Andras Balogh

Short Vita

Education

• Google / Advanced Data Analytics Professional Certificate, April 2024
• Google / Data Analytics Professional Certificate, February 2024
• Ph.D. in Mathematics, Texas Tech University, 1997.
• M.S. in Applied Mathematics, University of Texas at Dallas, 1994.
• B.S. in Mathematics, Jozsef Attila University of Szeged, Hungary, 1989.

Professional Experience

• Professor, School of Mathematical and Statistical Sciences, University of Texas Rio Grande Valley, 2015 - present.
• Professor, Department of Mathematics, University of Texas - Pan American, 2011 - 2015.
• Associate Professor, Department of Mathematics, University of Texas - Pan American, 2005 - 2011.
• Assistant Professor, Department of Mathematics, University of Texas - Pan American, 2002 - 2005.
• Assistant Project Scientist, Department of Mechanical and Aerospace Engineering, University of California, San Diego, 1998 - 2002.
• Visiting Assistant Professor, Department of Mathematics, Idaho State University, 1997 - 1998.

Projects

Salifort Motors: Salifort Motors Advanced Data Analysis using Python
Google Advanced Data Analytics Capstone Project using Python to analyze a dataset and build predictive models (Logistic Regression and Random Fores with XGBoost) that can provide insights to the Human Resources department at Salifort Motors about employee turnover.

Bellabeat: Bellabeat Marketing Analysis Case Study with R
Google Data Analytics Capstone Project using R about smart device use habits, with the goal of making recommendations for improving marketing strategies of a fictional company.

CSBN: Coupled Social and Biological Networks
Parallel Python CUDA code using the CuPy library to simulate parental decision-making about vaccinations against a childhood disease that spreads through a contact network. This model considers a bilayer network comprising two overlapping networks, which are either Erdős–Rényi (random) networks or Barabási–Albert networks. The model also employs a Bayesian aggregation rule for observational social learning on a social network. The code runs on Nvidia Graphics Processing Units.

Higgs boson: Higgs boson equation in de Sitter spacetime
Fortran CUDA and Python CUDA codes, the later using the CuPy library, to simulate the solution to the Higgs boson equation in the de Sitter Spacetime using explicit fourth order Runge–Kutta scheme on the temporal discretization and fourth order finite difference discretization in space. Bubble formation and boundedness of solutins are considered. The code runs on Nvidia Graphics Processing Units.

collegeprepmath: College Preparatory Mathematics
Online textbook materials for the Texas House Bill 5 High School College Preparatory Mathematics course administered through the University of Texas Rio Grande Valley. The textbook was created using the PreTeXt project entirely in the cloud, using GitHub Codespaces. It is based on the PDF version of the textbook "Beginning and Intermediate Algebra" by Tyler Wallace (Big Bend Community College).

Skills

• Python, R, SQL, Tableau, Kaggle, BigQuery, Spreadsheets, Power BI
• C, C++, CUDA, Fortran, Perl, Julia, Matlab, Mathematica
• Unix, Bash, GitHub, Docker
• Pandas, Numpy, CuPy, Scikit, Jupyter
• Strong analytical, problem solving and data interpretation skills.
• Ability to manage priorities and cross-functional collaboration
• Excellent communication skills
• Data cleaning
• Data ethics
• Exploratory data analysis
• Data visualization
• Regression models
• Machine learning
• Predictive models
• Statistical analysis

