I focus on cross-layer HW/SW co-design for AI—accelerator architecture, memory, and interconnect—for efficient, scalable, privacy-preserving training and inference. Work spans sparsity/compression-aware acceleration, neuro- and vector-symbolic computing, distributed LLM modeling, and CPU–GPU orchestration.