Ramtin Zand

University of South Carolina, Sharif University of Technology

Papers

Total Citations

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About

Ramtin Zand is a researcher working at the intersection of neuromorphic computing, edge artificial intelligence, and autonomous systems. His work addresses one of the most pressing challenges in modern computing: deploying sophisticated machine learning models on resource-constrained hardware platforms in real time. Zand's investigation into neuromorphic hardware versus edge AI accelerators for facial expression recognition represents a meaningful contribution to the growing field of efficient embedded intelligence, exploring how biological-inspired computing architectures can serve practical applications like social robotics. His research extends into autonomous underwater systems, where he has tackled the complex problem of real-time caveline detection for underwater cave exploration and mapping — a niche yet technically demanding application that pushes the boundaries of edge deployment. Earlier in his career, Zand demonstrated a strong foundation in intelligent control systems through his work on fuzzy logic controllers for quadruped locomotion, showcasing expertise in human expertise extraction and biologically-inspired robotics design. With citations accumulating across multiple emerging domains, Zand's portfolio reflects a researcher steadily building influence across neuromorphic engineering, computer vision, and autonomous robotics — areas of growing importance in both academic and industrial contexts.