Lodestar: Supporting Independent Learning and Rapid Experimentation Through Data-Driven Analysis Recommendations. - Deepthi Raghunandan; Zhe Cui 001; Kartik Krishnan; Segen Tirfe; Shenzhi Shi; Tejaswi Darshan Shrestha; Leilani Battle; Niklas Elmqvist (CoRR, 2022)

Code Code Evolution: Understanding How People Change Data Science Notebooks Over Time. - Deepthi Raghunandan; Aayushi Roy; Shenzhi Shi; Niklas Elmqvist; Leilani Battle (CHI, 2023)

How I Met Your Data Science Team: A Tale of Effective Communication. - Aayushi Roy; Deepthi Raghunandan; Niklas Elmqvist; Leilani Battle (VL/HCC, 2023)

Measuring How Data Science Notebooks Evolve Over Time. - Deepthi Raghunandan; Niklas Elmqvist; Leilani Battle (Interactions, 2023)

Supporting Independent Learning and Rapid Experimentation in Data Science. - Deepthi Raghunandan (2023)

Lodestar: Supporting rapid prototyping of data science workflows through data-driven analysis recommendations. - Deepthi Raghunandan; Zhe Cui 001; Kartik Krishnan; Segen Tirfe; Shenzhi Shi; Tejaswi Darshan Shrestha; Leilani Battle; Niklas Elmqvist (Inf. Vis., 2024)

A Physically Driven Long Short Term Memory Model for Estimating Snow Water Equivalent over the Continental United States. - Arun M. Saranathan; Mahmoud Saeedimoghaddam; Brandon Smith; Deepthi Raghunandan; Grey Nearing; Craig Pelissier (CoRR, 2025)