Kristen Vaccaro

PhD Computer Science University of Illinois


Kristen Vaccaro, Karrie Karahalios, Deirdre Mulligan, Daniel Kluttz and Tad Hirsch

CSCW 2019 Workshop

We will be running a workshop on contestability at CSCW 2019! Please join us! Workshop website!

Motahhare Eslami, Kristen Vaccaro, Min Kyung Lee, Amit Elazari Bar On, Eric Gilbert, Karrie Karahalios

CHI 2019

We study how users perceive and interact with potentially biased and deceptive opaque algorithms. What factors are associated with these perceptions, and how does adding transparency into algorithmic systems change user attitudes?

Kristen Vaccaro, Dylan Huang, Motahhare Eslami, Christian Sandvig, Kevin Hamilton, and Karrie Karahalios

CHI 2018

In this work, we study how users engage with difficult-to-validate control settings for social media, and find that they can function as placebos.

Kristen Vaccaro, Tanvi Agarwalla, Sunaya Shivakumar and Ranjitha Kumar

CHI 2018

To understand consumer pain points and opportunities for tech interventions, this paper presents the results from two need-finding studies that explore the gold-standard of personalized shopping: interacting with a personal stylist.

Motahhare Eslami, Kristen Vaccaro, Karrie Karahalios, and Kevin Hamilton

ICWSM 2017

How do users discover and behave around algorithmic biases? A cross-platform audit of online rating platforms revealed that users try to raise awareness of bias from within the platform.

Kristen Vaccaro, Sunaya Shivakumar, Ziqiao Ding, Karrie Karahalios and Ranjitha Kumar

UIST 2016

Using polylingual topic models (PLTMs), we learn latent fashion concepts jointly in two languages: a style language describing outfits and an element language labeling clothing items. This model allows us to translate between the two languages, exposing the elements of fashion style.

Jennifer G. Kim, Kristen Vaccaro, Karrie Karahalios and Hwajung Hong

CSCW 2016

Medical crowdfunding helps patients receive financial support, but little is known about who the patient's supporters are, what support they provide, and why. Interviews addressed these questions; we suggest making the variety of volunteering contributions more visible and discuss the associated design challenges.

Motahhare Eslami, Karrie Karahalios, Christian Sandvig, Kristen Vaccaro, Aimee Rickman, Kevin Hamilton and Alex Kirlik

CHI 2016

Interviews revealed 10 "folk theories" of automated news feed curation, some quite unexpected. Providing users a probe into the algorithm's operation also helped users quickly develop theories. Foregrounding these automated processes may increase interface design complexity but may also add usability benefits.

Motahhare Eslami, Aimee Rickman, Kristen Vaccaro, Amirhossein Aleyasen, Andy Vuong, Karrie Karahalios, Kevin Hamilton and Christian Sandvig

CHI 2015 Best Paper

Users are often surprisingly unaware of the algorithms that permeate their digital lives. This work (with Motahareh Eslami) developed a system to reveal the differences between curated and unfiltered News Feeds to users and found that users had often inferred social meaning from algorithmic filtering.

Workshop Papers

Kristen Vaccaro and Karrie Karahalios

NSF Trustworthy Algorithmic Decision-Making Workshop

How can and should users be able to appeal algorithmically generated decisions?

Ranjitha Kumar and Kristen Vaccaro

AAAI 2017 Spring Symposium

We propose an experimentation engine for fashion interfaces: leveraging social media platforms to run multivariate design tests with thousands to millions of users.

Kristen Vaccaro, Karrie Karahalios, Kevin Hamilton, Cedric Langbort and Christian Sandvig

CSCW 2014 Workshop

We argue that the ACM Code of Ethics requirement to follow terms of service is problematic. While the reasons for following terms of service are clear, there are hidden costs. Using research into algorithm awareness transparency as an example, we argue that for some research problems the benefits of work violating TOS outweigh the harms.


Before Illinois, I worked at the MITRE Corporation, a federally funded R&D center. I focused on two areas: data mining/AI and signal processing. This included algorithm evaluation work, primarily dealing with identity management, social network analysis and NLP. I also worked on several signal processing projects.

I graduated from Reed College in Portland, Oregon. While there, I worked with Joel Franklin to develop a novel application of speech recognition to sociolinguistics. I developed a proof-of-concept tool that could detect socio-economic and other background features of speakers.


I participate in a number of mentoring programs for undergraduates, including WCS, MUSE, and PURE, and for incoming graduate students.

Please check out the webpages of some of the students I work with:

If you are interested in working with our group, please email me!


I have TA'd a number of courses at the University of Illinois. I've also been selected to teach in the Graduate Academy for College Teaching, the University of Illinois' campus-wide TA training program. Teaching materials and/or information for each course below:

CS 598: Data-Driven Design
CS 498: The Art of Web Programming
CS 210: Ethics in Technology
CS 205: Data Structures for Non-majors
CS 102: Little Bits to Big Ideas