Mathematical Biology Research Group at UC Merced
The mathematical biology group meets on a weekly basis to share and discuss current mathematical biology research in the Applied Mathematics Unit here at UC Merced. We use mathematical modeling and computational simulation to explore a variety of biological processes including, but not limited to, protein aggregation, population genetics & structural variation, and biofluid dynamics of marine
Our group is led by Professors Suzanne Sindi (ssindi<at>ucmerced.edu) and Shilpa Khatri (skhatri3<at>ucmerced.edu) and consists of graduate students, postdocs and faculty in the Applied Mathematics Unit and works in collaboration with several experimentalists at UC Merced and other institutions.
You can follow our activities at our Twitter Account


Group Meeting is Held on Wednesdays 3:304:30 in Willow Room (COB1322)
Fall 2017
August 23, 2017:
Organizational Meeting
August 30, 2017:
Paul Lemarre, Visiting Master's Student
Title: Mathematical Investigation Into Prion Strains Coexistence and Costability
September 6, 2017:
Michael Stobb, Applied Mathematics Phd Candidate
Title: Uncertaintity Quantification in Biochemical Systems
September 13, 2017:
Mario Banuelos, Applied Mathematics Phd Candidate
Title: Genomic Variant Detection Through Generations
September 20, 2017:
Suzanne S. Sindi, Assistant Professor
Title: Prion Dynamics in Dividing Yeast Populations
September 27, 2017:
Fabian Santiago, Applied Mathematics PhD Student
Title: Developing Mathematical Models to Cope with Antibiotic Resistance
October 4, 2017:
No Meeting
October 11, 2017:
Jason K. Dark, Postdoctoral Researcher at UC Irvine
Title: Stochastic Modeling of Protein Aggregation
October 18, 2017:
Matea Alvarado, Applied Mathematics PhD Student
October 25, 2017:
Shayna Bennett, Applied Mathematics PhD Student
November 1, 2017:
Shilpa Khatri, Assistant Professor
November 8, 2017:
Jordan Collignon, Applied Mathematics PhD Student
November 15, 2017:
Alex Quijano, Applied Mathematics PhD Student
Title: Mathematical Models of the Evolution of Intelligent Systems