WENCHENG ZOU
Los Angeles,CA
Summary
Diligent Ph.D. student focused on machine learning and intelligent systems and dedication to prompt project completion and continual adaptation. Experienced researcher on polynomial regression and gradient descent. Talented candidate in graph neural network and hardware error detection. Team-oriented collaborator with reliability and focus on equitable task distribution through group projects and motivation to accomplish mutually held goals. Creative employee in machine learning implementation in EDA.
Overview
4
4
years of professional experience
Work History
AI Model Data Training Contractor
Scale AI
01.2024 - 04.2024
- Wrote C++, Java, and Python codes for the provided LLM to help it generate more data.
- Verified the response of LLM from different tasks based on accuracy and brevity.
- Modified the response from LLM to help fine-tuning the models.
EDA Machine Learning CO-OP
Skyworks Solutions, Inc
Irvine, California
05.2023 - 12.2023
- Coded the general tests for all PDK: cdf file and technology file test, PCell validation test, Layout test using cadence skill script and Keysight Eggplant Automation Script
- Designed an automation system that can finish PDK specific GUI tests using both Cadence Skill Scripts and Keysight Eggplant Script
- Predicted PDK design's deviations with multivariate polynomial model on the dataset with high dimensional data
- Developed Coordinate Descent Algorithm using pandas and scikit-learn packages to optimize filter design and find the best combinations of filter design variables
- Communicated with team members about optimization algorithms and proposed personal suggestions and ideas
- Evaluated robustness and efficiency of algorithm and model based on different filter design datasets
- Obtained goal of optimization 3 times faster than the algorithm in ADS.
Machine Learning Researcher
Shandong University
Shandong
07.2020 - 08.2020
- Collected COVID-19 pandemic data in each state in the U.S from Johns Hopkins University (JHU)
- Preprocessed data by choosing certain attributes and setting time windows based on theory of Markov Chains
- Utilized machine learning models such as Lasso Regression, Ridge Regression, and deep learning models such as Fully Connected Neural Network to predict positive cases
- Communicated with group members to discuss details of preprocessing dataset and choices of regression models
- Evaluated accuracy rate of these models based on mean square error (MSE), R2-Square
- Concluded that Lasso and Ridge regression fit into dataset better with the R2 score of 0.9.
Education
Ph.D. - Computer Engineering (Machine Learning)
George Washington University, The
Washington, DC05-2029
Master Of Science - Computer Engineering
University of Southern California
Los Angeles, CA12.2023
Bachelor Of Science - Software Engineering
Shandong University
Weihai City, Shandong Province06.2021
Skills
- Data Analysis
- Machine Learning/Deep Learning
- Python
- Pytorch Geometric (PyG)
- Tensorflow
- Keras
- Scikit-learn
- Numpy
- EDA
- Cadence Skill Script
- Keysight Eggplant Script
- Linear and polynomial Regression
- LSTM
- RetinaNet
- Graph Neural Network
Publications
Wencheng Zou, The COVID-19 Pandemic Prediction in the US based on Machine Learning, accepted by ICPHDS (2020 International Conference on Public Health and Data Science), 283-289, DOI 10.1109/ICPHDS51617.2020.00062
Links
- Https://ieeexplore.ieee.org/document/9361928
- Https://github.com/WenchengZou/FinallProjectForAIHUB
Timeline
AI Model Data Training Contractor
Scale AI
01.2024 - 04.2024
EDA Machine Learning CO-OP
Skyworks Solutions, Inc
05.2023 - 12.2023
Machine Learning Researcher
Shandong University
07.2020 - 08.2020
Ph.D. - Computer Engineering (Machine Learning)
George Washington University, The
Master Of Science - Computer Engineering
University of Southern California
Bachelor Of Science - Software Engineering
Shandong University
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