Math Modeling Seminar - Statistical and Stochastic Contributions to Math Modeling
Harnessing the Blessings of the Statistical and Stochastic Contributions to Mathematical Modelling
Dr. Ernest Fokoué
Professor
School of Mathematical Sciences, RIT
Abstract:
The quintessential motivation of this talk is to share with my audience what I perceive as a rich and vast array of paradigms or at least methods, concepts and techniques that inherently reside at the interface of deterministic and non-deterministic Mathematical modelling, and that providentially constitute a potent field for the creation and development of far superior and more useful and impactful mathematical models. Borrowing from themes like Gaussian Processes in Statistical Machine Learning, nonhomogeneous Poisson processes in reliability analysis to Bayesian estimation and inference for a wide class of models based on differential equations just to name a few, I intend to kindle the awareness of my audience on the inextricable links among various sub-paradigms of mathematical modelling often mistakenly treated as non-overlapping. A latent (secondary) intention of my talk lies in my hope to contribute to the healing or at least the bridging of the schism or chasm that I perceive among branches of mathematical modelling, hopefully substituting divisiveness with the more noble spirit of collaborative exploration that naturally contains the seed for a technically and methodologically more diverse and more inclusive, and topically far richer mathematical modelling experience for both faculty and their students. Throughout this talk, I will endeavor to focus on the intuitive appeal of the concepts and ideas, but I will occasionally make use of technical details and derivations wherever needed and will definitely make a lot of epistemological allusions!
Speaker Bio:
Dr. Ernest Fokoué is a Professor of Statistics with the School of Mathematical Sciences in the College of Science at Rochester Institute of Technology. His areas of research interest include Theoretical Statistics, Statistical Methodology, Bayesian Statistics, Statistical Learning Theory, Data Science, Statistical Machine Learning, Computational Statistics and Statistical Computing. Despite being a bold and zealous statistical evangelist and apologist, he is a mathematical universalist who naturally sees and joyfully embraces the beautiful interconnectedness of all the branches and members of the mystical body of mathematics, forever aware of their undivided and indivisible unity. Epistemology also occupies a place of choice in his array of scholarly interests, along with linguistics and mysticism. He is the current President of the Rochester Chapter of the American Statistical Association and the Founder of the Data Science Research Group.
Intended Audience:
Undergraduates, graduates, and experts. Those with interest in the topic.
The Math Modeling Seminar will recur each week throughout the semester on the same day and time. Find out more about upcoming speakers on the Mathematical Modeling Seminar Series webpage.
Event Snapshot
When and Where
Who
Open to the Public
Interpreter Requested?
No