Turning Narrative Descriptions of Individual Behavior into Network Visualization and Analysis: Example of Terrorist Group Dynamics. - Georgiy V. Bobashev; Marc Sageman; Amanda Lewis Evans; John Wittenborn; Robert F. Chew (SBP-BRiMS, 2018)

Assessing Target Audiences of Digital Public Health Campaigns: A Computational Approach. - Robert F. Chew; Annice Kim; Vivian Chen; Paul Ruddle; Antonio Morgan-Lopez (SBP-BRiMS, 2018)

Toward Model-Generated Household Listing in Low- and Middle-Income Countries Using Deep Learning. - Robert F. Chew; Kasey Jones; Jennifer Unangst; James Cajka; Justine Allpress; Safaa Amer; Karol Krotki (ISPRS Int. J. Geo Inf., 2018)

SMART: An Open Source Data Labeling Platform for Supervised Learning. - Rob Chew 001; Michael Wenger; Caroline Kery; Jason Nance; Keith Richards; Emily Hadley; Peter Baumgartner 004 (J. Mach. Learn. Res., 2019)

rollmatch: An R Package for Rolling Entry Matching. - Kasey Jones; Rob Chew 001; Allison Witman; Yiyan Liu (R J., 2019)

Identification of Bicycling Periods Using the MicroPEM Personal Exposure Monitor. - Robert F. Chew; Jonathan Thornburg 002; Darby Jack; Cara Smith; Qiang Yang; Steven N. Chillrud (Sensors, 2019)

Image Sequence Generation and Analysis via GRU and Attention for Trachomatous Trichiasis Classification. - Juan-Carlos Prieto 001; Hina Shah; Kasey Jones; Robert F. Chew; Hashiya M. Kana; Jerusha Weaver; Rebecca M. Flueckiger; Scott McPherson; Emily W. Gower (MIDL, 2021)

Improving Labeling Through Social Science Insights: Results and Research Agenda. - Jacob Beck; Stephanie Eckman; Robert F. Chew; Frauke Kreuter (HCI (43), 2022)

Dug: a semantic search engine leveraging peer-reviewed knowledge to query biomedical data repositories. - Alexander M. Waldrop; John B. Cheadle; Kira Bradford; Alexander Preiss; Robert F. Chew; Jonathan R. Holt; Yaphet Kebede; Nathan Braswell; Matthew Watson; Virginia Hench; Andrew Crerar; Chris M. Ball; et al. (Bioinform., 2022)

Annotation Sensitivity: Training Data Collection Methods Affect Model Performance. - Christoph Kern 001; Stephanie Eckman; Jacob Beck; Rob Chew 001; Bolei Ma; Frauke Kreuter (EMNLP (Findings), 2023)

LLM-Assisted Content Analysis: Using Large Language Models to Support Deductive Coding. - Robert F. Chew; John Bollenbacher; Michael Wenger; Jessica Speer; Annice Kim (CoRR, 2023)

Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programs. - Shawn T. O'Neil; Charisse R. Madlock-Brown; Kenneth Wilkins; Brenda M. McGrath; Hannah E. Davis; Gina S. Assaf; Hannah Wei; Parya Zareie; Evan T. French; Johanna Loomba; Julie A. McMurry; Andrea Zhou; et al. (npj Digit. Medicine, 2024)

Correcting Annotator Bias in Training Data: Population-Aligned Instance Replication (PAIR). - Stephanie Eckman; Bolei Ma; Christoph Kern 001; Robert F. Chew; Barbara Plank; Frauke Kreuter (CoRR, 2025)

Bayesian Pseudo Posterior Mechanism for Differentially Private Machine Learning. - Robert F. Chew; Matthew R. Williams; Elan A. Segarra; Alexander Preiss; Amanda Konet; Terrance D. Savitsky (CoRR, 2025)