Hi, I'm Chao P - Machine Learning Engineer at Google
I thrive at the intersection of complex research and practical application, building AI that powers the world's most critical search systems. My passion lies in scaling intelligence to solve real-world problems.
At a glance
Curated signals on strengths, focus areas, and how they can help.
Holds a PhD from UIUC and has contributed to major research publications in machine learning.
Engineers large-scale recommendation systems and search infrastructure within a major tech environment.
Offers technical mentorship in converting complex research models into high-impact, production-ready AI solutions.
🚀 Career trajectory
Academic Foundations
Completed PhD research focused on data mining and advanced AI at UIUC.
✦ PhD
✦ Researcher
Industry Acceleration
Transitioned to roles at Meta and TikTok to apply research to social discovery.
✦ Applied Research
✦ Large-Scale ML
Production Leadership
Currently leading ML efforts at Google, focusing on search and LLM deployment.
✦ Production AI
💪🏻 Superpowers
Production-Grade AI Architecture
Scaling complex models into robust, real-world production environments.
✦ Architecting high-throughput machine learning pipelines for global user bases.
✦ Transitioning theoretical breakthroughs into efficient, reliable infrastructure.
✦ Optimizing neural network performance for massive search and recommendation engines.
Research-Driven Innovation
Applying state-of-the-art methodology to solve complex data challenges.
✦ Applying Graph Neural Networks to improve complex recommendation accuracy.
✦ Developing privacy-preserving machine learning frameworks for data sensitivity.
✦ Publishing novel advancements in top-tier machine learning conferences.
Interdisciplinary Synthesis
Connecting diverse technical domains to create cohesive AI systems.
✦ Integrating computer vision with large-scale search infrastructure.
✦ Synthesizing spatio-temporal data analysis with real-time route planning.
✦ Driving technical convergence across engineering and data science teams.
I'm excited about
✦ Seeking peer networks in large-scale model optimization and production AI.
✦ Exploring cross-industry collaborations on privacy-preserving machine learning.
✦ Identifying innovative startups pushing boundaries in LLM-driven search experiences.
I can help with
✦ Mentoring junior researchers on bridging the gap between academia and industry.
✦ Providing expert guidance on scaling production ML pipelines for high-traffic apps.
✦ Advising on research strategy for recommendation systems and Graph Neural Networks.
I would love your help on
✦ Connecting with experts in distributed AI training and infrastructure cost optimization.
✦ Gaining insights into the evolving landscape of AI-based product discovery.
✦ Seeking strategic advice on balancing long-term research with short-term business impact.