Secure, negotiate, and maintain strategic partnerships, ensuring alignment between technical prototypes and long-term organizational goals.

Lead and manage a diverse, global team, fostering cross-continental collaboration, continuous improvement, and innovation in high-stakes technology projects.

Plan long-term projects by anticipating legal, business, and ethical implications of emerging technologies, ensuring responsible and sustainable adoption.

Scoped and delivered AI-driven case-lead identification pipelines, iterating on LLM prompts and outputs to improve classification accuracy and usability.

Regularly presented technical findings to non-technical stakeholders (executives, legal teams, regulators), bridging gaps between engineering, business, and law.

Mentored junior consultants, building internal capacity around data analysis, responsible AI practices, and cross-functional collaboration.

Analyzed large-scale pharmaceutical datasets (>20TB) to identify unusual ordering and distribution patterns, applying statistical modeling across geography, seasonality, and product characteristics.

Conducted rigorous code and algorithm reviews, surfacing technical risks (fairness, scalability, transparency) and potential legal implications.

Delivered dashboards and presentations to help non-technical stakeholders interpret findings and inform litigation and business strategy.

Partnered with program teams to evaluate AI adoption pathways, balancing technical feasibility, compliance, and ethical considerations.

Supported cross-functional project planning and workflow management, ensuring timely delivery across legal, business, and engineering teams.

Conducted market and data analysis for a global entertainment client, building equitable payout frameworks for digital creators using applied ML and statistical methods.

Translated complex codebases and legal documentation into actionable insights for business leaders, influencing strategy across multiple jurisdictions.

Experimented with early-stage AI/ML prototypes to assess real-world applicability, usability, and adoption barriers.

Collaborated with diverse stakeholders across technical and legal teams to ensure strategies were both data-driven and ethically grounded.

Focused on developing low-cost, minimally invasive mobile health applications to improve healthcare access in underserved communities.

• Designed, validated, and deployed novel CNN architectures to automate diabetic retinopathy diagnosis, reducing reliance on manual screening.

• Developed iris image segmentation techniques to explore iridology-based biomarkers as an alternative diagnostic pathway.

• Projected impact: reduce doctor diagnosis time by ~20% and expand early detection access to 20M+ people worldwide.

• Mentored and supervised an undergraduate researcher, defining tasks and providing feedback on a retinal image processing pipeline to filter out low-quality medical images.

Working with 20 teaching staff to plan logistics, prepare lesson plans, lecture, offer student office hours and grade assignments for a class attended >300 students.