Research Interest

My research interest is mainly in deep learning and photolithography process system integration. As a photolithography engineer, I have been working with various types of lithography tools and process systems. This allows me to have a better understanding of the lithography process and the challenges faced by the engineers. By developing novel systems that helps to improve the current process, I was able to accumulate approximately $10M annual cost savings through various system projects. Some of the projects involves the use of deep learning to detect defects from the wafer images. These projects are aimed to be able to detect defects in real time fashion (~1s) and outperform the vendor’s defect detection system.

Resume

Work Experience

Photolithography Process and Equipment Senior Engineer, Micron Technology (Aug 2018 - current)

Contribute as an individual contributor in areas including: photolithography systems, defect detection systems, automation software development, and machine learning projects to drive yield improvement/capacity optimization/cost reduction.

• Led the photo team through IATF 16949:2016 audit certification as audit rep without non-conformance, enabling the qualification of automotive memory supply to customers
• Accumulate 2.5M savings world wide per year through development of labour productivity automation project MyAssistant
• Initiated reticle-related project with intend of reducing/eliminating late detection of foreign particle introduction on reticle with a normalized annual 5M business value
• Developed personnel tracking dashboard during COVID for trace tracking and quarantine
• Facilitate training and mentoring to group of developers under Smart Manufacturing initiative to accelerate digital transformation

Education

Master of Science in Industrial 4.0, National University of Singapore (Aug 2021 - Jul 2023)

• Capstone Project: Auto Correlation Study and Forecasting in Yield Analysis

Bachelor of Engineering in Material Science and Engineering, Nanyang Technological University (Aug 2014 - Jul 2018)

• Final Year Project: Facile Formulation For Soil Conditioning And Moisturizing

Projects

MyAssistant

MyAssistant is develop to address one of the main concern of Process and Equipment Engineers – requesting additional sampling for process understanding and compiling the historical data in a presentable manner. It is a full-stack web application development project that aims to be robust and scalable. The project’s technological stack includes Micron’s in-house frontend framework Omelek (based on Angular) and Flask as the web application’s backend. HTTP requests are directed to an api gateway before forwarding to the intended microservice(s). The requests are choreographed such that each sub-request are transactional-like. Other technologies including Nginx, Celery, Redis and RabbitMQ are used to support the application. The automated CI/CD pipeline is build based on Jenkins and Docker to help push code changes to production. ELK stack is used to monitor the production containers and host machine’s health together with usage metric monitoring.

Awards

• Selected as Micron’s Productivity Idea of Quarter in Q4 2022 with annual 5M cost savings
• Roll out as Micron’s Productivity BKM and is adopted at Micron sites worldwide