Design and Implementation of Car Parking System on FPGA. - Ramneet Kaur; Balwinder Singh (CoRR, 2013)

Parameter Invariant Monitoring for Signal Temporal Logic. - Nima Roohi; Ramneet Kaur; James Weimer; Oleg Sokolsky; Insup Lee 001 (HSCC, 2018)

Self-Driving Vehicle Verification Towards a Benchmark. - Nima Roohi; Ramneet Kaur; James Weimer; Oleg Sokolsky; Insup Lee 001 (CoRR, 2018)

Runtime Verification of Parametric Properties Using SMEDL. - Teng Zhang; Ramneet Kaur; Insup Lee 001; Oleg Sokolsky (From Reactive Systems to Cyber-Physical Systems, 2019)

Assurance Case Patterns for Cyber-Physical Systems with Deep Neural Networks. - Ramneet Kaur; Radoslav Ivanov; Matthew Cleaveland; Oleg Sokolsky; Insup Lee 001 (SAFECOMP Workshops, 2020)

Are all outliers alike? On Understanding the Diversity of Outliers for Detecting OODs. - Ramneet Kaur; Susmit Jha; Anirban Roy; Oleg Sokolsky; Insup Lee 001 (CoRR, 2021)

Detecting OODs as datapoints with High Uncertainty. - Ramneet Kaur; Susmit Jha; Anirban Roy; Sangdon Park 001; Oleg Sokolsky; Insup Lee 001 (CoRR, 2021)

iDECODe: In-Distribution Equivariance for Conformal Out-of-Distribution Detection. - Ramneet Kaur; Susmit Jha; Anirban Roy; Sangdon Park 001; Edgar Dobriban; Oleg Sokolsky; Insup Lee 001 (AAAI, 2022)

Interpretable Detection of Distribution Shifts in Learning Enabled Cyber-Physical Systems. - Yahan Yang; Ramneet Kaur; Souradeep Dutta; Insup Lee 001 (ICCPS, 2022)

Towards Alternative Techniques for Improving Adversarial Robustness: Analysis of Adversarial Training at a Spectrum of Perturbations. - Kaustubh Sridhar; Souradeep Dutta; Ramneet Kaur; James Weimer; Oleg Sokolsky; Insup Lee 001 (CoRR, 2022)

CODiT: Conformal Out-of-Distribution Detection in Time-Series Data. - Ramneet Kaur; Kaustubh Sridhar; Sangdon Park 001; Susmit Jha; Anirban Roy; Oleg Sokolsky; Insup Lee 001 (CoRR, 2022)

Predicting Out-of-Distribution Performance of Deep Neural Networks Using Model Conformance. - Ramneet Kaur; Susmit Jha; Anirban Roy; Oleg Sokolsky; Insup Lee 001 (ICAA, 2023)

CODiT: Conformal Out-of-Distribution Detection in Time-Series Data for Cyber-Physical Systems. - Ramneet Kaur; Kaustubh Sridhar; Sangdon Park 001; Yahan Yang; Susmit Jha; Anirban Roy; Oleg Sokolsky; Insup Lee 001 (ICCPS, 2023)

Automated Labeling Function Generation using Distance Functions for Physiological Alarm Suppression. - Sydney Pugh; Souradeep Dutta; Ramneet Kaur; Yahan Yang; Elena Bernardis; Insup Lee 001 (ICCPS, 2023)

Using Semantic Information for Defining and Detecting OOD Inputs. - Ramneet Kaur; Xiayan Ji; Souradeep Dutta; Michele Caprio; Yahan Yang; Elena Bernardis; Oleg Sokolsky; Insup Lee 001 (CoRR, 2023)

Detection of Adversarial Physical Attacks in Time-Series Image Data. - Ramneet Kaur; Yiannis Kantaros; Wenwen Si; James Weimer; Insup Lee 001 (CoRR, 2023)

Learner-Centric Hybrid Filtering-Based Recommender System for Massive Open Online Courses. - Ramneet Kaur; Deepali Gupta; Mani Madhukar (Int. J. Perform. Eng., 2023)

Automating Weak Label Generation for Data Programming with Clinicians in the Loop. - Jean Park; Sydney Pugh; Kaustubh Sridhar; Mengyu Liu; Navish Yarna; Ramneet Kaur; Souradeep Dutta; Elena Bernardis; Oleg Sokolsky; Insup Lee 001 (CHASE, 2024)

Post-hoc Uncertainty Quantification for Neurosymbolic Artificial Intelligence. - Alexander M. Berenbeim; Ramneet Kaur; Adam D. Cobb; Anirban Roy; Susmit Jha; Nathaniel D. Bastian (MILCOM, 2024)

Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI. - Ramneet Kaur; Colin Samplawski; Adam D. Cobb; Anirban Roy; Brian Matejek; Manoj Acharya; Daniel Elenius; Alexander M. Berenbeim; John A. Pavlik; Nathaniel D. Bastian; Susmit Jha (CoRR, 2024)

Memory-based Distribution Shift Detection for Learning Enabled Cyber-Physical Systems with Statistical Guarantees. - Yahan Yang; Ramneet Kaur; Souradeep Dutta; Insup Lee 001 (ACM Trans. Cyber Phys. Syst., 2024)

Out-of-distribution Detection in Dependent Data for Cyber-physical Systems with Conformal Guarantees. - Ramneet Kaur; Yahan Yang; Oleg Sokolsky; Insup Lee 001 (ACM Trans. Cyber Phys. Syst., 2024)

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)

Taylor-Model Physics-Informed Neural Networks (PINNs) for Ordinary Differential Equations. - Chandra Kanth Nagesh; Sriram Sankaranarayanan 001; Ramneet Kaur; Tuhin Sahai; Susmit Jha (NeuS, 2025)

Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference. - Colin Samplawski; Adam D. Cobb; Manoj Acharya; Ramneet Kaur; Susmit Jha (UAI, 2025)

Zero-Shot Detection of Out-of-Context Objects Using Foundation Models. - Anirban Roy; Adam D. Cobb; Ramneet Kaur; Sumit Jha 001; Nathaniel D. Bastian; Alexander M. Berenbeim; Robert H. Thomson 001; Iain Cruickshank; Alvaro Velasquez; Susmit Jha (WACV, 2025)

Development of a cryptocurrency price prediction model: leveraging GRU and LSTM for Bitcoin, Litecoin and Ethereum. - Ramneet Kaur; Mudita Uppal; Deepali Gupta; Sapna Juneja; Syed Yasser Arafat; Junaid Rashid; Jungeun Kim; Roobaea Alroobaea (PeerJ Comput. Sci., 2025)

Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding. - Trilok Padhi; Ramneet Kaur; Adam D. Cobb; Manoj Acharya; Anirban Roy; Colin Samplawski; Brian Matejek; Alexander M. Berenbeim; Nathaniel D. Bastian; Susmit Jha (CoRR, 2025)