معرفی
Uri Keich is an Associate Professor at the School of Mathematics and Statistics, University of Sydney. His research bridges Bioinformatics, Computational Statistics, and Proteomics, with a focus on statistical methods for tandem mass spectrometry analysis, DNA replication origin mapping, and motif finding significance. He collaborates extensively with biologists and computational researchers.
- Education: PhD in Mathematics (Courant Institute, NYU), MSc in Mathematics (Technion, Israel), BSc in Computer Science and Mathematics (Hebrew University).
- Professional Experience: 2009–present at University of Sydney; 2003–2009 at Cornell University; prior roles at UCSD, UCR, Caltech, and NYU.
Research Interests
Keich's work centers on false discovery rate (FDR) control in high-throughput biological data, particularly for peptide identification and motif analysis. He develops exact statistical tests using large-deviation theory and FFT-based algorithms, with applications to proteomics and genomic sequence analysis. His research also explores DNA replication origins in yeast through collaborations.
Scientific Awards
- Best Paper Award, RECOMB 2015 for A Symmetric Length-Aware Enrichment Test.
Teaching and Supervision
Teaches advanced courses in Probability and Statistics (e.g., STAT 2911, MATH1905) and specialized topics like convolution and FFT. Supervises PhD students in computational statistics and bioinformatics.
