Kara Maki Headshot

Kara Maki

Associate Professor

School of Mathematical Sciences
College of Science

585-475-2541
Office Hours
Mondays, 2-3 PM, Zoom; Tuesdays, 3-4 PM, Gosnell 2348; Wednesdays, 2-3 PM, Zoom; Thursdays, 3-4 PM, Gosnell 2348
Office Location

Kara Maki

Associate Professor

School of Mathematical Sciences
College of Science

Education

BS, University of New Hampshire; MS, Ph.D., University of Delaware

585-475-2541

Personal Links
Areas of Expertise

Select Scholarship

Journal Paper
Wong, Tony E., et al. "Evaluating the sensitivity of SARS-CoV-2 infection rates on college campuses to wastewater surveillance." Infectious Disease Modeling 6. (2021): 1144-1158. Print.
Maki, Kara L., Richard J. Braun, and Gregory A. Barron. "The Influence of a Lipid Reservoir on the Tear Film Formation." Mathematical Medicine and Biology: A Journal of the IMA 37. (2020): 363-388. Print.
Burkhart, Collin T., Michael J. Schertzer, and Kara L. Maki. "Coplanar Electrowetting-induced Droplet De-tachment from Radially Symmetric Electrodes." Langmuir 36. (2020): 8129-8136. Print.
Bernetski, Kimberly A, Kara L Maki, and Michael J Schertzer. "Comment on “How to make sticky surfaces slippery: Contact angle hysteresis in electrowetting with alternating voltage”." Appl. Phys. Lett. 114. (2019): 116101. Print.
Li, Longfei, et al. "Tear Film Dynamics with Evaporation, Wetting, and Time-dependent Flux Boundary Condition on an Eye-shaped Domain." Physics of Fluids 26. 5 (2014): 52101. Print.
Maki, Kara L. and David S. Ross. "Exchange of Tears under a Contact Lens Is Driven by Distortions of the Contact Lens." Integrative and Comparative Biology 54. 6 (2014): 1043-1050. Print.
Lee, S. H., et al. "Gravity-driven Instability of a Thin Liquid Film Underneath a Soft Solid." Physical Review E 90. 5 (2014): 53009. Print.
Huang, J., et al. "Phantom Study of Tear Film Dynamics with Optical Coherence Tomography and Maximum-likelihood Estimation." Optics Letters 38. (2013): 1721-1723. Print.
Huang, J., et al. "Maximum-likelihood Estimation in Optical Coherence Tomography in the Context of the Tear." Biomedical Optics Express 4. (2013): 1806-1816. Print.
Maki, Kara L. and Yuriko Renardy. "The Dynamics of a Viscoelastic Liquid which Displays Thixotropic Yield Stress Behavior." Journal of Non-Newtonian Fluid Mechanics 181. (2012): 30-50. Print.
Maki, Kara L. and Satish Kumar. "Fast Evaporation of Spreading Droplets of Colloidal Suspensions." Langmuir 27. (2011): 11347-11363. Print.
Invited Paper
Reed, Kenneth, et al. "Modeling the Kinetic Behavior of Reactive Oxygen Species with Cerium Dioxide Nanoparticles." Biomolecules. (2019). Web.
Maki, Kara L. and David S. Ross. "A New Model for the Suction Pressure Under A Contact Lens." Journal of Biological Systems. (2014). Print.
Invited Article/Publication
Maki, Kara L, et al. "A model for tear film dynamics during a realistic blink." Journal for Modeling in Ophthalmology. (2019). Web.
Maki, Kara L., Rodolfo Repetto, and Richard J. Braun. "Mathematical modeling highlights from ARVO 2018." Journal for Modeling in Ophthalmology. (2019). Web.

Currently Teaching

ITDS-150
3 Credits
This course serves two purposes. One is to introduce students to metacognition, reflective practice and self-assessment. Students will explore how the continual assessment of one's own knowledge guides scientific progress in the development of both research and theoretical practice. The second is to apply metacognitive techniques to exploring scientific investigation from a combination of scientific, ethical and societal standpoints. Examples will be drawn from student interest, and may include topics such as: Chernobyl and Fukushima nuclear disasters, genetically modified organisms, indoor air quality, invasive species, forensic science. Metacognitive issues such as learning theory, stereotype threat and self-assessment will be explored for their role in the acquisition of scientific knowledge.
MATH-181
4 Credits
This is the first in a two-course sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals.
MATH-500
3 Credits
This capstone experience introduces students to mathematical problems and situations not encountered in previous courses of study. The class will primarily revolve around student-directed,collaborative efforts to solve a given problem using rigorous mathematical analysis and (as appropriate) computational methods. Significant work outside the classroom will be required of students. Students will write a formal report of their solution methods, and produce a poster for presentation at an end-of-term conference-style event.
MATH-606
1 Credits
The course prepares students to engage in activities necessary for independent mathematical research and introduces students to a broad range of active interdisciplinary programs related to applied mathematics.
MATH-622
3 Credits
This course will introduce graduate students to the logical methodology of mathematical modeling. They will learn how to use an application field problem as a standard for defining equations that can be used to solve that problem, how to establish a nested hierarchy of models for an application field problem in order to clarify the problem’s context and facilitate its solution. Students will also learn how mathematical theory, closed-form solutions for special cases, and computational methods should be integrated into the modeling process in order to provide insight into application fields and solutions to particular problems. Students will study principles of model verification and validation, parameter identification and parameter sensitivity and their roles in mathematical modeling. In addition, students will be introduced to particular mathematical models of various types: stochastic models, PDE models, dynamical system models, graph-theoretic models, algebraic models, and perhaps other types of models. They will use these models to exemplify the broad principles and methods that they will learn in this course, and they will use these models to build up a stock of models that they can call upon as examples of good modeling practice.
MATH-722
3 Credits
This course will continue to expose students to the logical methodology of mathematical modeling. It will also provide them with numerous examples of mathematical models from various fields.
MATH-790
0 - 9 Credits
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.

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