Suely Oliveira, Ph.D.


Research Interests

My research is interdisciplinary, I focus on the computational and theoretical aspects of algorithms in Scientific Computing and Machine Learning for Engineering, Biology (Genetics) and Medicine. My projects have included clustering algorithms for protein-protein networks, neural networks for antibiotic resistance, and interpretable neural networks for test assessments. In these areas the use of machine learning, optimization and high-performance computing is essential. I have co-authored over 80 refereed papers on these topics and also two books: Building Proofs: A Practical Guide, World Scientific and Writing Scientific Software, Cambridge University Press. A more comprehensive list of publications, including collaborators and former PhD students can be found on my personal web page. As a sample, below are 14 selected published papers. For more complete information, see my personal web-page: (

Research Interests (Keywords)

Machine Learning, Scientific Computing, Optimization, High Performance Computing, Clustering Algorithms, Neural Networks, Genetics, Data Science

Selected publications

Research areas
  • Algorithmic Foundations
  • Health- and Human-Centric Computing
  • Verifiable, Dependable, and High-Performance Systems
Suely Oliveira
Contact Information

101H MacLean Hall (MLH)
Iowa City, IA 52242
United States