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Harmanpreet Kaur
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2020 – today
- 2022
- [c16]Harmanpreet Kaur, Daniel McDuff, Alex C. Williams, Jaime Teevan, Shamsi T. Iqbal:
"I Didn't Know I Looked Angry": Characterizing Observed Emotion and Reported Affect at Work. CHI 2022: 199:1-199:18 - [c15]Harmanpreet Kaur, Eytan Adar, Eric Gilbert, Cliff Lampe:
Sensible AI: Re-imagining Interpretability and Explainability using Sensemaking Theory. FAccT 2022: 702-714 - [c14]Harmanpreet Kaur, Doug Downey, Amanpreet Singh, Evie Yu-Yen Cheng, Daniel S. Weld, Jonathan Bragg:
FeedLens: Polymorphic Lenses for Personalizing Exploratory Search over Knowledge Graphs. UIST 2022: 97:1-97:15 - [i3]Harmanpreet Kaur, Eytan Adar, Eric Gilbert, Cliff Lampe:
Sensible AI: Re-imagining Interpretability and Explainability using Sensemaking Theory. CoRR abs/2205.05057 (2022) - [i2]Harmanpreet Kaur, Doug Downey, Amanpreet Singh, Evie Yu-Yen Cheng, Daniel S. Weld, Jonathan Bragg:
FeedLens: Polymorphic Lenses for Personalizing Exploratory Search over Knowledge Graphs. CoRR abs/2208.07531 (2022) - 2021
- [j2]Oana Inel, Tomislav Duricic, Harmanpreet Kaur, Elisabeth Lex, Nava Tintarev:
Design Implications for Explanations: A Case Study on Supporting Reflective Assessment of Potentially Misleading Videos. Frontiers Artif. Intell. 4: 712072 (2021) - [c13]David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan:
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence. HCOMP 2021: 35-47 - [c12]Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan:
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. DaSH@KDD 2021 - [i1]David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan:
A Human-Centered Interpretability Framework Based on Weight of Evidence. CoRR abs/2104.13299 (2021) - 2020
- [c11]Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan:
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. CHI 2020: 1-14 - [c10]Harmanpreet Kaur, Alex C. Williams, Daniel McDuff, Mary Czerwinski, Jaime Teevan, Shamsi T. Iqbal:
Optimizing for Happiness and Productivity: Modeling Opportune Moments for Transitions and Breaks at Work. CHI 2020: 1-15 - [c9]Harmanpreet Kaur, Cliff Lampe, Walter S. Lasecki:
Using affordances to improve AI support of social media posting decisions. IUI 2020: 556-567
2010 – 2019
- 2019
- [c8]Alex C. Williams, Harmanpreet Kaur, Shamsi T. Iqbal, Ryen W. White, Jaime Teevan, Adam Fourney:
Mercury: Empowering Programmers' Mobile Work Practices with Microproductivity. UIST 2019: 81-94 - 2018
- [j1]Harmanpreet Kaur, Alex C. Williams, Anne Loomis Thompson, Walter S. Lasecki, Shamsi T. Iqbal, Jaime Teevan:
Creating Better Action Plans for Writing Tasks via Vocabulary-Based Planning. Proc. ACM Hum. Comput. Interact. 2(CSCW): 86:1-86:22 (2018) - [c7]Raymond Fok, Harmanpreet Kaur, Skanda Palani, Martez E. Mott, Walter S. Lasecki:
Towards More Robust Speech Interactions for Deaf and Hard of Hearing Users. ASSETS 2018: 57-67 - [c6]Harmanpreet Kaur, Isaac L. Johnson, Hannah Jean Miller, Loren G. Terveen, Cliff Lampe, Brent J. Hecht, Walter S. Lasecki:
Oh The Places You'll Share: An Affordances-Based Model of Social Media Posting Behaviors. CHI Extended Abstracts 2018 - [c5]Harmanpreet Kaur, Alex C. Williams, Anne Loomis Thompson, Walter S. Lasecki, Shamsi T. Iqbal, Jaime Teevan:
Using Vocabularies to Collaboratively Create Better Plans for Writing Tasks. CHI Extended Abstracts 2018 - [c4]Alex C. Williams, Harmanpreet Kaur, Gloria Mark, Anne Loomis Thompson, Shamsi T. Iqbal, Jaime Teevan:
Supporting Workplace Detachment and Reattachment with Conversational Intelligence. CHI 2018: 88 - [c3]Akshay Rao, Harmanpreet Kaur, Walter S. Lasecki:
Plexiglass: Multiplexing Passive and Active Tasks for More Efficient Crowdsourcing. HCOMP 2018: 145-153 - 2017
- [c2]Harmanpreet Kaur, Mitchell L. Gordon, Yiwei Yang, Jeffrey P. Bigham, Jaime Teevan, Ece Kamar, Walter S. Lasecki:
CrowdMask: Using Crowds to Preserve Privacy in Crowd-Powered Systems via Progressive Filtering. HCOMP 2017: 89-97 - 2015
- [c1]F. Maxwell Harper, Funing Xu, Harmanpreet Kaur, Kyle Condiff, Shuo Chang, Loren G. Terveen:
Putting Users in Control of their Recommendations. RecSys 2015: 3-10
Coauthor Index
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