NCHOFON TAGHA GHOGOMU

Profile

Nchofon Tagha Ghogomu

Earned a Master of Science in Information Technology, Applied Machine Learning concentration, from the College of Engineering of Carnegie Mellon University in May 2026. I contribute to the Wood Neuro Research Group, where I study cognition in patients with sickle cell disease using neuro-physiological signals and machine learning.

Previously, as Research Assistant at CMU AI Healthcare Research Laboratory, I developed explainable arrhythmia classification models and advanced reaserch on rheumatic heart disease detection. Given its growing application in healthcare, my curiosity extends to computational materials science. I hold a Master of Engineering in Industrial Robotics from École Nationale Supérieure Polytechnique de Douala. Find attached my curriculum vitae to find out more.

Neuroscience · AI/ML Research · Cognition · Digital Transformation

News Click a date to read more. (show all)

05/2026 Graduated from Carnegie Mellon University!
03/2026 Oral presentation at IEEE/CVF WACV 2026 in Tucson, Arizona.
01/2026 Joined the Wood Neuro Research Group at Carnegie Mellon University.
08/2025 Attended and served as judge at the Deep Learning Indaba Conference in Kigali, Rwanda.
07/2025 Attended the Digital Humanism Summer School at Carnegie Mellon University Africa.
06/2025 Attended the 2025 Afritech Network's Annual Conference in Kigali, Rwanda.
06/2025 Paper accepted for presentation at the European Public Health Conference 2025, Helsinki, Finland.
04/2025 Round table discussion with Trevor Mundel, president of Global Health at the Gates Foundation.
04/2025 Met Emmanuel Lubanzadio, Lead for OpenAI in Africa.
02/2025 Joined Carnegie Mellon University AI and Healthcare Research Lab.
02/2025 One-on-one with Prof. Mary-Anne Annie Hartley of LiGHT Laboratory on AI models and tools for resource-constrained communities.

Publications Click a venue to read more. (show all)

arXiv '26 Zero-Shot Neural Priors for Generalizable Cross-Subject and Cross-Task EEG Decoding
WACV '26 Bridging the Trust Gap: Interpretable AI for Clinical Decision Support in Arrhythmia Diagnostics
EPH '25 Evaluating Health Facility Distribution and District-Level Disease Prevalence in Rwanda: A Data-driven Approach
CMPBU '25 Machine Learning-Based Analysis of ECG and PCG Signals for Rheumatic Heart Disease Detection: A Scoping Review (2015--2025)

Academic Research

Advancing Digital Twins for Urban Mobility in Sub-Saharan Africa: Feature-Based Road Classification (2025). Conducted computer vision research at CMU-Africa, developing a deep learning model for real-time road feature classification in Kigali to support digital twins for Sub-Saharan African cities. Instructor: Prof. João Barros. Final Report.

Prolonged Post-stroke Recovery Rates in Sub-Saharan Africa: AI for Enhanced Post-Stroke Recovery (2025). Team project on AI for post-stroke monitoring in resource-constrained settings. Instructor: Prof. Edith Luhanga. Team: Nchofon Tagha G., Brandone Fonya, Miracle James, Peng Boris, Abel Jotie. Report available on request.

Design and Prototyping of a Medical Device for Automatic Health Data Collection, Storage and Management — The Health Pad (MEng Thesis, 2022). Engineered a medical tablet with five embedded clinical sensors for real-time data acquisition and storage. Academic Supervisor: Dr. EKE Samuel. Final report.

Industrial Exposure

Affiliations

Research affiliations and collaborating labs.

Wood Neuro Research Group AI Healthcare Research Laboratory

✉ ntaghagh [at] andrew [dot] cmu [dot] edu Last updated: 2026-08-21
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