Computational models are essential tools that can be used to simultaneously explain and guide biological intuition. My lab employs agent-based modeling, machine learning, and dynamical systems to explain biological observations and to uncover design principles that drive individual cellular decisions as well as cell population dynamics. We are interested in the inherent multiscale nature of biology, with a specific focus on system-level dynamics that emerge from interactions of simpler individual-level modules.

As educators, we expand the reach of our classrooms when we create inclusive and welcoming environments that invite students to apply their learning in novel ways. Our evidence-based teaching strategies allow students to scaffold their learning and see deep connections between different organizational levels and subfields of biology. Not only do we strive to create meaningful learning experiences within the classroom, but our scholarship and service shape our students’ broader educational experiences.

Increasing opportunities for undergraduate students to practice research, particularly underrepresented student populations in STEM, improves the recruitment and retention of these students because they are exposed to an authentic research environment in their required courses and learn valuable skills necessary for success in their discipline. Community colleges are an excellent venue for providing more inclusive access to research experiences because underrepresented minorities (URMs) account for almost half of all undergraduates attending community colleges.

An organism’s appearance is the result of evolutionary pressures, and those same pressures apply to the structures organisms build, such as nests. Superorganism nests function as extended phenotypes to perform key biological processes, to survive, grow, and reproduce. Social insects are masters of solving organizational problems because they must coordinate thousands of individuals to accomplish these goals. One such problem is how to construct nests, and then, how to organize resources within that nest. Both, presumably, are optimized to maximize colony performance.