Elias Platanios focused on stabilizing PJRT runtime behavior in the Intel-tensorflow/tensorflow and Intel-tensorflow/xla repositories by addressing critical bugs related to callback size references. Using C++ and leveraging his expertise in software debugging and callback handling, he corrected logic errors that previously led to segmentation faults during execution. His work involved cross-repository debugging, regression testing, and coordinated pull requests to ensure consistent fixes across both codebases. By resolving these issues, Elias improved the reliability and uptime of PJRT workloads, directly supporting more predictable machine learning training and inference pipelines while emphasizing maintainability and business value in his engineering approach.