Research
Our three core research areas pushing the boundaries of analog IC design.
Analog Design Automation
Investigating the use of AI/machine learning-assisted topology selection and transistor sizing for analog circuits. We train machine learning models to select the optimal topology for a given set of design requirements and develop systematic methods for synthesizing innovative circuit architectures using two-port network modeling techniques and symbolic math solvers.
Silicon Photonics & Optical Communication
Design and development of advanced optical communication systems based on silicon photonics. We integrate silicon waveguides with receiver components such as photodetectors, transimpedance amplifiers (TIA), variable gain amplifiers (VGA), clock and data recovery (CDR) circuits, and equalizers to achieve efficient, high-speed data transmission with low power consumption for data centers and next-generation communication networks.
Ultra-Low Power IoT Sensor Interfaces
Development of ultra-low power analog sensor interfaces critical for IoT applications. We optimize power consumption in analog ICs while maintaining high performance and reliability, enabling self-powered platforms for smart sensing and wireless transmission.