Andy Kang
About Andy Kang
Andy Kang is a Staff Software Engineer at Synaptics Incorporated, specializing in deep learning and optimization for IoT applications. He previously worked as a Principal Software Engineer at Samsung Electronics for nine years.
Work at Synaptics
Andy Kang has been employed at Synaptics Incorporated as a Staff Software Engineer since 2015. In this role, he focuses on developing advanced software solutions, particularly in the realm of deep learning. He has contributed to the creation of a deep learning inference platform designed for executing TensorFlow Lite models on a compact Neural Processing Unit (NPU). His work is instrumental in enhancing the performance of various applications within the company.
Previous Experience at Samsung Electronics
Before joining Synaptics, Andy Kang worked at Samsung Electronics for nine years, from 2006 to 2015, in Hwaseong, Gyeonggi-do, Korea. During his tenure as a Principal Software Engineer, he gained significant experience in software development and optimization. His role involved working on projects that required a deep understanding of software engineering principles and practices.
Technical Expertise
Andy Kang specializes in optimizing convolution kernels specifically for ARM-based System on Chips (SoCs). His expertise extends to profiling and analyzing CPU and NPU latency, particularly in the context of Internet of Things (IoT) applications. This skill set enables him to enhance the efficiency and performance of software solutions in various technological environments.
Contributions to Image Processing
In his professional career, Andy Kang has worked on optimizing image processing and matching algorithms using ARM NEON technology. This work has been particularly relevant for optical fingerprint software solutions, where image accuracy and processing speed are critical. His contributions have helped improve the effectiveness of these biometric systems.
Development of Low Power Software
Andy Kang has developed low power software that incorporates sensor retention modes in firmware for capacitive fingerprint solutions. This development focuses on energy efficiency, which is crucial for devices that require prolonged battery life while maintaining performance standards.