I architect ZeroToOne's Large Behavioral Model, the platform unifying physical and digital behavioral traces at 1B+ signals daily for Fortune 500 marketing intelligence.
At Adobe, I led GenStudio's guideline-aware AI systems. Delivered semantic knowledge graph grounding that enabled Adobe's first fully AI-generated marketing campaign and 60% content velocity improvement.
Carnegie Mellon PhD in privacy-preserving behavioral modeling. Published in ISR, DMKD, KDD, Management Science with 250+ citations. Research deployed in ZeroToOne's production systems.
California. Wife. Cat named Binxy.
Ph.D. in Information Systems
2016 - 2021M.Sc. and B.Sc. in Mathematics and Computing
2009 - 2014Head of Artificial Intelligence
2024 - PresentSenior Machine Learning Engineer
2021 - 2024Founding ML Engineer
2017 - 2021Research Scientist
2014 - 2016• Multi-modal, multi-task foundational models
• Spatio-temporal trajectory modeling
• Unified behavioral representations
• Intent prediction
• Knowledge graph-augmented generation
• Parameter-efficient fine-tuning
• Fact verification systems
• Prompt optimization
• Distributed data processing
• Automatic feature engineering
• Model monitoring at scale
• Continuous learning systems
• Behavioral data platform architecture
• Predictive intelligence roadmap
• Enterprise AI transformation
• Scaling ML from prototype to production
• Building multi-disciplinary AI teams
• Fostering engineering excellence
• Translating data into measurable ROI
• Data-driven marketing solutions
• Cross-functional collaboration
Enterprise AI systems delivering measurable business outcomes.
Large Behavioral Model unifying physical and digital signals for predictive marketing intelligence.
Impact: 85% prediction accuracy • 1B+ daily signals • Media spend optimization
Semantic knowledge graph grounding for guideline-aware content generation.
Impact: 60% content velocity gain • Adobe's first AI campaign • Brand safety at scale
Differential privacy techniques enabling enterprise mobility intelligence.
Impact: Privacy-preserving analytics • ISR 2023 • COVID-19 response deployment
Subspace characterization algorithms for interpretable anomaly detection.
Impact: Enterprise fraud detection • Human-interpretable rules • DMKD 2018
Platform thinking over point solutions. Measurable impact over innovation theater.
I build AI organizations that ship. At ZeroToOne, architected the LBM platform from research to Fortune 500 production. At Adobe, delivered GenStudio's core AI capabilities.
My teams translate complex ML research into systems business leaders trust. Focus: composable platforms, not point solutions. Measurement-driven development. Systems that compound value.
Composable systems that enable rapid iteration and scale across diverse use cases.
Measurable business outcomes through systems that balance innovation with operational excellence.
Building teams that deliver immediate business value while maintaining technical excellence.
Research deployed in production. Patents protecting enterprise AI systems.
Interpretable anomaly detection using subspace rules for enterprise fraud and risk analysis • 68 citations
Privacy-preserving behavioral prediction balancing individual privacy with enterprise mobility intelligence • 48 citations
Large-scale behavioral analysis of privacy decisions enabling crisis response systems • 29 citations
Non-parametric attribution modeling for enterprise marketing spend optimization • 26 citations
5 patents • Enterprise content safety and generation
7 patents • Privacy-preserving ML for enterprise
3 patents • Enterprise knowledge representation
Total: 15+ patents across behavioral ML, GenAI, and privacy
Enterprise AI advisory. Speaking. Research collaboration.