I have contributed extensively to the literature at the intersection of AI, embedded systems, and hardware acceleration. Selected publications include:

• "Heterogeneous Computing of Multi-Agent Deep Reinforcement Learning on Edge Devices" (CRC Press, 2023)
  This book chapter details a novel architecture enabling efficient distributed reinforcement learning on resource-constrained hardware.

• "Fully Convolutional Network for Edge Devices: FPGA Implementation for Agricultural Applications" (Elsevier, 2024)
  A journal article presenting a specialized FPGA-based accelerator for deploying CNNs in real-time crop monitoring scenarios.

• Numerous conference papers on topics such as FPGA-based AI inference acceleration, reinforcement learning in robotics, and embedded vision systems.

Access My Work

For full access to my research papers, datasets, and code repositories, visit my Google Scholar profile.