Derek Cole Aguiar

Derek Cole Aguiar serves as an Assistant Professor in the Computer Science and Engineering Department at the University of Connecticut's School of Engineering. His academic journey includes B.S. degrees in Computer Engineering and Computer Science from the University of Rhode Island, a Ph.D. in Computer Science from Brown University under Professor Sorin Istrail, and postdoctoral research at Princeton University with Professor Barbara Engelhardt.

• University of Rhode Island: B.S. Computer Engineering & Computer Science
• Brown University: Ph.D. Computer Science
• Princeton University: Postdoctoral Research

Dr. Aguiar's research focuses on developing probabilistic machine learning models and combinatorial algorithms for analyzing high-dimensional genomic data, with applications to complex diseases. His work bridges theoretical computer science with practical biological applications, particularly in genomics, transcriptomics, population genetics, and immunology. He develops foundational methods for haplotype assembly, isoform discovery, variant calling, and cis-regulatory element analysis.

Analysis of his publication record reveals a consistent trajectory in computational genomics, beginning with haplotype assembly algorithms and expanding into RNA-seq analysis, variant detection, and regulatory genomics. His work demonstrates a progression from algorithmic development to increasingly sophisticated probabilistic modeling approaches applied to complex biological problems. The tools he develops (HapCompass, BIISQ, Tractatus, DELISHUS, CYRENE) have become established methods in their respective subfields.

Dr. Aguiar actively seeks motivated PhD students interested in foundational research at the intersection of statistics, probabilistic machine learning, and algorithms applied to genomics and related fields. His teaching portfolio includes advanced courses in Bayesian Machine Learning (CSE5825) and Algorithms & Complexity (CSE3500), where he emphasizes the three fundamental components of probabilistic modeling: model specification, inference algorithms, and model checking.

His laboratory develops several widely-used bioinformatics tools including HapCompass for haplotype assembly, BIISQ for isoform discovery, Tractatus for identity-by-descent analysis, DELISHUS for variant calling, and CYRENE for cis-regulatory element visualization. These tools represent significant contributions to the computational genomics community and demonstrate his lab's focus on developing practical, scalable solutions to challenging biological problems.