Keivin Isufaj is a Research Assistant at QCRI, focusing on Machine Learning, Traffic Data Analytics, and Bioinformatics. He holds a Computer Science degree with a Minor in Mathematical Sciences from Carnegie Mellon University. Keivin's experience includes managing and developing frameworks and systems in diverse projects. He has contributed to areas such as traffic trajectory imputation, data visualization, and oral lesion detection. Additionally, Keivin has applied Machine Learning and AI to metabolomic and genomic data to model and predict Coronary Heart Disease and Type 2 Diabetes in Middle Eastern cohorts.
QCRI, HBKU
2021 - PresentCarnegie Mellon University
2021