Research Program and Theme
Cancer Technology and Data Science | Computational Engineering and Data Science
Research Focus
Mohammed El-Kebir has worked on various cancer research topics, including tumor phylogenetics in the context of intra-tumor heterogeneity. El-Kebir develops algorithms to study the progression of a tumor from its initial stage, where the healthy cell first mutates, to the final stages, where the tumor cells metastasize and invade and colonize distant organs and tissues. His lab develops algorithms to reconstruct patterns of spread in disease outbreaks. One algorithm, called MACHINA, tracks the spread of cancer cells. He has also worked on a project under Jian Peng to predict response to cancer immunotherapy using a subclone-integrated machine learning model of neoantigen processing, presentation, and recognition.
Education
- Ph.D., Computer Science, VU University Amsterdam, 2015
Campus Affiliations
- Associate Professor, Siebel School of Computing and Data Science
- Associate Professor, Electrical and Computer Engineering
- Affiliate, Carl R. Woese Institute for Genomic Biology
- Affiliate, National Center for Supercomputing Applications (NCSA)
Select Honors and Recognitions
- NSF CAREER Award, 2021