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

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

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; Brad A. Myers (UIST, 2019)

Bridger: Toward Bursting Scientific Filter Bubbles and Boosting Innovation via Novel Author Discovery. - Jason Portenoy; Marissa Radensky; Jevin West; Eric Horvitz; Daniel S. Weld; Tom Hope (CoRR, 2021)

Bursting Scientific Filter Bubbles: Boosting Innovation via Novel Author Discovery. - Jason Portenoy; Marissa Radensky; Jevin D. West; Eric Horvitz; Daniel S. Weld; Tom Hope (CHI, 2022)

Exploring the Role of Local and Global Explanations in Recommender Systems. - Marissa Radensky; Doug Downey; Kyle Lo; Zoran Popovic; Daniel S. Weld (CHI Extended Abstracts, 2022)

Exploring How Anomalous Model Input and Output Alerts Affect Decision-Making in Healthcare. - Marissa Radensky; Dustin Burson; Rajya Bhaiya; Daniel S. Weld (CoRR, 2022)

"I Think You Might Like This": Exploring Effects of Confidence Signal Patterns on Trust in and Reliance on Conversational Recommender Systems. - Marissa Radensky; Julie Anne Séguin; Jang Soo Lim; Kristen Olson; Robert Geiger (FAccT, 2023)

Mixed-Initiative Methods for Co-Creation in Scientific Research. - Marissa Radensky (Creativity & Cognition, 2024)

Let's Get to the Point: LLM-Supported Planning, Drafting, and Revising of Research-Paper Blog Posts. - Marissa Radensky; Daniel S. Weld; Joseph Chee Chang; Pao Siangliulue; Jonathan Bragg (CoRR, 2024)

Scideator: Human-LLM Scientific Idea Generation Grounded in Research-Paper Facet Recombination. - Marissa Radensky; Simra Shahid; Raymond Fok; Pao Siangliulue; Tom Hope; Daniel S. Weld (CoRR, 2024)

CodeScientist: End-to-End Semi-Automated Scientific Discovery with Code-based Experimentation. - Peter Jansen 001; Oyvind Tafjord; Marissa Radensky; Pao Siangliulue; Tom Hope; Bhavana Dalvi Mishra; Bodhisattwa Prasad Majumder; Daniel S. Weld; Peter Clark (ACL (Findings), 2025)

Facets, Taxonomies, and Syntheses: Navigating Structured Representations in LLM-Assisted Literature Review. - Raymond Fok; Joseph Chee Chang; Marissa Radensky; Pao Siangliulue; Jonathan Bragg; Amy X. Zhang; Daniel S. Weld (CoRR, 2025)

Literature-Grounded Novelty Assessment of Scientific Ideas. - Simra Shahid; Marissa Radensky; Raymond Fok; Pao Siangliulue; Daniel S. Weld; Tom Hope (CoRR, 2025)