Research in the lab focuses on designing and optimizing key photonic components such as tapers, multimode interferometers (MMI), Mach-Zehnder modulators (MZM), splitters/combiners, and wavelength division multiplexing (WDM) devices to enhance energy efficiency, reduce costs, and minimize losses and reflections.
It further integrates AI and machine-learning tools to improve the synthesis platforms they develop, including Rsoft-CAD and Lumeciel, leveraging NVIDIA GPUs for computational acceleration.
Beyond silicon photonics, the lab also explores AI-driven image processing for detecting mind wandering and human behavior analysis, integrating CNN-based optical modules.
In addition, the Lab provides hands-on training in image processing and photonic chip design, enabling students to develop innovative solutions for AI photonics.
Contact: Dr. Dror Malka
Located: Building 1, Room 504
