2021-2022 Florida Tech Catalog [ARCHIVED CATALOG]
Department of Mathematical Sciences
Gnana Bhaskar Tenali, Ph.D., Head
Ugur G. Abdulla, Ph.D., partial differential equations, potential theory, nonlinear partial differential equations, optimal control and inverse problems, free boundary problems, quantum biology, mathematical biosciences, dynamical systems and ergodic theory.
Jewgeni H. Dshalalow, Dr. Sci., real analysis, stochastic analysis, mathematical finance, mathematical biology with applications to cell-molecular biology and cancer research, stochastic games, cybersecurity, queueing theory.
Kastro M. Hamed, Ph.D., STEM teaching and learning, physics education, teacher education, engineering education, mathematics education, financial education, learning sciences, student success, research methodologies.
Thomas J. Marcinkowski, Ph.D., science and environmental education, teaching and learning, classroom and large-scale assessment, research and evaluation design.
Kanishka Perera, Ph.D., nonlinear elliptic partial differential equations, variational problems, free boundary problems, critical point theory.
Gnana B. Tenali, Ph.D., functional differential equations, set differential equations.
Jian Du, Ph.D., mathematical biology and scientific computing.
Jim Jones, Ph.D., computational mathematics, parallel computing, numerical solution of PDEs.
Tariel I. Kiguradze, Ph.D., partial differential equations, ordinary differential equations, nonlinear boundary value problems, quantitative theory.
Jay J. Kovats, Ph.D., elliptic and parabolic partial differential equations.
Nezamoddin Nezamoddini-Kachoiue, Ph.D., statistical modeling, data science, machine learning, trend analysis, biostatistics, signal and image processing, pattern recognition, computer vision.
Michael D. Shaw, Ph.D., nonlinear differential equations, Lyapunov stability theory.
Munevver M. Subasi, Ph.D., operations research, optimization, stochastic programming, machine learning, data science, pattern recognition, mathematical biology, stochastic modeling, financial mathematics.
Vladislav Bukshtynov, Ph.D., numerical and computational optimization, control theory, inverse problems, high performance scientific computing, mathematical modeling.
William T. Girton, Ph.D., difference and differential equations.
Joo Young Park, Ph.D., mathematics education, mathematical modeling approach in undergraduate mathematics education, statistical literacy.
Stanley Snelson, Ph.D., partial differential equations, mathematical physics, kinetic theory, shape optimization, nonlinear waves.
Aaron Welters, Ph.D., mathematical physics, applied mathematics.
Ryan White, Ph.D., probability theory, stochastic analysis, deep learning, computer vision, machine learning, natural language processing.
Frederick B. Buoni, Ph.D.; Richard E. Enstice, Ph.D.; Robert H. Fronk, Ph.D., Charles T. Fulton, Ph.D.; Dennis E. Jackson, Ph.D.
Debra Blenis, M.S.; Semen Koksal, Ph.D.
The mission of the Department of Mathematical Sciences is to create and maintain a culture of excellence in teaching and research, with the goal of setting the stage for research based and innovative pedagogies that foster student engagement, learning, and success and that nurture the integration of ideas and open new avenues for interdisciplinary research to prepare the next generation of mathematicians and educators for tackling the pressing issues society faces both today and in the decades to come.
Minors in athletics coaching and computational mathematics are offered through the department. A complete policy statement regarding minors can be found under Undergraduate Academic Information . Information about current minor offerings is available through the individual colleges/departments.
Applied mathematics: Active research areas in applied mathematics include analysis of partial differential equations, functional differential equations, optimal control, mathematical biology, scientific computing, real and stochastic analysis, mathematical physics, optimization, inverse problems, dynamical systems and ergodic theory.
Educational Technology: Research activities in the diverse and ever-expanding area of educational technology also spans the K-16 spectrum, including educational applications of AV resources to enrich traditional instruction, social media and simulation technologies including Virtual Reality (VR) to enhance learning within targeted audiences, and evolving technologies and strategies for improving the effectiveness of remote/distance and online learning.
Environmental Education and Environmental Literacy Assessments: Funded by NOAA and EPA, and administered by NAAEE, the National Environmental Literacy Assessment (NELA) project was a 10-year, multi-phase research project to help determine how environmental education (EE) practices support the development of environmental literacy among middle-school students around the U.S. The NELA team supported national assessments (K-12) in South Korea, Israel, and Turkey, and later worked with members of each national team to summarize and compare results. After NELA, doctoral students at Florida Tech have developed instruments to assess environmental literacy among college students in Mainland China and high school students in Saudi Arabia. Other areas of research in environmental education include environmental sensitivity and significant life experiences.
Mathematics Education: Diverse research activities focus on issues related to the theory and practice of K-16 mathematics or statistics education. A distinctive feature of the mathematics education program is a strong emphasis on the role of mathematics content knowledge and mathematics application in STEM education. Research areas include but are not limited to teaching and learning of mathematical modeling, statistical literacy, project-based learning in mathematics at the undergraduate level, and the role of simulation technologies in teaching and learning mathematics.
Operations research: Active areas of research in operations research include stochastic analysis, optimization, computational optimization, stochastic programming, probability theory, statistical modeling, biostatistics, data science, machine learning, pattern recognition, computer vision, trend analysis, image and signal processing, natural language processing, game theory, mathematical biology, financial mathematics and their applications to medicine, engineering, science, and nontechnical disciplines.
Science education: Research activities in science education vary across all major science disciplines including aeronautics, biology, chemistry, computer science, environmental and earth science, physics and psychology. Students are encouraged to pursue research topics commensurate with their science background and teaching experience and represent the application of science to the K-16 education community. Examples include but are not limited to: scientific literacy; the nature of science and science inquiry; and socio-scientific issues.
ProgramsBachelor of ScienceNondegreeMaster of EducationMaster of ScienceSpecialist in EducationDoctor of Philosophy