Salt-based autopeering for DLT-networks. - Sebastian Müller 006; Angelo Capossele; Bartosz Kusmierz; Vivian Lin; Hans Moog; Andreas Penzkofer; Olivia Saa; William Sanders; Wolfgang Welz (BRAINS, 2021)

Piezoelectric-Based Respiratory Monitoring: Towards Self-Powered Implantables for the Airways. - Luis Lopez Ruiz; Vivian Lin; Lucy Fitzgerald; Joe Zhu; Larry Borish; Daniel Quinn; John C. Lach (BSN, 2021)

T4V: Exploring Neural Network Architectures that Improve the Scalability of Neural Network Verification. - Vivian Lin; Radoslav Ivanov; James Weimer; Oleg Sokolsky; Insup Lee 001 (Principles of Systems Design, 2022)

Imprecise Bayesian Neural Networks. - Michele Caprio; Souradeep Dutta; Kuk Jin Jang; Vivian Lin; Radoslav Ivanov; Oleg Sokolsky; Insup Lee 001 (CoRR, 2023)

Take Me Home: Reversing Distribution Shifts using Reinforcement Learning. - Vivian Lin; Kuk Jin Jang; Souradeep Dutta; Michele Caprio; Oleg Sokolsky; Insup Lee 001 (CoRR, 2023)

DC4L: Distribution shift recovery via data-driven control for deep learning models. - Vivian Lin; Kuk Jin Jang; Souradeep Dutta; Michele Caprio; Oleg Sokolsky; Insup Lee 001 (L4DC, 2024)

Credal Bayesian Deep Learning. - Michele Caprio; Souradeep Dutta; Kuk Jin Jang; Vivian Lin; Radoslav Ivanov; Oleg Sokolsky; Insup Lee 001 (Trans. Mach. Learn. Res., 2024)

Distributionally Robust Statistical Verification with Imprecise Neural Networks. - Souradeep Dutta; Michele Caprio; Vivian Lin; Matthew Cleaveland; Kuk Jin Jang; Ivan Ruchkin; Oleg Sokolsky; Insup Lee 001 (HSCC, 2025)

Monitor and Recover: A Paradigm for Future Research on Distribution Shift in Learning-Enabled Cyber-Physical Systems. - Vivian Lin; Insup Lee 001 (ICCPS, 2025)

Safety Monitoring for Learning-Enabled Cyber-Physical Systems in Out-of-Distribution Scenarios. - Vivian Lin; Ramneet Kaur; Yahan Yang; Souradeep Dutta; Yiannis Kantaros; Anirban Roy; Susmit Jha; Oleg Sokolsky; Insup Lee 001 (ICCPS, 2025)