S. Cenk Sahinalp

Photo of S. Cenk Sahinalp
Graduation Year:
Locally consistent parsing for string processing

S. Cenk Sahinalp received his Ph.D. from University of Maryland in 1997 under the supervision of Prof. Uzi Vishkin. His thesis was on development and theoretical analysis of string/sequence algorithms. After a brief postdoctoral fellowship in Bell Labs, Murray Hill, Sahinalp worked as a computer science professor until 2019, when he moved to the newly founded Cancer Data Science Laboratory in the National Cancer Institute, Bethesda, MD, as a Senior Investigator.

Sahinalp’s research is focused on developing algorithmic methods for analysis and interpretation of molecular sequence data, primarily from tumor samples. Some of these algorithmic methods have been used by leading consortia to investigate the evolution and the genomic heterogeneity of cancers. He has also developed many algorithmic methods and data structures for the resolution of the repetitive regions of the human genome, especially those harboring genes involved in the drug metabolism, or the innate and adaptive immune system. Sahinalp has also developed algorithms for pattern matching, data compression, metric embeddings of string spaces, and privacy preserving genome sequence analysis.

Sahinalp has (co)-advised more than 30 Ph.D. students and postdocs. His past trainees have won numerous awards and accolades; many of them hold faculty and research positions in some of the leading institutions around the world.

Cenk was the general chair of RECOMB 2011, and the PC chair of RECOMB 2017. He has also founded SSACB, NCI Spring School on Algorithmic Cancer Biology, RECOMB-Seq, the RECOMB Satellite Meeting on Sequencing, and has been serving on the steering committee of RECOMB.

Cenk was named a University of Maryland Computer Science Department Distinguished Alumnus in 2012.