TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks. - Alexander Geiger; Dongyu Liu; Sarah Alnegheimish; Alfredo Cuesta-Infante; Kalyan Veeramachaneni (IEEE BigData, 2020)

Cardea: An Open Automated Machine Learning Framework for Electronic Health Records. - Sarah Alnegheimish; Najat Alrashed; Faisal Aleissa; Shahad Althobaiti; Dongyu Liu; Mansour Alsaleh; Kalyan Veeramachaneni (DSAA, 2020)

Probabilistic Programming Bots in Intuitive Physics Game Play. - Fahad Alhasoun; Sarah Alnegheimish (AAAI, 2021)

Probabilistic Programming Bots in Intuitive Physics Game Play. - Fahad Alhasoun; Sarah Alnegheimish; Joshua B. Tenenbaum (CoRR, 2021)

AER: Auto-Encoder with Regression for Time Series Anomaly Detection. - Lawrence Wong; Dongyu Liu; Laure Berti-Équille; Sarah Alnegheimish; Kalyan Veeramachaneni (IEEE Big Data, 2022)

Using Natural Sentence Prompts for Understanding Biases in Language Models. - Sarah Alnegheimish; Alicia Guo; Yi Sun (NAACL-HLT, 2022)

Sintel: A Machine Learning Framework to Extract Insights from Signals. - Sarah Alnegheimish; Dongyu Liu; Carles Sala; Laure Berti-Équille; Kalyan Veeramachaneni (SIGMOD Conference, 2022)

Using Natural Sentences for Understanding Biases in Language Models. - Sarah Alnegheimish; Alicia Guo; Yi Sun (CoRR, 2022)

MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time Series. - Dongyu Liu; Sarah Alnegheimish; Alexandra Zytek; Kalyan Veeramachaneni (Proc. ACM Hum. Comput. Interact., 2022)

Making the End-User a Priority in Benchmarking: OrionBench for Unsupervised Time Series Anomaly Detection. - Sarah Alnegheimish; Laure Berti-Équille; Kalyan Veeramachaneni (CoRR, 2023)

OrionBench: Benchmarking Time Series Generative Models in the Service of the End-User. - Sarah Alnegheimish; Laure Berti-Équille; Kalyan Veeramachaneni (IEEE Big Data, 2024)

Explingo: Explaining AI Predictions using Large Language Models. - Alexandra Zytek; Sara Pidò; Sarah Alnegheimish; Laure Berti-Équille; Kalyan Veeramachaneni (IEEE Big Data, 2024)

Can Large Language Models be Anomaly Detectors for Time Series? - Sarah Alnegheimish; Linh Nguyen; Laure Berti-Équille; Kalyan Veeramachaneni (DSAA, 2024)

Single Word Change is All You Need: Designing Attacks and Defenses for Text Classifiers. - Lei Xu 040; Sarah Alnegheimish; Laure Berti-Équille; Alfredo Cuesta-Infante; Kalyan Veeramachaneni (CoRR, 2024)

Large language models can be zero-shot anomaly detectors for time series? - Sarah Alnegheimish; Linh Nguyen; Laure Berti-Équille; Kalyan Veeramachaneni (CoRR, 2024)

M2AD: Multi-Sensor Multi-System Anomaly Detection through Global Scoring and Calibrated Thresholding. - Sarah Alnegheimish; Zelin He; Matthew Reimherr; Akash Chandrayan; Abhinav Pradhan; Luca D'Angelo (AISTATS, 2025)

Single Word Change Is All You Need: Using LLMs to Create Synthetic Training Examples for Text Classifiers. - Lei Xu 040; Sarah Alnegheimish; Laure Berti-Équille; Alfredo Cuesta-Infante; Kalyan Veeramachaneni (Expert Syst. J. Knowl. Eng., 2025)

Harnessing Vision-Language Models for Time Series Anomaly Detection. - Zelin He; Sarah Alnegheimish; Matthew Reimherr (CoRR, 2025)