About
ML engineer and founder with a background across healthcare, fintech, and autonomy. Blends research with product instincts.
Background
ML engineer and founder with experience building production systems across healthcare, fintech, and autonomy. Comfortable owning the whole lifecycle from data to deployment, with a focus on systems that scale and deliver measurable business impact.
Research background in computer vision and medical AI, with publications in histopathology and multimodal systems. Teaching experience includes designing and delivering AI curriculum that transforms students into practitioners capable of building end-to-end systems.
Entrepreneurial experience includes founding multiple companies, raising venture funding, and leading cross-functional teams through product development and market validation. Focus on bridging the gap between cutting-edge research and practical business applications.
Technical Principles
Core beliefs that guide technical decision-making and system design.
Correctness over Cleverness
Simple, reliable solutions that work consistently in production environments.
Reliability under Load
Systems designed to handle real-world scale with graceful degradation and monitoring.
Interpretable Results
ML models and systems that provide clear insights and actionable outcomes.
Mindful Data Provenance
Careful attention to data quality, bias, and ethical implications throughout the pipeline.
Leadership Approach
Building high-performing teams through clear communication and shared ownership.
Servant Leadership
Leading by enabling others to succeed and removing obstacles to team productivity.
Clear Interfaces
Defining clean boundaries between systems, teams, and responsibilities.
Mentoring Focus
Investing in team growth through knowledge sharing and skill development.
Strong Documentation
Maintaining clear, up-to-date documentation for sustainable system evolution.
Teaching & Mentorship
Course design and instruction that turns ideas into working systems. Focus on hands-on learning that bridges theory with practical implementation. Committed to developing the next generation of ML practitioners who can build reliable, scalable systems.