Publications

• "Modeling the effect of observational social learning on parental decision-making for childhood vaccination and diseases spread over household networks," Front. Epidemiol., Sec. Infectious Disease Epidemiology, Volume 3 - 2023 (12 January 2024) with T. Oraby.
• "Coordinating STEM Core Courses for Student Success," PRIMUS, 31(3–5), 316–329, 2021 with M.C. Villalobos, H.W. Kim, T.J. Huber, R. Knobel, S. Setayesh, L. Sasidharan and A. Galstyan.
• High-performance implementation of a Runge–Kutta finite-difference scheme for the Higgs boson equation in the de Sitter spacetime," Communications in Nonlinear Science and Numerical Simulation, Volume 68, March 2019, Pages 15-30, with J. Banda and K. Yagdjian.
• "The maximum principle and sign changing solutions of the hyperbolic equation with the Higgs potential," Journal of Mathematical Analysis and Applications, Volume 465, Issue 1, 1 September 2018, Pages 403-422, with K. Yagdjian.
• "Output-feedback stabilization of an unstable wave equation," Automatica, Volume 44, Issue 1, pp. 63-74, 2008, with M. Krstic, B-Z. Guo and A. Smyshlyaev.
• "Control of a Tip-Force Destabilized Shear Beam by Observer-Based Boundary Feedback," SIAM Journal on Control and Optimization, Volume 47, Issue 2, pp. 553-574, 2008, with M. Krstic, B-Z. Guo and A. Smyshlyaev.
• "Forced nonlinear oscillations of elastic membranes," Nonlinear Analysis: Real World Applications, Volume 7, Number 5, pp. 1005-1028, 2006, with V. Varlamov.
• "Global Boundary Stabilization of 2D Poiseuille Flow," Control of Fluid Flow, Lecture Notes in Control and Inform. Sci., 330, (Eds.: P. Koumoutsakos and I. Mezic), pp. 157-172, Springer, 2006, with M. Krstic.
• "Asymptotic Distribution of Eigenvalues for Damped String Equation: Numerical Approach," Journal of Aerospace Engineering, Vol. 18, Issue 2, pp. 69-83, 2005, with M. Shubov.
• "Optimal Mixing Enhancement in 3D Pipe Flow," IEEE Transactions on Control Systems Technology, Vol. 13, Issue 1, pp. 27-41, 2005, with O.M. Aamo and M. Krstic.
• "Analysis of Nonlinear Elastic Membrane Oscillations by Eigenfunction Expansion," WSEAS Transactions on Systems, Issue 4, Vol. 3, 2004, pp. 1430-1435, with V. Varlamov.
• "Stability of Partial Difference Equations Governing Control Gains in Infinite Dimensional Backstepping," Systems and Control Letters, Vol. 51, No. 2, pp. 151--164, 2004, with M. Krstic.
• "Infinite Dimensional Backstepping for nonlinear parabolic PDEs," in Unsolved Problems in Mathematical Systems and Control Theory, (Eds. V.D. Blondel and A.Megretski), pp. 12--18, Princeton University Press, 2004, with M. Krstic.
• "Backstepping in Infinite Dimension for a Class of Parabolic Distributed Parameter Systems," Mathematics of Control, Signals, and Systems, Vol. 16, No. 1, 2003, pp. 44--75, with D. Boskovic and M. Krstic.
• "Infinite Dimensional Backstepping-Style Feedback Transformations for a Heat Equation with an Arbitrary Level of Instability," European Journal of Control, Vol. 8, No. 2, pp. 165-175, 2002, with M. Krstic.
• "Stability Enhancement by Boundary Control in 2D Channel Flow," IEEE Transactions on Automatic Control, Vol. 46, No. 11, pp. 1696-1711, 2001, with W.-J. Liu, and M. Krstic.
• "Burgers' Equation with Nonlinear Boundary Feedback: H¹ Stability, Well Posedness, and Simulation," Mathematical Problems in Engineering, Vol. 6, pp. 189-200, 2000, with M.Krstic.
• "Boundary Control of the Korteweg-de Vries-Burgers Equation: Further Results on Stabilization and Well Posedness, with Numerical Demonstration," IEEE Transactions on Automatic Control, Vol. 45, No. 9, pp. 1739-1745, 2000, with M. Krstic.
• "Stationary Solutions for a Boundary Controlled Burgers' Equation," Mathematical and Computer Modeling, Vol. 33, No. 1-3, pp. 21-37, 2001, with D.S. Gilliam and V.I. Shubov.
• "Numerical Stationary Solutions for a Viscous Burgers' Equation," Journal of Mathematical Systems, Estimation and Control, Summary: Vol. 8,  No. 2, 1998, pp. 253-256, (Electronic version retrieval code: 55578),    with J. Burns, D.S. Gilliam and V.I. Shubov.
• "Modeling Infrared Imaging in Biomaterials," in Industrial Mathematics Modeling Workshop for Graduate Students, (Eds. B.Fitzpatric and H.T.Tran) CRSC-TR96-7,    Center for Research in Scientific Computation, North Carolina State University, Raleigh, NC, pp. 66-83,     with E. Cumberbatch, J. Appel, K.R. Fister, M. Luca and Z.P.Yang.

Elements

i = 0;

while (!deck.isInOrder()) {
    print 'Iteration ' + i;
    deck.shuffle();
    i++;
}

print 'It took ' + i + ' iterations to sort the deck.';