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Mental Health Rating System for National Taiwan University Students Director: Professor Kai-Ping Yao (Department of Psychology, National Taiwan University) Responsibility for the project The main goal for me is to constructing the Computerized Adaptive Testing for Students to reduce the time-consuming questionnaire but with high percentage of correct classification which students should be taken care of more. This is my first time constructing a test with real data . Instead of simulated data, empirical data with time and social effect may influence the test validity and reliability. To reduce the interaction between the confounding variable and

AI/ML solutions to accelerate yield ramping and virtual metrology , design system architecture for analysis/inference at scale . Projects Chip image pattern recognition. Apply various Deep/Machine Learning technique to cluster sub-die issue pattern for users. Implement supervised VAE and Xception model for classification with ~90% accuracy. Interactive with yield auto diagnostic system, provide root cause in minutes. Yield Auto Diagnostic Automatically analysis/search the yield opportunity and/or the root cause of issues. Hundreds of yield toggle have been found via this system, saving millions of dollars