I'm a PhD candidate in the Department of Computer Science at Purdue University where I am fortunate to be advised by Dr. Ming Yin. My research interests broadly lie in the fields of human-computer interaction, human computation and crowdsourcing, social computing, and human-AI interaction. My current thesis work aims to understand the challenges faced by various data worker populations in order to devise interventions and systems to help mitigate these challenges [HCOMP20, IJCAI21, CSCW22, HCOMP23]. Some of my work has also looked into how factors of machine learning models impact people's trust in its decisions [CHI22] and analyzing how population size influences language used on social media [LREC20].
I received a BSE in Computer Science and Engineering from the University of Michigan. During this time, I was part of the Daly Design and Engineering Education Research Group exploring the impacts of problem framing on ideation flexibility in engineering design [ASEE16, ASEE17, Des.Stud.21].
I also currently serve as the Computer Science representative for the Purdue Graduate Women in Science Program (WISP) leadership team. Feel free to reach out to me if you have questions about Grad WISP events and other activities!
News
December 2023: Our paper "Snapper: Accelerating Bounding Box Annotation in Object Detection Tasks with Find-and-Snap Tooling" has been accepted to IUI 2024! This work was done with Alex Williams, Min Bai, Jonathan Buck, Tristan McKinney, Koushik Kalyanaraman, Matt Lease, Patrick Haffner, Xiong Zhou, Kumar Chellapilla, and Erran Li.
October 2023: I attended CSCW's Doctoral Consortium to receive feedback on my current thesis progress.
August 2023: Our paper "Characterizing Time Spent in Video Object Tracking Annotation Tasks: A Study of Task Complexity in Vehicle Tracking" has been accepted to HCOMP 2023! This work was done with Alex Williams, Matt Lease, and Erran Li during my internship at Amazon.
May 2023: I passed my preliminary exam and have achieved candidacy!
Selected Publications
Understanding the Microtask Crowdsourcing Experience for Workers with Disabilities: A Comparative View
Amy Rechkemmer and Ming Yin.
The 25th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), Taipei, Taiwan, November 2022.
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[Supplementary Materials] ·
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When Confidence Meets Accuracy: Exploring the Effects of Multiple Performance Indicators on Trust in Machine Learning Models
Amy Rechkemmer and Ming Yin.
The 40th ACM Conference on Human Factors in Computing Systems (CHI), New Orleans, LA, April 30th - May 6th 2022.
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[Supplementary Materials] ·
[Talk]
Best Paper Award
Motivating Novice Crowd Workers through Goal Setting: An Investigation into the Effects on Complex Crowdsourcing Task Training
Amy Rechkemmer and Ming Yin.
The 8th AAAI Conference on Human Computation and Crowdsourcing (HCOMP), Hilversum, Netherlands, November 2020.
[Slides] · [Extended Talk]
Best Paper Award