AI Researcher · Engineering Lead · Google DeepMind
Building the future of AI — from large language models and generative AI to agentic systems that reason, plan, and act.
I'm an AI researcher and engineering lead at Google DeepMind, where I work on Project Astra and Gemini — building the next generation of AI agents and large language models.
My work sits at the intersection of generative AI, agentic systems, model quality & evaluation, and ML infrastructure. I care deeply about making AI systems more capable, reliable, and useful.
Before DeepMind, I built systems at Google, Yahoo, NetApp, and Symantec/Veritas, and contributed extensively to OpenStack. I hold degrees from Stanford University and The Ohio State University.
Building and evaluating frontier LLMs including Gemini 2.5 and Gemma 2. Deep expertise in model architecture, training, and inference optimization.
Pioneering generative AI systems that create, reason, and solve complex problems. From multimodal models to creative applications.
Designing AI agents that plan, reason, and take action. Contributing to Project Astra — Google DeepMind's universal AI assistant prototype.
Developing robust evaluation frameworks, benchmarks, and quality metrics to measure and improve model capabilities across tasks.
Scaling machine learning systems from research to production. Experience building distributed training and serving infrastructure at Google scale.
Background in high-performance computing, parallel filesystems, and distributed data systems. Building reliable data pipelines for ML at scale.
Engineering — Astra + Gemini
Working on Project Astra and Gemini models. Contributing to frontier AI research including Gemini 2.5 and agentic AI capabilities. Focus on agents, generative AI, LLMs, model quality, and evaluation.
Software Engineering
Built large-scale systems and infrastructure. Contributed to ML and distributed systems work across Google's platform.
Engineering
Worked on infrastructure and platform engineering at Yahoo's scale.
Engineering
Built storage and data management systems. Applied expertise in distributed systems and high-performance I/O.
Software Engineering
Early career in enterprise software engineering, working on storage and data protection systems.
Advanced studies in computer science and AI.
Research in high-performance computing, parallel filesystems, and distributed systems.
Selected publications spanning frontier AI models, distributed systems, and high-performance computing.
Technical report on the Gemini 2.5 model family, advancing state-of-the-art in reasoning, multimodal understanding, long-context processing, and agentic AI capabilities.
Read Paper →Advancing open-weight language models with improved quality and efficiency, making capable AI more accessible to the research community.
Read Paper →Designing a decentralized metadata service layer to improve the scalability and performance of metadata operations in parallel filesystems while maintaining reliability and consistency.
View on DBLP →Exploring hierarchical data staging approaches to improve the efficiency of checkpoint/restart mechanisms in high-performance computing clusters.
View on DBLP →Active contributor to major open-source projects, with significant contributions to the OpenStack ecosystem.
Core contributor to OpenStack's compute service. Authored blueprints and fixes for Nova-Cinder volume lifecycle interactions and ServiceGroup drivers.
Contributed to OpenStack's block storage service, including quota management fixes for hierarchical multi-tenancy and subproject defaults.
Contributions to OpenStack's shared filesystem service for managing file shares across cloud environments.
Worked on OpenStack's identity and authentication service, supporting secure multi-tenant cloud deployments.
Interested in collaborating on AI research, discussing generative AI and agentic systems, or connecting about engineering leadership? I'd love to hear from you.