Marissa Radensky

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Hi! I’m a second-year computer science PhD student at the University of Washington advised by Dan Weld and Zoran Popović. My research interests are in human-AI interaction and explainable AI. More specifically, I am interested in how methods of transparency can be used to help users of intelligent systems understand when and when not to trust those systems.

Email: radensky at cs dot washington dot edu

CV | LinkedIn | Semantic Scholar | Google Scholar

Publications

PUMICE: A Multi-Modal Agent that Learns Concepts and Conditionals from Natural Language and Demonstrations
Toby Jia-Jun Li, Marissa Radensky, Justin Jia, Kirielle Singarajah, Tom M. Mitchell and Brad A. Myers (UIST 2019)

The Story in the Notebook: Exploratory Data Science using a Literate Programming Tool
Mary Beth Kery, Marissa Radensky, Mahima Arya, Bonnie E. John, and Brad A. Myers (CHI 2018)

Posters and Workshops

Interactive Task and Concept Learning from Natural Language Instructions and GUI Demonstrations
Toby Jia-Jun Li, Marissa Radensky, Justin Jia, Kirielle Singarajah, Tom M. Mitchell and Brad A. Myers (IPA 2020 Workshop)

A Multi-Modal Approach to Concept Learning in Task Oriented Conversational Agents
Toby Jia-Jun Li, Marissa Radensky, Tom M. Mitchell and Brad A. Myers (CHI 2019 Workshop)

How End Users Express Conditionals in Programming by Demonstration for Mobile Apps
Marissa Radensky, Toby Jia-Jun Li, and Brad A. Myers (VL/HCC 2018 Poster)