Research

My research builds behavior-driven mathematical and computational models of collectives and individuals — interdisciplinary work that often involves an integrated approach between mathematics and the quantitative life sciences. I lead a research group that translates domain -specific questions into mechanistic models and then implements, simulates, and analyzes those models using the full toolbox of applied mathematics. Our computational work is primarily in Python with parallel processing, GPU acceleration, and compiled extensions where the problem demands it. Examples of my code are available on my GitHub page.

Current research themes include the collective dynamics of small organisms in complex fluid environments, the social and policy dynamics of disease and substance-use outbreaks in human populations, the formation and movement of locust hopper bands, and emerging work on the modeling of perception and decision-making in organisms. The fluid-flow work is anchored by Planktos, an open-source agent-based modeling framework I developed with collaborators in computational fluid dynamics; recent National Science Foundation funding supports its extension to dynamic structures and active filter feeders. The substance-use work, conducted with Oak Ridge National Laboratory and the U.S. Department of Veterans Affairs, has produced individual-based and compartmental models that inform intervention strategy at the community scale.

Earlier projects include the development of a mathematical and Bayesian framework for inferring stratified parasitoid wasp dispersal across agricultural fields — implemented as CUDA-powered Python software producing meter-scale resolution results across roughly twenty square kilometers — and a transparent model of savanna ecosystem dynamics showing how seasonal rainfall distribution and fire disturbance jointly determine stand structure through soil water dynamics. Both illustrate themes that continue to run through my work: mechanistic models grounded in the underlying science, careful numerical implementation, and applications at the interface of mathematics and the life sciences.

I currently advise two PhD students in the Strickland Lab and have graduated five doctoral students since 2020. Further detail on the lab, its current members, and ongoing projects is available at the Strickland Lab website.

LAB WEBSITE

Funding

National Science Foundation - DMS Math Bio. Collaborative Research: RUI: The fluid dynamics of organisms filtering particles at the mesoscale. PI, $170,164 (Multi-institutional total: $469,842), Sept. 2024 - Aug. 2027.

Oak Ridge National Lab (Prime Sponsor: US Dept. of Veterans Affairs). Quantifying Environmental Factors for Opioid Use Disorder. PI, $617,243 (UTK total: $804,062), Feb. 2023 - Dec. 2025.

Auburn University (Prime Sponsor: NSF). NSF INCLUDES Alliance: The Alliance of Students with Disabilities for Inclusion, Networking, and Transition Opportunities in STEM (TAPDINTO-STEM). Co-PI, $237,122, 2021-2026.

Simons Foundation. Collaboration Grant for Mathematicians. PI, $42,000, 2018-2023.

Burroughs Wellcome Fund. Enhancing Quantitative and Data Science Education for Graduate Students in Biomedical Science. Senior Personnel, $149,823, 2018-2020.

Workshop funding from AIMS (SQuaREs), NIMBioS, IAS, and AMS (MRC)

SELECTED PUBLICATIONS

Journal Publications

Bouka, Strickland (2025)

Strong information delay as a driver of epidemic waves: mathematical modeling for drug trends and epidemic bio-preparedness. Theoretical Population Biology, 167, 22-39.

Pearcy, Lenhart, Strickland (2024)

Structural instability and linear allocation control in generalized models of substance use disorder. Mathematical Biosciences, 371, 109169.

Elzinga, Strickland (2023)

Generalized stressors on hive and forager bee colonies. Bulletin of Mathematical Biology, 85(122).

Elzinga, Beckford, Strickland (2023)

A mathematical model of the impacts of climate change on the winter tick epizootic in moose. Ecological Modelling, 483, 110421.

Gross, McCord, LoRe, Ganusov, Hong, Strickland, Talmy, von Arnim, Wiggins (2023)

Prioritization of the concepts and skills in quantitative education for graduate students in biomedical science. PLOS ONE, 18, 1-12.

Strickland, Battista, Hamlet, Miller (2022)

Planktos: An agent-based modeling framework for small organism movement and dispersal in a fluid environment with immersed structures. Bulletin of Mathematical Biology, 84(72).

Phillips, Lenhart, Strickland (2021)

A data-driven mathematical model of the heroin and fentanyl epidemic in Tennessee. Bulletin of Mathematical Biology, 83(97).

Bernoff, Culshaw-Maurer, Everett, Hohn, Strickland, Weinburd (2020)

Agent-based and continuous models of hopper bands for the Australian plague locust: How resource consumption can mediate pulse formation and geometry. PLOS Computational Biology, 16(5), e1007820.

Battista, Pearcy, Strickland (2019)

Modeling the opioid epidemic. Bulletin of Mathematical Biology, 81(7), 2258-2289. This is a post-peer-review, pre-copyedit version of an article published in Bulletin of Mathematical Biology. The final authenticated version is available online at https://doi.org/10.1007/s11538-019-00605-0.

Battista, Strickland, Barrett, Miller (2018)

IB2d Reloaded: an updated Python and MATLAB implementation of the immersed boundary method. Mathematical Methods in the Applied Sciences, 41(18), 8455-8480.

Strickland, Kristensen, Miller (2017)

Inferring stratified parasitoid dispersal mechanisms and parameters from coarse data using mathematical and Bayesian methods, Royal Society Interface, 14, 20170005. This is a post-peer-review, pre-copyedit version of the article published in Royal Society Interface. The final version is available online at https://doi.org/10.1098/rsif.2017.0005.

Anonymous reviewer: "...the methodology is excellent, and the study serves as an exemplar of the use of Bayesian methods to estimate parameters in a mechanistic mathematical model and is applicable to modelling in any field, not just dispersal."

Anonymous reviewer: "I think the paper will be interesting and useful to a broad audience of scientists across an array of fields and fits perfectly with the aims and scope of Journal of Royal Society Interface."

Strickland, Miller, Santhanakrishnan, Hamlet, Battista, Pasour (2017)

Three-dimensional low Reynolds number flows near biological filtering and protective layers, Fluids, 2(62).

Battista, Strickland, Miller (2017)

IB2d: An easy to use immersed boundary method in 2D, with multiple options for fiber-structure models with possible porosity, advection-diffusion, and/or artificial forcing, Bioinspiration & Biomimetics, 12(3).

Strickland, Liedloff, Cook, Dangelmayr, Shipman (2016)

The role of fire and water in driving tree dynamics in Australian savannas, Journal of Ecology, 104(3), 828-840.

Strickland, Dangelmayr, Shipman, Kumar, Stohlgren (2015)

Network spread of invasive species and infectious diseases, Ecological Modelling, 309-310, 1-9.

Strickland, Dangelmayr, Shipman (2014)

Modeling the presence probability of invasive plant species with nonlocal dispersal, Journal of Mathematical Biology 69(2), 297-294

Shipman, Faria, Strickland (2013)

Towards a continuous population model for natural language vowel shift, Journal of Theoretical Biology, 332, 123, 135