Current Affiliation: University of California San Diego
Wednesday, January 16, 2019 @ 11:00am-12:30pm
Room 1242, CSE Building
Scalable methods for molecular epidemiology of rapidly-evolving pathogens
(CSE Colloquium Lecture Series)
The spread of many infectious diseases is driven by social and sexual networks, and reconstructing their transmission histories from molecular data may be able to enhance intervention. In the case of rapidly-evolving pathogens such as Human Immunodeficiency Virus (HIV), genomic mutations in samples collected from patients can provide evolutionary signal that can be used to infer patterns of transmission. With the rapid growth of pathogen sequencing, the ability to analyze ultra-large datasets in a scalable manner has become increasingly important. In this talk, I will present my efforts to model the components of an epidemic as stochastic processes, to efficiently sample from the probabilistic distributions defined by these models, and to infer properties of an epidemic from ultra-large molecular datasets. Next, I will discuss my teaching experiences and my scholarly contributions to Computer Science education. Lastly, I will describe my efforts to increase diversity in science and engineering, largely focusing on increasing accessibility to Computer Science and Bioinformatics education.
Niema Moshiri is a Ph.D. candidate in the Bioinformatics and Systems Biology program at UC San Diego, where he is co-advised by Siavash Mirarab in the Electrical and Computer Engineering Department and by Pavel Pevzner in the Computer Science and Engineering Department. He works on computational biology, and his research focuses on phylogenetics. His current research interests are primarily in modeling HIV transmission and evolution as well as in developing massively-scalable computational methods for HIV transmission history inference. In his teaching, Niema has developed multiple Massive Open Online Courses (MOOCs) in Bioinformatics and Data Structures. He has also authored a textbook, Design and Analysis of Data Structures, whose digital companion on the Stepik platform is frequently utilized in UC San Diego's CSE 100: Advanced Data Structures.
Faculty Host: George Porter