Bernard Brooks Headshot

Bernard Brooks

Professor

School of Mathematics and Statistics
College of Science
Associate Head, Applied and Computational Mathematics

585-475-5138
Office Hours
TW 12-12:50
Office Location

Bernard Brooks

Professor

School of Mathematics and Statistics
College of Science
Associate Head, Applied and Computational Mathematics

Education

BSc, University of Toronto (Canada); MBA, Rochester Institute of Technology; MSc, Ph.D., University of Guelph (Canada)

Bio

Bernard Brooks has been invited to present his rumor propagation research at numerous research institutions including the S.N.Bose National Centre For Basic Sciences in Calcutta, the Princeton Plasma Physics Laboratory, the Budapest University of Technology and Economics and the Institute for Advanced Studies in Vienna. He has been featured in the popular media as well on programs such as World Business on CNBC Europe and National Public Radio’s Science Friday: Using Math to Track Terrorists. 

Dr. Brooks won the Eisenhart Award for Outstanding Teaching in 2012.

585-475-5138

Areas of Expertise

Select Scholarship

Shows/Exhibits/Installations
Bastards, Sad. Fringe Festival. 18 Sep. 2018. Little Theatre Cafe, Rochester. Performance.
Journal Paper
Pudane, Mara, et al. "Agent Based Model of Anger Contagion and its Correlations with Personality and Interaction Frequency." International Journal of Education and Information Technologies 12. (2018): 7-12. Print.
Brooks, Bernard. "Linear Stability Conditions for a First Order 4-Dimensional Discrete Dynamic." J Appl Computational Math 3. 5 (2014): 174-177. Print.
Longo, David J. and Bernard Brooks. "Modeling the RIT Facebook Social Network." RIThink 3. (2013): 74-78. Web.
Brooks, Bernard, N. DiFonzo, and D. Ross. "GBN-Dialogue Model of Outgroup-Negative Rumor Transmission: Group Membership, Belief, and Novelty." Nonlinear Dynamics, Psychology and Life Sciences 17. 2 (2013): 269-293. Print.
Brooks, Radin, Wiandt, and Basener. "Spatial Effects and Turing Instabilities in the Invasive Species Model." , Nonlinear Dynamics, Psychology and Life Sciences 15. 4 (2011): 455-64. Print.
Invited Keynote/Presentation
Brooks, Bernard. "The Mathematics of Propagating a Rumour on a Social Network." Science & Technology Seminar Series of the Laboratory for Laser Energetics. University of Rochester. Rochester, NY. 31 Jan. 2014. Lecture.
Brooks, Bernard. "Modeling of the Human Colonization of Eastern Polynesia." NYCAM. Cornell. Ithaca, NY. 9 Nov. 2013. Conference Presentation.
Brooks, Bernard. "Mathematical Modeling Rumour Propagation on Social Networks." UIBE. University for International Business and Economics. Beijing, China. 30 Jul. 2013. Lecture.
Brooks, Bernard. "A Two-Population Competition Model for a Finite Natural Resource." Canadian Mathematical Society Winter Meeting. Canadian Mathematical Society. Montreal, PQ. 8 Dec. 2012. Conference Presentation.
Brooks, Bernard. "Predictive Emergency Response Modelling (PERM) via Agent-Based Models and Network Analysis." NYCAM. RPI. Troy, NY. 13 Oct. 2012. Conference Presentation.
Brooks, Bernard. "How Popular are You on Facebook?" U.S. Department of Energys National Science Bowl. U.S. Department of Energy. National Science Bowl, Washington, DC. 30 Apr. 2011. Keynote Speech.
Brooks, Bernard. "Rumour Propagation on Social Networks as a Function of Diversity." The Fifth International Workshop on Dynamics of Social and Economical Systems. DYSES. University of Sannio, Benevento, Italy. 23 Sep. 2010. Conference Presentation.
Formal Presentation
Brooks, Bernard. “Rumour Propagation on Social Networks as a Function of Diversity.” Fifth International Workshop on Dynamics of Social and Economical Systems. Benevento, Italy. 23 Sept. 2010. Presentation.
Brooks, Bernard. “Discrete Diffusion in Systems of 1st Order Difference Equations.” AMS Fall Eastern Sectional Meeting. Syracuse, NY. 2 Oct. 2010. Presentation.

Currently Teaching

ITDS-450H
1 Credits
This course uses a discussion format to help students wrestle with social and ethical issues associated with natural science, mathematics, or data science in the modern world. Students will be challenged to reflect on their own role and responsibility as citizens. It culminates in a written report or project presentation.
MATH-151H
3 Credits
The course will explore the structure of networks and how it relates to the behavior of the people in the networks. Students will develop an understanding, through experimentation and investigation, of how the net result of many apparently independent qualities, events, or ideas is influenced by the network structure. Common and familiar phenomena, such as social networks and food webs, can be modeled as networks. The course will introduce students to the subject of graph theory (the branch of mathematics that studies networks). Students will examine real networks through the viewpoint of a mathematician, gaining an understanding of many seemingly unrelated concepts. The honors seminar integrates the required YearOne curriculum.
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-182
4 Credits
This is the second in a two-course sequence. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates.
MATH-219
3 Credits
This course is principally a study of the calculus of functions of two or more variables, but also includes the study of vectors, vector-valued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, and includes applications in physics. Credit cannot be granted for both this course and MATH-221.
MATH-231
3 Credits
This course is an introduction to the study of ordinary differential equations and their applications. Topics include solutions to first order equations and linear second order equations, method of undetermined coefficients, variation of parameters, linear independence and the Wronskian, vibrating systems, and Laplace transforms.
MATH-241
3 Credits
This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course.
MATH-495
1 - 3 Credits
This course is a faculty-directed project that could be considered original in nature. The level of work is appropriate for students in their final two years of undergraduate study.
MATH-735
3 Credits
This is the first course in a sequence that examines mathematical and statistical models in finance. By taking a mathematical viewpoint the course provides students with a comprehensive understanding of the assumptions and limitations of the quantitative models used in finance. Topics include probability rules and distributions, the binomial and Black-Scholes models of derivative pricing, interest and present value, and ARCH and GARCH time series techniques. The course is mathematical in nature and assumes a background in calculus (including Taylor series), linear algebra and basic probability. Other mathematical concepts and numerical methods are introduced as needed.
MATH-736
3 Credits
This is the second course in a sequence that examines mathematical and statistical models in finance. By taking a mathematical viewpoint the course provides students with a comprehensive understanding of the assumptions and limitations of the quantitative models used in finance. Topics include delta hedging, introduction to Ito calculus, interest rate models and Monte Carlo simulations. The course is mathematical in nature and assumes a background in calculus (including Taylor series), linear algebra and basic probability. Other mathematical concepts and numerical methods are introduced as needed.
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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