Hasan Genc

The University of Texas at Austin, University of California, Berkeley

Papers

Total Citations

H-Index

About

Hasan Genc is a researcher at the forefront of embedded and autonomous systems, specializing in the intersection of computer vision, energy-efficient computing, and cyber-physical systems. His work is driven by the critical need to make intelligent machines—from autonomous vehicles to Micro Aerial Vehicles (MAVs)—faster and more energy-efficient without sacrificing accuracy. Genc’s major contributions include pioneering domain-specific approximations for object detection, a technique that strategically trades off precision for speed, enabling real-time performance in resource-constrained environments like advanced driver assistance systems. This work, his most cited with 11 citations, directly addresses the computational bottleneck in autonomous navigation. He further advanced the field by analyzing the role of on-board compute in MAVs, optimizing for both mission time and energy efficiency—a crucial insight for applications like surveillance and package delivery. With a growing citation impact and a focus on practical, deployable solutions, Genc’s research is shaping the next generation of autonomous, mobile cyber-physical machines, making them more viable for real-world missions.