Dooyong Koh

Dooyong Koh, a graduate student in electrical engineering and computer science, explores energy-efficient electronic devices with the aim to redefine the future of semiconductor technology. His research focuses on harnessing ferroelectric materials for ultra-low-power logic and memory, including pioneering work on negative capacitance transistors that enhance performance while reducing energy use. As a MathWorks Fellow, Dooyong will optimize gate dielectrics built from hafnia–zirconia–based materials to overcome traditional scaling bottlenecks, aiming to deliver next-generation logic and memory. He utilizes MATLAB’s Curve Fitting, Statistical Analysis, and Machine Learning Toolboxes to extract parameters, such as charge carrier injection velocities, from ferroelectric device measurements. By uniting material innovation with computation, Dooyong’s work is poised to transform how chips are designed, enabling smaller, faster, and more energy-efficient technologies for the future of computing.