Suleyman is a computational genomics and research-computing specialist in the Bioinformatics Division of IIHG, bridging genomic data analysis with the HPC infrastructure that supports it. He earned his Ph.D. from Emory University, where his research focused on the biophysics of transcription. He then moved to Columbia University's Department of Biological Sciences, where he worked with colleagues from the Clinical Genetics program on CRISPR-based gene-editing therapeutics for sickle cell anemia; the project was awarded funding through Columbia's Translational Therapeutics Accelerator program.

At IIHG, Suleyman designs and maintains reproducible sequencing workflows for bulk and single-cell RNA-seq, methylation profiling, and differential expression analysis, using Nextflow, nf-core, and R-based statistical pipelines including DESeq2 and Seurat. He also optimizes the SGE-based HPC environment and provisions GPU workloads, managing shared storage, and handling data staging in order to keep high-throughput genomic pipelines running reliably.

Suleyman works directly with investigators to turn complex sequencing data into clear, decision-ready results, from analytical reports to manuscript-ready figures. He's especially interested in workflow automation, machine learning interpretability in genomics, and building better tools for scientific communication and visualization across research teams.