Designing and implementing data collection/analysis tools to measure the impact of free medical outreach programmes in Lagos, Abuja, and Imo states.

Training volunteer teams to ensure effective tool adoption.

Supported experts from Harvard, Howard, and Johns Hopkins Universities in evaluating gaps in technologies and commercialization plans for various novel neurotechnologies from start-ups and academic teams.

Provided technical support and training to client teams in using the Guidance and Impact Tracking System (GAITS) Platform Portal for project tracking, reporting, and data analysis.

Developed and implemented a machine learning model architecture that improves speech intelligibility for deaf people who use cochlear implants in reverberant environments with PyTorch and MATLAB.

Co-authored 'The Omni-Expert: A Computationally Efficient Approach to Achieve a Mixture of Expertise in a Single Expert Model' [poster] published at the 2025 Conference on Neural Information Processing Systems (NeurIPS 2025), one of the top annual conference in the world for AI and machine learning along ICML.

Engineered and documented a pipeline to create a dataset of over 5 million tweets about COVID-19 with Python and Bash scripts.

Engineered and documented a pipeline to gather census data on essential workers distributions across various geographies in the United States using Python, Selenium web scraper, and Bash scripts on a SLURM scheduler.

Analysed how the attitude of social media users towards conventional scientific wisdom about COVID-19 affects how they interact with public health experts with Python, large language models, and NLP techniques.