Quinnipiac University
James Soda, Jr., Ph.D.

Assistant Professor of Math and Data Science

Professor Soda is an Assistant Professor of Mathematics and Data Science. His teaching interests include probability and statistics, computational mathematics, and scientific programming. He also contributes to the curriculum design for Quinnipiac’s Data Science Program. As an instructor, Prof. Soda seeks to impart the knowledge and academic skills necessary for students to succeed in their professional and intellectual endeavors, not just while they are students but throughout their careers.

Professor Soda’s research interests center on data science applications to ecology, evolution, and medicine. His recent work has focused on disease modeling and geometric morphometrics, the statistical study of biological shape variation. In addition, he is the current moderator for the popular Morphmet listserv, which functions as an international forum for researchers to discuss work related to geometric morphometrics.

Professor Soda earned a B.S. in Biology from Western Washington University in 2009 and a M.A. in Biology from Stony Brook University in 2011. Starting in 2011, his academic interests shifted towards data science, leading him to earn a M.S. and Ph.D. in Computational Science from Florida State University. Between 2017 and 2019, he worked as a Post-Doctoral Researcher at the University of Notre Dame, until accepting his current position at Quinnipiac.


  • BS, Western Washington University
  • MA, SUNY Stony Brook
  • MS, Florida State University
  • PHD, Florida State University

Areas of Expertise

  • Data Science
  • Geometric Morphometrics
  • Disease Modeling


  • Mathematics and Statistics

Office Location

  • College of Arts & Sciences 3 105

Mail Drop

  • CL-AC3


Quinnipiac University

Assistant Professor of Mathematics and Data Science

Hamden, CT, USA

2019 - Present

University of Notre Dame

Post-Doctoral Researcher

Notre Dame, IN, USA

2017 - 2019

Selected Publications

Peer Reviewed Journal

Expected endpoints from future chikungunya vaccine trial sites informed by serological data and modeling

Tran, Q.M., Soda, J., Siraj, A., Moore, S., Clapham, H., Perkins, T.A.

41(1) Vaccine 182-192 Jan (2023)

Peer Reviewed Journal

Monitoring and responding to emerging infectious diseases in a university setting: A case study using COVID-19

Soda, K.J., X Chen X, R Feinn, Hill, D.R.

18(5) PLoS ONE e0280979 May (2023)

Invited Speaker

Agent-based modeling to inform public health policy at institutions of higher education: A case study using COVID-19

Soda, K.J.

Mathematical Biology Seminar, Lincoln, Nebraska, University of Nebraska-Lincoln (2022)


Population biology of vector-borne diseases

Perkins T.A., Espana, G., Moore, S.M., Oidtman, R.J., Sharma, S., Singh, B., Siraj, A.S., Soda, K.J., Smith, M., Walters, M.K., and Michael, E.

Seven challenges for spatial analyses of vector-borne diseases 29-44 Oxford (Oxford University Press 2021)

Peer Reviewed Poster

Dynamic factor analysis as a dimension reduction technique for shape trajectory data

Soda, K. J.

89th Annual Meeting of the American Association of Physical Anthropologists, Cancelled, but abstract was published, American Association of Physical Anthropologists (2020)

Peer Reviewed Journal

Leveraging multiple data types to estimate the size of the Zika epidemic in the Americas

Moore, S.M., Oidtman, R.J., Soda, K.J., Siraj, A.S., Reiner Jr, R.C., Barker, C.M., and Perkins, T. A.

14(9) PLoS Neglected Tropical Diseases e0008640 Sept. 28 (2020)