Leveraging Compiler Optimizations to Reduce Runtime Fault Recovery Overhead. - Fateme S. Hosseini; Pouya Fotouhi; Chengmo Yang; Guang R. Gao (DAC, 2017)

Segment and Conflict Aware Page Allocation and Migration in DRAM-PCM Hybrid Main Memory. - Hoda Aghaei Khouzani; Fateme S. Hosseini; Chengmo Yang (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2017)

A Low Overhead Solution to Resilient Assembly Lines Built From Legacy Controllers. - Patrick Cronin; Fateme S. Hosseini; Chengmo Yang (IEEE Embed. Syst. Lett., 2018)

Compiler-Directed and Architecture-Independent Mitigation of Read Disturbance Errors in STT-RAM. - Fateme S. Hosseini; Chengmo Yang (DATE, 2019)

Comprehensive Evaluation of Program Reliability with ComFIDet: An Integrated Fault Injection and Detection Framework for Embedded Systems. - Fateme S. Hosseini; Chengmo Yang (ICESS, 2019)

Trustworthy AI Inference Systems: An Industry Research View. - Rosario Cammarota; Matthias Schunter; Anand Rajan; Fabian Boemer; Ágnes Kiss; Amos Treiber; Christian Weinert; Thomas Schneider 003; Emmanuel Stapf; Ahmad-Reza Sadeghi; Daniel Demmler; Huili Chen; et al. (CoRR, 2020)

A Self-Test Framework for Detecting Fault-induced Accuracy Drop in Neural Network Accelerators. - Fanruo Meng; Fateme S. Hosseini; Chengmo Yang (ASP-DAC, 2021)

Safeguarding the Intelligence of Neural Networks with Built-in Light-weight Integrity MArks (LIMA). - Fateme S. Hosseini; Qi Liu 017; Fanruo Meng; Chengmo Yang; Wujie Wen (HOST, 2021)

A Compile-Time Framework for Tolerating Read Disturbance in STT-RAM. - Fateme S. Hosseini; Chengmo Yang (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2021)

Tolerating Defects in Low-Power Neural Network Accelerators Via Retraining-Free Weight Approximation. - Fateme S. Hosseini; Fanruo Meng; Chengmo Yang; Wujie Wen; Rosario Cammarota (ACM Trans. Embed. Comput. Syst., 2021)