Borko Furht

Papers

Total Citations

365

H-Index

About

Borko Furht is a versatile computer scientist whose research spans decades and disciplines, ranging from parallel computing architectures to cutting-edge artificial intelligence applications. Early in his career, Furht made foundational contributions to robotics and high-performance computing, pioneering dataflow multiprocessor systems for real-time robot arm control — work that addressed the computational challenges of nonlinear, multi-link robotic systems at a time when such problems were at the frontier of engineering research. In more recent years, Furht has demonstrated a remarkable capacity to evolve with the field, pivoting toward deep learning and its transformative real-world applications. His 2021 survey, "Deep Learning Applications for COVID-19," has garnered an impressive 350 citations, underscoring its significance as a comprehensive resource during one of the most urgent global health crises in modern history. The work spans Natural Language Processing, Computer Vision, Life Sciences, and Epidemiology, providing both a critical synthesis of existing research and a roadmap for future inquiry. Furht's career reflects a rare intellectual breadth — from hardware-level multiprocessing in the late 1980s to pandemic-era AI — making him a compelling figure for students navigating the evolving landscape of computer science and applied machine learning.