# Meng-Han Wu > Software Engineer @ Google | Purdue ECE PhD Location: San Francisco Bay Area, United States Profile: https://flows.cv/menghanwu With over two years of experience as a Full-Stack Engineer at Google, I leverage my PhD in Computer Engineering and my expertise in crowdsourcing and human-computer interaction (HCI) to develop and implement web applications and solutions that enhance user experience and engagement. I use Java, AngularJS, TypeScript, and other technologies to build a task management system that enables external contributors to process user feedbacks from 1) search results and 2) generative AI search responses. The processed results were used to ensure the correctness of the knowledge graph and improve the search generative AI model Before joining Google, I spent seven years as a Research Assistant and a Teaching Assistant at Purdue University, where I conducted cutting-edge research on HCI, crowdsourcing, and human computation. I published multiple papers and web applications that analyzed and visualized data from over 2,000 users, demonstrating my skills in statistical data analysis and front-end development. I also taught advanced C programming to more than 500 undergraduate students, showcasing my communication and leadership skills. I am passionate about applying my skills and knowledge to contribute to the advancement of technology and science. ## Work Experience ### Software Engineer @ Google Jan 2021 – Present | Mountain View, California, United States Android App Safety Engineering (Mar 2024 - present) SDK risk in Android. Working on LLM model to improve SDK risk detection. Knowledge Engine Trust & Feedback (Sep 2021 - Mar 2024) Tooling in Search. Working on a next-gen task management system that leverages user feedback and real-time data streams to identify and address search trust concerns, leading to lasting system-wide enhancements. ### Research Assistant @ Purdue University Jan 2015 – Jan 2021 | West Lafayette, Indiana Area Crowdsourcing unlocks solutions computers and humans alone can't achieve efficiently or effectively. But the key challenge lies in ensuring clear communication between requesters and workers. My research tackles this head-on, focusing on task design as the crucial bridge for accurate results and reduced variability. My dissertation explores how to elevate communication through four key strategies: 1. Targeted incentives: Attract workers with the right skills for the job. 2. Crystal-clear instructions: Leave no room for misinterpretations. 3. Optimal knowledge transfer: Choose the best method to share crucial task information. 4. Rapid AR prototyping: Empower requesters to quickly create immersive, interactive instructions. ### Teaching Assistant @ Purdue University Jan 2017 – Jan 2019 | West Lafayette Advanced C Programming, Teaching Assistant Fall 2017, Spring 2018, Spring 2019 - Wrote and managed automated testing of programming assignments - >300 students in Fall 2017; 184 students in Spring 2018; 159 students in Spring 2019 - Responsible for updating course web page and assignment descriptions - Office hours helping undergraduate students with C programming ### Software Engineer Intern @ Google Jan 2019 – Jan 2019 | Irvine ■ Built a Chrome Extension to help users easily insert links from multiple sources to webpage ■ Simplified implementation to pure frontend and reduced SLC from 4.2k to 1.3k ■ Implemented UI and data aggregation in TypeScript ■ Used Chrome Extension API to monitor user behavior and insert links to webpage ### Summer Internship @ CSBC Corporation, Taiwan Jan 2011 – Jan 2011 | Kaohsiung City, Taiwan ## Education ### Doctor of Philosophy (Ph.D.) in Electrical and Computer Engineering Purdue University Jan 2014 – Jan 2021 ### Bachelor's degree in Engineering Science National Taiwan University Jan 2009 – Jan 2013 ## Contact & Social - LinkedIn: https://linkedin.com/in/meng-han-wu --- Source: https://flows.cv/menghanwu JSON Resume: https://flows.cv/menghanwu/resume.json Last updated: 2026-03-22