San Jose, California, United States
• Led cross-functional team to research, build, and drive adoption of deep learning vision models for single cell detection. Achieved 24% higher candidate counts and 3 percentage points lower doublet rates while eliminating user-facing analysis wait time. • Led cross-functional team to research and build generative AI LLM agents and ML models to accelerate development and analysis of liquid handler chemistry protocol automation. • Led effort to research, build, and train AI optimization models using reinforcement learning. • Architected and developed custom AI inference engine for serving fast, real-time model inference across all Takara instruments, with 10x faster I/O speed and at-rest encryption for proprietary IP on deployed hardware. • Developed computer vision algorithms for automated high-precision instrument calibration (auto-focus, alignment) and checks (verifying proper loading and reading IDs of consumables). • Built and managed on-premises AI compute cluster to enable internal R&D model training and inference as well as experiment tracking. • Responsible for establishing AI standards and delivering seminars highlighting and advocating for AI initiatives at Takara. Led all instrumentation-related AI R&D efforts. • Architected and developed control software for qPCR liquid handler instrument. Served as sole technical product owner, taking user feedback, supporting in-house experiments, orchestrating cross-functional collaboration, and communicating with field service team to support in-field instruments. • Designed modern UI/UX style system for use across Takara’s qPCR and single cell instrumentation.