Sergazy Nurbavliyev
Mathematician | AI/ML Specialist | Google Hackathon Grand Prize Winner | Entrepreneur | Turning research into real-world AI solutions
About Me
Passionate About AI Innovation
Senior ML Researcher (PhD, Math) with 5+ years of experience delivering ML, DL, RL, and LLM systems at scale in e-commerce and advertising. Led agent-based LLMs and pricing/ad tech optimizations driving $20M+ revenue. Strong academic background in probability theory, stochastic processes, combinatorics, statistical mechanics, nonparametric statistics, and Bayesian modeling.
Key Achievements
Industry Recognition
Featured in top AI conferences and publications
Business Impact
Delivered $10M+ in measurable business value
Team Leadership
Led cross-functional teams of 15+ professionals
Innovation
Pioneered cutting-edge ML solutions and frameworks
Professional Experience
A journey through innovative companies where I've built scalable AI solutions and led high-performing teams
Senior Machine Learning Researcher
Beyond (formerly Overstock.com)
Technologies Used:
Machine Learning Scientist
Overstock.com
Technologies Used:
Ph.D. Student in Mathematics
University of Utah
Technologies Used:
Mathematics Instructor
Suleyman Demirel University, Kazakhstan
Technologies Used:
Research Assistant
Boğaziçi University
Technologies Used:
Instructor
Suleyman Demirel University, Kazakhstan
Technologies Used:
Featured Projects
Showcasing innovative AI and machine learning solutions that drive real business impact
Won Grand Prize at Google Cloud Agent Development Kit hackathon (10,000+ participants). Built 34 specialized agents orchestrated via ADK, deployed as microservices on Google Cloud Run with advanced orchestration patterns.
Developed internal AI assistant for Beyond enabling teams to query pricing, promotion, product, inventory data from documents, spreadsheets, and images with OCR and metadata extraction.
Advanced AI system combining multiple data modalities for enhanced information retrieval and generation capabilities with state-of-the-art performance.
Research into autonomous AI agents and their applications, exploring advanced agent architectures and coordination mechanisms for complex problem-solving.
ML-driven advertising optimization platform that maximizes ROI through intelligent bid management and audience targeting strategies.
Personalized marketing system that uses ML algorithms to deliver targeted coupon recommendations, increasing customer engagement and conversion rates.
Technical Skills
Comprehensive expertise across modern technologies and frameworks
Programming Languages
ML Frameworks
Cloud Platforms
MLOps/DevOps Tools
Databases
Statistical Methods & Optimization
Education
Academic foundation and continuous learning journey in technology and innovation
University of Utah
Ph.D. in Mathematics
Specialized in probability theory, stochastic processes, and mathematical analysis. Conducted research on random walks in random environments with applications to statistical mechanics.
Relevant Coursework
University of Utah
M.S. in Statistics
Focused on advanced statistical methods, machine learning, and data analysis. Applied state-of-the-art machine learning models to construct prediction engines for complex datasets.
Relevant Coursework
Boğaziçi University
M.S. in Mathematics
Advanced study in probability theory, statistical inference, and mathematical modeling. Conducted research in theoretical probability and statistical mechanics.
Relevant Coursework
Boğaziçi University
B.S. in Mathematics
Strong foundation in pure and applied mathematics, including analysis, algebra, topology, and mathematical modeling. Graduated with highest honors.
Relevant Coursework
Selected Publications
Research contributions in mathematics, probability theory, and statistical mechanics
A Debiased Machine Learning Framework for Optimizing Price Promotion within E-commerce
Published in the Applied Data Science Track at KDD 2025. Proposed the Delta Method, a de-meaning technique inspired by fixed-effects regression, to isolate within-product variation and estimate causal treatment effects from observational data. Demonstrated a 3% increase in revenue and 2% increase in profit via a real-world pricing experiment using the method on a furniture e-commerce platform.
A shape theorem and a variational formula for the quenched Lyapunov exponent of random walk in a random potential
We study the quenched Lyapunov exponent of random walk in a random potential and establish a shape theorem and variational formula for this quantity. Our results provide new insights into the behavior of random walks in random environments with applications to statistical mechanics and probability theory.
Get In Touch
Ready to collaborate on your next AI project? Let's discuss how we can bring your ideas to life.
Let's Start a Conversation
I'm always excited to discuss new opportunities, innovative projects, and potential collaborations. Whether you have a specific project in mind or just want to explore possibilities, I'd love to hear from you.
Location
Salt Lake City, Utah, United States