Research Excellence: Dr. Lucas's Paper Accepted in Top-Tier IEEE TDSC Journal

Dr. Lucas's paper, titled "HTCNN: High-Throughput Batch CNN Inference with Homomorphic Encryption," represents significant advances in privacy-preserving machine learning technologies. The work addresses critical challenges in performing efficient convolutional neural network inference while maintaining data confidentiality through homomorphic encryption techniques—a crucial capability for secure cloud computing and privacy-sensitive AI applications.

The acceptance, achieved after two rounds of rigorous peer review and revisions, demonstrates Dr. Lucas’s dedication to research excellence and his ability to address reviewer feedback constructively. This iterative refinement process exemplifies the scholarly rigor valued in top-tier publications. IEEE TDSC focuses on foundations and mechanisms for achieving dependable and secure computing systems, making this publication particularly impactful for advancing secure AI deployment.

Congratulations, Dr. Lucas, on this well-deserved recognition! We encourage you to continue sharing your learning experiences with the CALAS community as we grow together.