A chronological view of my work, research, products, and career milestones.
Built a lightweight model that established interaction tracking as a first-class perception target. Raised accuracy from under 50% with a flagship VLM to over 80%, while cutting per-frame latency from 15 seconds to 0.22 seconds.
The physical world is not a collection of isolated objects. It is a stream of interactions. Interaction tracking is the right abstraction for Physical AI, yet it remains absent as a first-class perception target.
Relaxes LLM-JEPA's two-view requirement through randomized fractional views and introduces a JEPA-style regularizer that improves signal-to-noise ratio and preserves diversity during LLM fine-tuning.
First successful integration of JEPA with LLMs, establishing JEPA as a practical regularizer for language models while eliminating the moving-average mechanism traditionally required to stabilize JEPA training.
Helped organize and shape the AI/ML for Distributed Systems track at ICDCS 2025.
Led fine-tuning of Atlassian’s first 70B model for code review, using DeepSeek-generated review reasoning to improve review quality.
A one-step adversarial distillation method for diffusion models that improves both sample quality and distillation efficiency.
Originated the vision that the CLI would become the ultimate battleground for coding agents, despite the success of IDE-based workflows. Built a coding-agent CLI integrated with Atlassian’s Jira and Confluence ecosystem, bringing project context and developer workflows directly into the terminal.
A data-free method that distills the generative capabilities of pretrained diffusion models into a single-step generator.
Developed a self-supervised representation-learning system that discovered semantic structure without predefined domain knowledge. Improved system performance by approximately 50× and enabled applications across Google Search, Google Cloud, and Google Ads, including test selection, LLM context retrieval, and integration optimization.
Benchmarked Spanner against Bigtable and showed that, for representative read-heavy cloud workloads, Spanner could deliver lower latency while providing stronger transactional guarantees. The work helped shift Spanner’s perception from a specialized database accepted despite its performance tradeoffs, and also demonstrated approximately 3× higher simulated transaction throughput using three proposed capabilities.