Fokoué Research Group

Teaching Projects

• Courses taught
• Teaching Philosophy
• Teaching Initiatives
• Teaching Appointments around the world
• African Institute for Mathematical Sciences (AIMS)
• RIT Dubai
• University of Rwanda – African Center for Excellence
• Universite de Bretagne-Sud

Service Projects

• UPSTAT Conference Series (since 2012)
  The UPSTAT Conference Series is an annual gathering of statisticians, data analysts, and data enthusiasts. It features talks and poster sessions presented by professionals, faculty, postdocs, and students at all levels.
   
• ASA DataFest at RIT Series (since 2017)
  The American Statistical Association (ASA) DataFest is a celebration of data in which teams of undergraduates work around the clock to find and share meaning in a large, rich, and complex data set.
   
• Pre-College Data Science Challenge (since 2018)
  This data hackathon, created specifically for pre-college students, is proudly sponsored by the Student Chapter of the American Statistical Association (ASA) at the Rochester Institute of Technology.

Present Institutions

• Rochester Institute of Technology
• African Institute for Mathematical Sciences
• University of Dschang
• University of Rwanda

Past Institutions

• Kettering University
• Ohio State University
• Duke University
• Fudan University
• Université de Bretagne-Sud
• University of Glasgow
• Aston University
• University of Yaoundé

Are you interested in having Dr. Fokoué as a speaker at your upcoming event? He is available for speaking engagements. For inquiries, reach out using the contact link provided below.

Contact

Statistical Machine Learning and Protein Dynamics (2022)

• Babbitt GA, Fokoue EP, Srivastava HR, Callahan B, Rajendran M. (2022) Statistical machine learning for comparative protein dynamics with the DROIDS/maxDemon software pipeline. STAR Protoc. 2022 Feb 24;3(1):101194.

Bayesian Methods and Regression Models (2022)

• Ma, Z. and Fokoue, E. (2022) Bayesian variable selection for linear regression with the κ − G priors, Mathematics for Applications, Vol 11, Pages 143-154, 2022.

Deep Learning and Kernel Machines (2022)

• Pei, E. and Fokoue, E. (2022) On Some Similarities and Differences Between Deep Neural Networks and Kernel Learning Machines, Mathematics for Applications, Vol 11, Pages 75-106, 2022.

Model Selection and Statistical Learning Theory (2021-2020)

• Fokoue, Ernest (2021) Kernel Regression, Wiley Statistics Reference Online.
• Murray, Ryan W. and Fokoue, Ernest (2021) Dropout Fails to Regularize Nonparametric Learners, Journal of Statistical Theory and Practice., Volume 15, Pages 1-20, 2021.
• Pei, E. and Fokoue, Ernest (2021) Graph Enhanced High Dimensional Kernel Regression, ArXiv 2011.01990., stat.ML, November, 2020.
• Fokoue, Ernest (2020) Model Selection for Optimal Prediction in Statistical Machine Learning, Notices of the American Mathematical Society., Volume 67, Number 2, Pages 155-168, February, 2020.

Ensemble Learning and Methodology (2020-2018)

• Wu, Q. and Fokoue, E. and Kudithipudi, D. (2018) An Ensemble Learning Approach to the Predictive Stability of Echo State Networks, Journal of Informatics and Mathematical Sciences (JIMS), Vol 10, Numbers 1-2, Pages 181-199, 2018.
• Elshrif, M. and Fokoue, E. (2018) Random subspace learning (RASSEL) with Data Driven Weighting Schemes, Mathematics for Applications, Vol 7, Pages 11-30, 2018.

Data Science and Statistical Methodology (2019-2018)

• Fokoue, E. (2019) On the Ubiquity of the Bayesian Paradigm in Statistical Machine Learning and Data Science, Mathematics for Applications, Vol 8, Pages 189-209, 2019.
• Fokoue, E. and Brimkov, B. (2018) The Multifaceted Impact of Statistical Methodology and Theory in Data Science, Mathematics for Applications, Vol 7, Pages 1-2, 2018.

Alternative Statistical Approaches (2017-2016)

• Zhang, X. and Rollins, B. and Gunduz, N. and Fokoue, E. (2017) Estimating the strength of the impact of rushing attempt in NFL game outcomes, British Journal of Mathematics & Computer Science, Vol 22, Number 4, Pages 1-12, 2017.
• Jha, U. K. and Bajorski, P. and Fokoue, E. and Van Aardt, J. and Anderson, G. (2017) Dimensionality Reduction of High-Dimensional Highly Correlated Multivariate Grapevine Dataset, Open Journal of Statistics, Vol 7, Number 4, Pages 702-717, 2017.

Human Monitoring and Behavioral Analysis (2017)

• Rantanen, E. M. and Fokoue, E. and Gegner, K. and Haut, J. and Overbye, T. J. (2017) Data properties underlying human monitoring performance, In Human Factors and Ergonomics Society 2017 Annual Meeting, Pages 1711-1715. SAGE Publications, October 2017.

Information Theory and Statistical Modeling (2016-2015)

• N. Gunduz and E. Fokoue (2016) An Information-Theoretic Alternative to the Cronbach’s Alpha Coefficient of Item Reliability, British Journal of Mathematics & Computer Science, Volume 15, Number 1, Pages 1-9, 2016.
• Ly, V. and Fokoue, E. (2016) Frequentist Approximation of the Bayesian Posterior Inclusion Probability by Stochastic Subsampling, British Journal of Mathematics & Computer Science, Vol 18, Number 5, pp 1-22, 2016.

