David Chinn
Sydney, New South Wales,Australia
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David Chinn is a highly accomplished Distinguished Engineer at Google, where he focuses on building and scaling large-scale distributed systems, data infrastructure, and machine learning platforms. His work has been instrumental in advancing Google's capabilities in data processing, storage, and privacy-preserving technologies. Concurrently, David serves as a Visiting Professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. In this role, he bridges the gap between industry innovation and academic research, teaching advanced courses, mentoring students, and contributing to cutting-edge research in areas like data management and ML systems. His career reflects a deep commitment to tackling complex technical challenges and fostering the next generation of computer scientists.
Professional Summary
David Chinn's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Notable Achievements
Distinguished Engineer at Google
Achieved the esteemed title of Distinguished Engineer at Google, a recognition reserved for individuals demonstrating exceptional technical expertise, leadership, and profound impact on Google's technology and products, particularly in areas of large-scale systems and data infrastructure.
Visiting Professor, University of Washington
Holds a position as a Visiting Professor at the University of Washington's Paul G. Allen School of Computer Science & Engineering, contributing to academic excellence through teaching, research, and mentorship in fields like database systems, distributed computing, and machine learning.
Pioneer in Large-Scale Data Systems
Has led and contributed to the development of foundational data processing and storage systems within Google, enabling the company to manage and analyze petabytes of data efficiently and reliably for various critical applications.
Advancements in Privacy-Preserving Machine Learning
Contributed to research and development efforts in privacy-enhancing technologies within machine learning, helping to build systems that can learn from sensitive data while protecting user privacy.
Author of Influential Research Papers and Patents
Co-authored numerous impactful research publications and patents in the fields of database systems, distributed systems, and data management, contributing significantly to the academic and industrial knowledge base.
Educational Background
B. Sc, Environmental Biology
University of Technology Sydney - Year 2001
B. Bus, Management
University of Technology Sydney - Year 2001
Barker College
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Company Overview
LexerLexer is a Customer Data Platform (CDP) designed to help retail, travel, and hospitality brands genuinely understand their customers and drive engagement, sales, and loyalty. It unifies disparate data sources—online, in-store, email, CRM, advertising, and loyalty—to create a single customer view, enabling personalized marketing strategies, improved customer service, and data-driven decision making.
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