOMP), Hilversum, Netherlands, October 2020.
Amy Rechkemmer, Ming Yin. Exploring the Effects of Goal Setting When Training for Complex Crowdsourcing Tasks. In Proc. of the 30th International Joint Conference on Artificial Intelligence (IJCAI), Montreal, QC, August 2021. (Invited to Sister Conferences Track)
Amy Rechkemmer, Ming Yin. When Confidence Meets Accuracy: Exploring the Effects of Multiple Performance Indicators on Trust in Machine Learning Models. In Proc. of the 40th ACM Conference on Human Factors in Computing Systems (CHI), New Orleans, LA, April 30 - May 6, 2022.
Amy Rechkemmer, Ming Yin. Understanding the Microtask Crowdsourcing Experience for Workers with Disabilities: A Comparative View. In Proc. of the ACM on Human-Computer Interaction: Computer-Supported Cooperative Work and Social Computing (CSCW), November 2022.
Amy Rechkemmer, Alex C. Williams, Matthew Lease, Li Erran Li. Characterizing Time Spent in Video Object Tracking Annotation Tasks: A Study of Task Complexity in Vehicle Tracking. In Proc. of the 11th AAAI Conference on Human Computation and Crowdsourcing (HCOMP), Delft, Netherlands, November 2023.