Application of Bayesian Networks (2016)

• Zhang, X. and Bramati, M. C. and Fokoue, E. (2016) Using Dynamic Bayesian Networks to Characterize and Predict Job Placement, ICCSS 2017: International Conference on Computational Social Science, Amsterdam, The Netherlands, (May 14-15, 2017), Volume 3, Number 5, Page 3035, 2016.

• Principles and Theory for Data Mining and Machine Learning, Springer Verlag, 2009
• Logistic Regression, Springer Verlag, 2025, To Appear
• Statistical Machine Learning for Data Science, Springer Verlag, 2025, To Appear

• Associate Editor, Statistics, Taylor and Francis
  Taylor & Francis Group is an international company originating in England that publishes books and academic journals.
   
• Associate Editor, International Journal of Biostatistics, De Guyter
• Associate Editor, Health Services Journal , Springer
• Associate Editor, Mathematics for Applications Journal

Statistical Modeling and Machine Learning Applications (2015)

• Corsetti, M. and Fokoue, E (2015) Nonnegative Matrix Factorization with Zellner Penalty, Open Journal of Statistics, Vol. 5, No. 7, pp. 777-786, December 2015.

Outlier Detection and Bayesian Methods (2015)

• Liu, B. and Fokoue, E (2015) Random Subspace Learning Approach to High-Dimensional Outliers Detection, Open Journal of Statistics, Vol. 5, No. 6, pp. 618-630, October 2015.

Bayesian Variable Selection and Regression (2015)

• Dey, T. and Fokoue, E (2015) Bayesian Variable Selection for Predictively Optimal Regression, Book Chapter, Current Trends in Bayesian Methodology with Applications, Editors, Dipak K. Dey, Umesh Singh and A. Loganathan, Published by Chapman & Hall/CRC Press, 2015.

Big Data Analysis and Predictive Learning (2014)

• Fokoue, E (2014) A Taxonomy of Big Data for Optimal Predictive Machine Learning and Data Mining, Serdica Journal of Computing, Volume 8, Number 2, pp 111-136, 2014.
• Bill, J. and Fokoue, E (2014) A Comparative Analysis of Predictive Learning Algorithms on High-Dimensional Microarray Cancer Data, Serdica Journal of Computing, Volume 8, Number 2, pp 137-168, 2014.

Signal Processing and Pattern Recognition (2014)

• Ma, Z. and Fokoue, E (2014) Accent Recognition For Noisy Audio Signals, Serdica Journal of Computing, Volume 8, Number 2, pp 169-182, 2014.

Bayesian Models and Correlated Topic Modeling (2014)

• Yu, X. and Fokoue, E (2014) Probit Normal Correlated Topic Models, Open Journal of Statistics, Vol. 4, No. 11, pp. 879-888, December 2014.

Speaker Accent Recognition and Machine Learning (2014)

• Ma, Z. and Fokoue, E (2014) A Comparison of Classifiers in Performing Speaker Accent Recognition Using MFCCs, Open Journal of Statistics, Vol. 4, No. 4, 258-266, 2014.

• Fokoue, E (2013) Simultaneous Variable Selection and Sensor Selection using Convex Penalties, Interstat, April 2013.
• Fokoue, E (2012) Beta Induced Sparsity Algorithm, Advances and Applications in Statistical Sciences, Volume 7, Issue 7, October 2012, Pages 75-82.
• Fokoue, E (2011) Stable Radial Basis Function Selection via Mixture Modelling of the Sample Path, Journal of Data Science, Vol 9, Issue 3, pp. 345-358, October 2011.
• Fokoue, E and Sun, D. and Goel, P. (2011) Fully Bayesian Analysis of the Relevance Vector Machine With Extended Prior, Statistical Methodology. Vol 8, Pages 83-96, 2011.
• Fokoue, E and Goel, P. (2011) An Optimal Experimental Design Perspective on Radial Basis Function Regression, Communications in Statistics: Theory and Methods, Vol 40, Issue 6, Pages 1-12, 2011.
• Fokoue, E and B. Clarke (2009) Bias Variance Tradeoff for Prequential Model List Selection, Statistical Papers. Here, 2009.
• Fokoue, E (2009) Bayesian computation of the Intrinsic Structure of Factor Analytic Models, Journal of Data Science, Volume 7, Number 3, pp. 285-311, 2009.
• Fokoue, E. (2009) Latent Variable Models in Heterogeneous Spaces for Observations of Mixed Types, Communications in Statistics - Theory and Methods. 38, pp. 1-12, 2009.
• Fokoue, E. (2008) Foundational Aspects of the Theory of Statistical Function Estimation and Pattern Recognition, Bulletin of PFUR, Series Mathematics, Information Sciences, Physics. 3, pp. 40-54, 2008.
• Fokoue, E. (2007) Estimation of Atom Prevalence for Optimal Prediction, Contemporary Mathematics, Vol 443, pp 103-129, The American Mathematical Society.
• Fokoue, E. (2004) Mixtures of Factor Analyzers: An Extension with Covariates. Journal of Multivariate Analysis, 95, 370-384.
• Fokoue, E. and Titterington, D. M. (2003) Mixtures of Factor Analyzers: Bayesian Estimation and Inference by Stochastic Simulation, Machine Learning, 50, 73-94.
• Csato, L., Fokoue, E, Opper, M, Schottky, B., Winther, O. (2000) Efficient Approaches to Gaussian Process Classification, Advances in Neural Information Processing Systems 12, S. A. Solla, T. K. Leen, K.-R. Müller, eds., MIT Press, 2000.