University of Houston - Mathematics
Mathematics Professor at HCC
Research
Sergey
Sarkisov
Houston, Texas Area
Having attained my Ph.D. in mathematics from the University of Houston, I now teach math at the collegiate level. I have over 19 years of experience training young minds to think and to enjoy the learning process. Having recited and taught mathematics as a graduate student for 6+ years, I have found that teaching is my most highlighted attribute. Alongside higher education, I have 2+ years of managing, teaching, and evaluating younger students in preparation for the National Olympiads. Overall, my strongest teaching topics are: Calculus I/II, Geometry, Trigonometry, Algebra, Probability, Statistics, Number Theory, Linear Algebra, ODE’s, and Complex Analysis.
In the research spectrum, my areas of expertise are statistics, probability, stochastic processes, genetic evolution, mutations, modeling, mathematical biology, data analysis, simulation, time series, estimation theory, optimization, data science, and algorithm development. I have been working on my doctoral studies and afterwards with Profs. Robert Azencott, Tim Cooper, Ilya Timofeyev, Ricardo Azevedo, et al. (See below the publication of 2018 (in progress) for brief research description.)
TA
Teaching Calculus.
Research Assistant
Stochastic modelling and parametric estimation of large-deviation mutation growth models. Also, finding algorithms for the visual/automatic detection of mutation occurrence times.
Advisor - Dr. Robert G. Azencott
Research Assistant
sssoptical.com
Instructor
Organized the academy in Huntsville, AL and taught olympiad-level math classes to talented middle school and high school students.
Professor Of Mathematics
Sergey worked at Houston Community College as a Professor Of Mathematics
Mathematics Instructor
Sergey worked at Momentum Learning as a Mathematics Instructor
Master's Degree
Mathematics
Masters of Science in Mathematics and continuing PhD pursuits.
Doctor of Philosophy (Ph.D.)
Mathematics
TA
Teaching Calculus.
Research Assistant
Stochastic modelling and parametric estimation of large-deviation mutation growth models. Also, finding algorithms for the visual/automatic detection of mutation occurrence times.
Advisor - Dr. Robert G. Azencott
Took classes in Math PhD program
SPIE
SPIE
Journal of Applied Physics
SPIE
Journal of Applied Physics
Optics Express
SPIE
Journal of Applied Physics
Optics Express
Theoretical Population Biology
This contains an overview of the results attained while working on my dissertation regarding parameter estimation for bacterial populations and the statistical analysis of the algorithm discovered and used. I can now give accurate predictions on how many types of mutants there are, how strong these mutants are, and how likely they are to occur on a particular day. This work can be extended from bacterial populations to more complex life or other probabilistic/stochastic models such as quantitative trends, etc.
SPIE
Journal of Applied Physics
Optics Express
Theoretical Population Biology
This contains an overview of the results attained while working on my dissertation regarding parameter estimation for bacterial populations and the statistical analysis of the algorithm discovered and used. I can now give accurate predictions on how many types of mutants there are, how strong these mutants are, and how likely they are to occur on a particular day. This work can be extended from bacterial populations to more complex life or other probabilistic/stochastic models such as quantitative trends, etc.
Applied Physics Letters
SPIE
Journal of Applied Physics
Optics Express
Theoretical Population Biology
This contains an overview of the results attained while working on my dissertation regarding parameter estimation for bacterial populations and the statistical analysis of the algorithm discovered and used. I can now give accurate predictions on how many types of mutants there are, how strong these mutants are, and how likely they are to occur on a particular day. This work can be extended from bacterial populations to more complex life or other probabilistic/stochastic models such as quantitative trends, etc.
Applied Physics Letters
SPIE
SPIE
Journal of Applied Physics
Optics Express
Theoretical Population Biology
This contains an overview of the results attained while working on my dissertation regarding parameter estimation for bacterial populations and the statistical analysis of the algorithm discovered and used. I can now give accurate predictions on how many types of mutants there are, how strong these mutants are, and how likely they are to occur on a particular day. This work can be extended from bacterial populations to more complex life or other probabilistic/stochastic models such as quantitative trends, etc.
Applied Physics Letters
SPIE
SPIE