# Zilu Zhang

> Software Engineer in Google

Location: San Francisco Bay Area, United States
Profile: https://flows.cv/zilu

M.S. Software Engineering student in Carnegie Mellon University, Silicon Valley. Strong interests in Machine Learning and Artificial Intelligence, and willing to apply cutting-edge technologies in industrial products. Also interested in interpreting and analyzing data and models in ways of visualization.
Actively looking for 2020 full-time positions in San Francisco Bay Area.

## Work Experience
### Software Engineer @ Google
Jan 2020 – Present | Sunnyvale, California, United States
• Efficiently order, plan and fulfill compute, storage, ML, network, and infrastructure resources for Alphabet's fleet.
• Optimally perform fleet actions while facilitating touchless fleet transformations supporting Alphabet's capacity growth.

### Software Engineer Intern @ Apple
Jan 2019 – Jan 2019
SDE Intern in FileMaker DevOps Team
• Designed and deployed a serverless engine on AWS to collect raw logs from Lambda API calls, EC2 systems and DynamoDB to form an organized, partitioned and SQL-queryable Data Lake and replicate DynamoDB tables hourly. 
• Used Glue to perform ET and data cataloging on semi-structured data, and extracted various identifiers to form mappings for correlation purpose.
• Automated engine deployment using CloudFormation. The engine helped DevOps team on troubleshooting and monitoring with high scalability and low maintenance.

### Graduate Research Assistant @ Carnegie Mellon University Silicon Valley
Jan 2018 – Jan 2018 | San Francisco Bay Area
•  Running LSTM, feedforward neural networks and other deep learning networks on sequential datasets, such as air quality over years and traffic flows throughout days, digging into trained models and exploring interpretations for model behavior.

### Research Intern @ Megvii Technology Limited (Face++)
Jan 2017 – Jan 2018 | Beijing, China
Meta-learning, Face Recognition Group

### Summer Research Student @ UCLA
Jan 2017 – Jan 2017 | Los Angeles, US
• Statistical and Relational Artificial Intelligence (StarAI) Lab. Advisor: Prof. Guy Van den Broeck.
• Proposed a differentiable function for propositional logic sentence to capture how well a probability distribution is to match the logic. Supplementing the function as a semantic loss to neural networks in order to improve probability of model outputs satisfying constraints.
• Achieved (near-)state-of-the-art results on semi-supervised classification on MNIST & CIFAR-10, and increased ability of feedforward neural networks to predict structured objects, such as shortest paths and rankings, by 23% and 12% respectively.
• Research paper accepted to ICML 2018.

### Intern @ Microsoft Research Asia
Jan 2017 – Jan 2017 | Beijing, China
Short-term intern in Software Analytics Group, Microsoft Research Asia. Mentor: Han Shi
• Spreadsheet Data Detection: Built a CNN model to detect tables on real-world Microsoft Excel spreadsheets. Implemented data preprocessing and feature extraction code in C# individually. Improved detection accuracy from 80% to 95%. 
• Table Layout Analysis: Analyzed cell features in C# using regular expression and Microsoft Excel patterns to evaluate layout similarity along rows and columns. Created cascade model to classify row-major, column-major and cross tables, reaching an classification accuracy of more than 90%.


## Contact & Social
- LinkedIn: https://linkedin.com/in/zilu-zhang

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Source: https://flows.cv/zilu
JSON Resume: https://flows.cv/zilu/resume.json
Last updated: 2026-03-29