Outstanding Paper Award: Schedulability Analysis of the Linux Push and Pull Scheduler with Arbitrary Processor Affinities. - Arpan Gujarati; Felipe Cerqueira; Björn B. Brandenburg (ECRTS, 2013)

Linux's Processor Affinity API, Refined: Shifting Real-Time Tasks Towards Higher Schedulability. - Felipe Cerqueira; Arpan Gujarati; Björn B. Brandenburg (RTSS, 2014)

When Is CAN the Weakest Link? A Bound on Failures-in-Time in CAN-Based Real-Time Systems. - Arpan Gujarati; Björn B. Brandenburg (RTSS, 2015)

Multiprocessor real-time scheduling with arbitrary processor affinities: from practice to theory. - Arpan Gujarati; Felipe Cerqueira; Björn B. Brandenburg (Real Time Syst., 2015)

Swayam: distributed autoscaling to meet SLAs of machine learning inference services with resource efficiency. - Arpan Gujarati; Sameh Elnikety; Yuxiong He; Kathryn S. McKinley; Björn B. Brandenburg (Middleware, 2017)

Quantifying the Resiliency of Fail-Operational Real-Time Networked Control Systems. - Arpan Gujarati; Mitra Nasri; Björn B. Brandenburg (ECRTS, 2018)

Tableau: a high-throughput and predictable VM scheduler for high-density workloads. - Manohar Vanga; Arpan Gujarati; Björn B. Brandenburg (EuroSys, 2018)

From Iteration to System Failure: Characterizing the FITness of Periodic Weakly-Hard Systems. - Arpan Gujarati; Mitra Nasri; Rupak Majumdar; Björn B. Brandenburg (ECRTS, 2019)

Achal: building highly reliable networked control systems. - Arpan Gujarati; Malte Appel; Björn B. Brandenburg (EMSOFT Companion, 2019)

Correspondence article: a correction of the reduction-based schedulability analysis for APA scheduling. - Arpan Gujarati; Felipe Cerqueira; Björn B. Brandenburg; Geoffrey Nelissen (Real Time Syst., 2019)

New Wine in an Old Bottle: N-Version Programming for Machine Learning Components. - Arpan Gujarati; Sathish Gopalakrishnan; Karthik Pattabiraman (ISSRE Workshops, 2020)

Serving DNNs like Clockwork: Performance Predictability from the Bottom Up. - Arpan Gujarati; Reza Karimi; Safya Alzayat; Wei Hao; Antoine Kaufmann; Ymir Vigfusson; Jonathan Mace (OSDI, 2020)

Real-Time Replica Consistency over Ethernet with Reliability Bounds. - Arpan Gujarati; Sergey Bozhko; Björn B. Brandenburg (RTAS, 2020)

Serving DNNs like Clockwork: Performance Predictability from the Bottom Up. - Arpan Gujarati; Reza Karimi; Safya Alzayat; Antoine Kaufmann; Ymir Vigfusson; Jonathan Mace (CoRR, 2020)

Towards "Ultra-Reliable" CPS: Reliability Analysis of Distributed Real-Time Systems. - Arpan Gujarati (2020)

Understanding the Resilience of Neural Network Ensembles against Faulty Training Data. - Abraham Chan; Niranjhana Narayanan; Arpan Gujarati; Karthik Pattabiraman; Sathish Gopalakrishnan (QRS, 2021)

The Fault in Our Data Stars: Studying Mitigation Techniques against Faulty Training Data in Machine Learning Applications. - Abraham Chan; Arpan Gujarati; Karthik Pattabiraman; Sathish Gopalakrishnan (DSN, 2022)

Towards Building Resilient Ensembles against Training Data Faults. - Abraham Chan; Arpan Gujarati; Karthik Pattabiraman; Sathish Gopalakrishnan (DSN Workshops, 2022)

Arming IDS Researchers with a Robotic Arm Dataset. - Arpan Gujarati; Zainab Saeed Wattoo; Maryam Raiyat Aliabadi; Sean Clark 004; Xiaoman Liu; Parisa Shiri; Amee Trivedi; Ruizhe Zhu; Jason Hein; Margo I. Seltzer (DSN, 2022)

In-ConcReTeS: Interactive Consistency meets Distributed Real-Time Systems, Again! - Arpan Gujarati; Ningfeng Yang; Björn B. Brandenburg (RTSS, 2022)

Evaluating the Effect of Common Annotation Faults on Object Detection Techniques. - Abraham Chan; Arpan Gujarati; Karthik Pattabiraman; Sathish Gopalakrishnan (ISSRE, 2023)

Harnessing Explainability to Improve ML Ensemble Resilience. - Abraham Chan; Arpan Gujarati; Karthik Pattabiraman; Sathish Gopalakrishnan (DSN-S, 2024)

RABIT, a Robot Arm Bug Intervention Tool for Self-Driving Labs. - Zainab Saeed Wattoo; Petal Vitis; Ruizhe Zhu; Noah Depner; Ivory Zhang; Jason Hein; Arpan Gujarati; Margo I. Seltzer (DSN, 2024)

Response-Time Analysis of a Soft Real-time NVIDIA Holoscan Application. - Philip Schowitz; Soham Sinha; Arpan Gujarati (RTSS, 2024)

ReMlX: Resilience for ML Ensembles using XAI at Inference against Faulty Training Data. - Abraham Chan; Arpan Gujarati; Karthik Pattabiraman; Sathish Gopalakrishnan (DSN, 2025)

D-semble: Efficient Diversity-Guided Search for Resilient ML Ensembles. - Abraham Chan; Arpan Gujarati; Karthik Pattabiraman; Sathish Gopalakrishnan (SAC, 2025)