| 2025 | DSN | ReMlX: Resilience for ML Ensembles using XAI at Inference against Faulty Training Data. | Abraham Chan, Arpan Gujarati, Karthik Pattabiraman, Sathish Gopalakrishnan |
| 2025 | SAC | D-semble: Efficient Diversity-Guided Search for Resilient ML Ensembles. | Abraham Chan, Arpan Gujarati, Karthik Pattabiraman, Sathish Gopalakrishnan |
| 2025 | RTSS | Faster, Exact, More General Response-Time Analysis for NVIDIA Holoscan Applications. | Philip Schowitz, Shubhaankar Sharma, Siddharth Balodi, Soham Sinha, Bruce Shepherd, Arpan Gujarati |
| 2025 | RTCSA | EtherTime: Cross-Vendor Evaluation of PTP/NTP on Ethernet-Based COTS Embedded Platforms. | Vincent Bode, William Shen, Arpan Gujarati |
| 2024 | DSN | Harnessing Explainability to Improve ML Ensemble Resilience. | Abraham Chan, Arpan Gujarati, Karthik Pattabiraman, Sathish Gopalakrishnan |
| 2024 | DSN | 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 |
| 2024 | RTSS | Response-Time Analysis of a Soft Real-time NVIDIA Holoscan Application. | Philip Schowitz, Soham Sinha, Arpan Gujarati |
| 2023 | ISSRE | Evaluating the Effect of Common Annotation Faults on Object Detection Techniques. | Abraham Chan, Arpan Gujarati, Karthik Pattabiraman, Sathish Gopalakrishnan |
| 2022 | DSN | 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 |
| 2022 | DSN | Towards Building Resilient Ensembles against Training Data Faults. | Abraham Chan, Arpan Gujarati, Karthik Pattabiraman, Sathish Gopalakrishnan |
| 2022 | DSN | Arming IDS Researchers with a Robotic Arm Dataset. | Arpan Gujarati, Zainab Saeed Wattoo, Maryam Raiyat Aliabadi, Sean Clark, Xiaoman Liu, Parisa Shiri, Amee Trivedi, Ruizhe Zhu, Jason Hein, Margo I. Seltzer |
| 2022 | RTSS | In-ConcReTeS: Interactive Consistency meets Distributed Real-Time Systems, Again! | Arpan Gujarati, Ningfeng Yang, Bjrn B. Brandenburg |
| 2021 | QRS | Understanding the Resilience of Neural Network Ensembles against Faulty Training Data. | Abraham Chan, Niranjhana Narayanan, Arpan Gujarati, Karthik Pattabiraman, Sathish Gopalakrishnan |
| 2020 | ISSRE | New Wine in an Old Bottle: N-Version Programming for Machine Learning Components. | Arpan Gujarati, Sathish Gopalakrishnan, Karthik Pattabiraman |
| 2020 | OSDI | Serving DNNs like Clockwork: Performance Predictability from the Bottom Up. | Arpan Gujarati, Reza Karimi, Safya Alzayat, Wei Hao, Antoine Kaufmann, Ymir Vigfusson, Jonathan Mace |
| 2020 | RTAS | Real-Time Replica Consistency over Ethernet with Reliability Bounds. | Arpan Gujarati, Sergey Bozhko, Bjrn B. Brandenburg |
| 2019 | ECRTS | From Iteration to System Failure: Characterizing the FITness of Periodic Weakly-Hard Systems. | Arpan Gujarati, Mitra Nasri, Rupak Majumdar, Bjrn B. Brandenburg |
| 2019 | EMSOFT | Achal: building highly reliable networked control systems. | Arpan Gujarati, Malte Appel, Bjrn B. Brandenburg |
| 2018 | ECRTS | Quantifying the Resiliency of Fail-Operational Real-Time Networked Control Systems. | Arpan Gujarati, Mitra Nasri, Bjrn B. Brandenburg |
| 2018 | EuroSys | Tableau: a high-throughput and predictable VM scheduler for high-density workloads. | Manohar Vanga, Arpan Gujarati, Bjrn B. Brandenburg |
| 2017 | Middleware | Swayam: distributed autoscaling to meet SLAs of machine learning inference services with resource efficiency. | Arpan Gujarati, Sameh Elnikety, Yuxiong He, Kathryn S. McKinley, Bjrn B. Brandenburg |
| 2015 | RTSS | When Is CAN the Weakest Link? A Bound on Failures-in-Time in CAN-Based Real-Time Systems. | Arpan Gujarati, Bjrn B. Brandenburg |
| 2014 | RTSS | Linux's Processor Affinity API, Refined: Shifting Real-Time Tasks Towards Higher Schedulability. | Felipe Cerqueira, Arpan Gujarati, Bjrn B. Brandenburg |
| 2013 | ECRTS | Outstanding Paper Award: Schedulability Analysis of the Linux Push and Pull Scheduler with Arbitrary Processor Affinities. | Arpan Gujarati, Felipe Cerqueira, Bjrn B. Brandenburg |