Taipei, Taiwan
As an innovative and results-driven Senior FPGA Application Engineer with a Ph.D. in deploying AI models on edge computing devices, I bring extensive experience in FPGA design, artificial intelligence, machine learning, and deep learning. My expertise spans deploying and managing AI projects on Xilinx and Jetson platforms. Proficient in Python, C/C++, Vitis-AI, ROCm, and CUDA, I am passionate about leveraging cutting-edge technologies to deliver impactful solutions that drive technological advancements and benefit society.
Jan 2023 - Present
As a Senior FPGA Application Engineer, I specialize in the intersection of machine learning, AI, and FPGA technology. My work involves deploying advanced AI models and their implementation on edge devices, particularly leveraging Xilinx FPGAs and Jetson boards. I am adept at AI model training, hardware configuration, and integrating complex machine learning systems.
Sep 2019 - Dec 2022
I have done extensive research in the field of BNN of CNN and FCN for segmentation on SoC FPGA. Additionally, he was involved in industrial cooperation projects including DPU AI machine learning on E-elements PYNQ ZU FPGA and the development of open-source RISC-V using E300 SiFive core on E-element EGO-1 FPGA. His expertise in AI edge implementation on embedded platforms has been particularly noteworthy and positions him as a leading researcher in this burgeoning field
Feb 2016 - Jan 2017
The job responsibility involves operating advanced nanomaterial characterization instruments, such as X-ray Diffraction (XRD), Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM), and Transmission Electron Microscopy (TEM), to analyze and collect data on material properties. This includes preparing samples, running experiments, and using specialized software to interpret the results. The role requires maintaining detailed records of experiments, ensuring the accuracy and quality of data, and troubleshooting any issues with the instruments.
May 2014 - Feb 2016
The job responsibility involves the fabrication of a Resistive Plate Chamber (RPC), a type of gas detector used in particle detection experiments. This includes constructing the RPC, which typically consists of parallel resistive plates separated by a gas-filled gap. The role also involves designing and developing a front-end electronics system that can efficiently collect and process the data generated by the RPC. This system manages signal amplification, filtering, and digitization to ensure accurate data acquisition. The position requires a strong understanding of both the physical construction of the gas detector and the electronics required to interface with it, supporting high-quality data collection for research or monitoring purposes.
Aug 2013 - Apr 2014
Taught Signal Systems, Applied Engineering Mathematics, and Electronics Devices, focusing on signal processing, differential equations, and electronic circuits.
2019 - 2023 Ph.D.
2017 - 2019 M.Tech.
2008 - 2012 B.Tech.
2004 - 2006