Building Foundational Models for the brain

• Led the development of an Explainable AI (xAI) library focused on explaining internal ML models

for disease detection, and integrating it with CI/CD pipelines.

• Designed LLM solutions utilizing OpenAI GPT models, offering UIs for plain language queries on

nested data structures and RAG-based functionalities for in-house documentation querying.

• Co-led Disease Detection project for client deploying a prediction model forecasting future patients.

• Collaborated with the Caltech LHC group, actively contributing to the machine-learning division focused on particle-flow within the Compact Muon Solenoid (CMS).

• Developed a deep-learning model for particle classification and momentum regression within the detector.

• Utilized archival data to calibrate the code and built a predictive model with a 97% accuracy rate for determining the flavor of particles in the detector.

• Collaborated within a team of transport modelers to create highway transport models for surface

access to Heathrow airport.

• Gained proficiency in using SATURN software and implemented network changes following the calibration and validation of existing models.

• Contributed to the development of Base Matrix for traffic forecasting up to 2050.

• Worked as a math tutor at a student run peer support scheme for pre-honours students.

• Enhanced communication skills by presenting solutions to sample problems to a group of fifteen students and helped them develop problem solving skills.