Resilient AI 2026
Mon 3 - Fri 7 August 2026 Pasadena, California, United States
co-located with IEEE SMC-IT/SCC 2026

Resilient AI 2026 Contributors

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Results (13)

B
Bayat, Farnood
Panel 1: Rad-Hard vs. COTS: Can software ever truly fix bad hardware?
Butler, Jim
NASA/Caltech Jet Propulsion Laboratory
Creating HPSC Supervised Resilient Hardware for Commercial Processors in Space
Chair in Organizing Committee within the Resilient AI-track
E
El-Hadedy, Mohamed
California State Polytechnic University, PomonaUnited States
Resilience as a Service Plane for AI at the Space Edge: Reconfigurable Hardware, Fault Evidence, and Safe-Fail Autonomy
H
Hall, Brendan
AI That Knows How to Come Home: Preventing Hidden Alignment Drift in Space Systems
I
Iyer, Ravishankar K.
University of Illinois
Panel 1: Rad-Hard vs. COTS: Can software ever truly fix bad hardware?
Iyer, Ravishankar R.
Google
Committee Member in Organizing Committee within the Resilient AI-track
K
Kogge, Peter
Panel 1: Rad-Hard vs. COTS: Can software ever truly fix bad hardware?
AI: Faults, Architectures, and Resilience
L
Lightholder, Jack
Jet Propulsion Laboratory, California Institute of Technology
From Algorithms to Flight Software: Resilient AI Applications for Onboard Science Instrument Autonomy
Panel 2: Can LLMs make into Space?
Lupu, Sorina
Resilient AI Software & systems
S
Shehayib, Reem
University of Notre DameUnited States
Student Demo: Lightweight ML Models Robustness Against Fault Injections in Space Applications
T
T. Lu, Thomas
NASA/Caltech/JPLUnited States
Creating HPSC Supervised Resilient Hardware for Commercial Processors in Space
Panel 2: Can LLMs make into Space?
Committee Member in Organizing Committee within the Resilient AI-track
Tashakkor, Scott
NASA
Panel 2: Can LLMs make into Space?
Artificial Intelligence/Machine Learning on Safety Critical Systems
Troxel, Ian
Panel 1: Rad-Hard vs. COTS: Can software ever truly fix bad hardware?