Shibu Yooseph

Dr. Shibu Yooseph is a Professor in the Department of Computer Science at the University of Central Florida. He is also the Cluster Lead for the Genomics and Bioinformatics Faculty Research Cluster. He has a Secondary Joint Appointment in the Burnett School of Biomedical Sciences. Dr. Yooseph’s primary research is in Computational Biology and Bioinformatics, with a focus on the design and development of efficient algorithms for large-scale biological data analysis. His research is interdisciplinary, involving applications and collaborations in the fields of computing, genomics, microbiology, environmental research and biomedical sciences. (Brief Bio)

Research areas:

• Algorithm design and combinatorial optimization
• Machine Learning
• Genomics, Computational Biology, and Bioinformatics
  • Metagenomics
  • Sequence Assembly
  • Homology Detection
  • Phylogenetics
  • Biomarker Discovery
  • Clustering and Ordination
  • Functional Genomics
• Microbiome Research
  • Integration and analysis of microbiome ‘-omics’ data
  • Microbial diversity and ecology in different environments including air, water, and human
  • Prediction of microbial associations/interactions
  • Host-microbiome associations and mechanisms in the context of health and disease

Google Scholar link to publications.

Teaching:

• (Undergraduate CS course) COT3100H Honors Introduction to Discrete Structures: Topics covered include Logic, Sets, Functions, Relations, Boolean Algebras, Mathematical Induction, Recursion, Counting, Probability, Algorithms and Computational Complexity.
• (Graduate CS course) COT6417 Algorithms on Strings and Sequences: Topics covered include Pattern Matching Algorithms, Data Structures and Indexing (Keyword Trees, Suffix Trees, Suffix Arrays, Burrows-Wheeler Transform, Wavelet Trees, Compressed Suffix Arrays, FM-index), Biological Sequence Alignment Algorithms and Homology Detection, and Speeding up Searching and Clustering (Filtering and Locality-Sensitive Hashing).

We have recently developed a Minor Program in Genomics and Bioinformatics. More information can be found here.