Xinqiao Zhang
Senior Machine Learning Scientist at CoreLogic
Specializing in GenAI, Deep Learning, and Trustworthy ML
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Resume Highlights
A concise overview of my qualifications and experience
Professional Summary
Senior Machine Learning Scientist with extensive expertise in GenAI, Deep Learning, and Trustworthy ML. Experienced in designing secure AI systems, developing neural network watermarking techniques, and optimizing machine learning models for efficiency. PhD from UC San Diego, focused on AI security and hardware acceleration.
Core Competencies
AI Security
Expertise in developing robust ML systems resistant to adversarial attacks. Led team to 2nd place in NIST TrojAI competition.
GenAI & LLMs
Building secure retrieval-augmented generation systems. Implemented RAG for LLMs that achieved 80% time savings.
Hardware Optimization
Designing efficient hardware acceleration for deep learning. Created systems achieving 2-11x faster inference.
Media Authentication
Creating watermarking techniques to counter deepfakes. Developed FaceSigns with 90%+ detection accuracy.
Professional Experience
Senior Machine Learning Scientist
CoreLogic
- Working on cutting-edge GenAI projects
- Implementing secure RAG systems for enterprise data
- Developing ML models for real estate data analysis
Founder and Chief Technology Officer
Check-It Analytics
- Founded and led development of AI-driven financial information platform
- Implemented RAG for LLMs to streamline financial processes
- Achieved up to 80% time savings compared to traditional platforms
Research Intern
Arm
- Developed data distillation algorithm for ML efficiency
- Reduced data size to at least 1/10,000
- Improved ML model performance by at least 50%
Graduate Student Researcher
UC San Diego
- Developed techniques for identifying compromised AI models
- Led team to 2nd place in NIST TrojAI security challenge
- Published in top-tier conferences including ICCV and NeurIPS
- Filed 5 patents related to AI security and watermarking
Education
PhD, Computer Engineering
University of California, San Diego
Aug 2024
Advisor: Prof. Farinaz Koushanfar
Focus: AI Security, Hardware Acceleration, Neural Watermarking
MS, Electrical Engineering
San Diego State University
Dec 2019
BS, Electrical Engineering
Northeastern University (China)
May 2017
Key Achievements
Outstanding Paper Award at NeurIPS 2022 TSRML Workshop for "zPROBE: Zero Peek Robustness Checks for Federated Learning"
DAC Young Fellow at the 58th Design Automation Conference (2021), recognizing promising early-career researchers
Contributed to 5 patent applications in AI security, neural watermarking, and hardware optimization
Author of 10+ publications in top-tier conferences and journals (ICCV, NeurIPS, ACM TECS, IEEE TETC)
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