Dr. Reinaldo (Rei) Sanchez-Arias joined Florida Polytechnic University in the fall
2018 and is an assistant professor of data science and serves as the assistant chair
of the Department of Data Science and Business Analytics. Sanchez-Arias earned his
Bachelor of Science degree in Mathematics from Universidad del Valle in Cali, Colombia.
In the fall of 2008 he started his doctoral studies in the Computational Science Program
at The University of Texas at El Paso (UTEP). During his years at UTEP, he was involved
in research projects for the Army High-Performance Computing Research Center (AHPCRC)
in collaboration with a group at Stanford University. He interned at Repsol Oil Company
USA during the summer of 2011, where he worked with the Research and Innovation Geophysics
Department. He obtained a Ph.D. degree in computational science from UTEP in the spring
of 2013, working on sparse representation methods for classification problems and
dimensionality reduction. He completed a postdoctoral researcher appointment for the
AHPCRC working in reduced order models for underbody-blast simulations and compression
techniques. From 2014 to 2016, Sanchez-Arias was part of the Applied Mathematics Department
at Wentworth Institute of Technology (WIT) in Boston, Massachusetts, where he taught
courses for applied mathematics and engineering students, nominated and served as
the faculty advisor for the Society of Industrial and Applied Mathematics (SIAM) Student
Chapter, coordinated linear algebra and capstone courses, and helped develop different
elective courses in applied mathematics. In the fall of 2016, Sanchez-Arias joined
St Thomas University, in Miami, Florida, where he served as the program director for
the master of science degree in big data analytics in the School of Science, advised
and supervised graduate students in the School of Science, and revised curriculum
for the computer science and mathematics undergraduate programs.
In the fall of 2018, he joined the Department of Data Science and Business Analytics
(DSBA) at Florida Poly, where he leads multiple data science research projects, and
teaches courses for the BS in Data Science, BS in Business Analytics, MS in Data Science,
and MS in Engineering Management programs. Sanchez-Arias was the recipient of Florida
Poly’s Excellence in Teaching Ablaze Award in 2020. He was invited as scientific session
speaker in the area of statistics and data analysis for the LatMath 2022 conference
sponsored by the Institute for Pure and Applied Mathematics (IPAM) at UCLA, and was
also an invited speaker for the INFORMS Teaching Effectiveness Colloquium in 2021,
which featured speakers from business and engineering schools who address different
aspects of incorporating and assessing effective teaching techniques in OR/MS/analytics
undergraduate or graduate curriculum.
His general areas of interest include data mining and machine learning, computational
linear algebra and optimization, and data science education. His work has been presented
at international and national conference meetings including SIAM annual meetings,
the International Conference for High Performance Computing, the IEEE International
Conference of the Engineering in Medicine and Biology Society, the IEEE International
Conference in Machine Learning and Applications, and INFORMS annual meeting. Sanchez-Arias
is a member of SIAM, IEEE, IEOM, ACM and INFORMS.
Outstanding Service Award, IEOM, 2022
Ablaze Excellence in Teaching Award, Florida Polytechnic University, 2020
Best Paper Award in the Data Analytics and Big Data Track, Industrial Engineering
and Operations Management (IEOM) 6th North American Conference, 2021
Outstanding Ph.D. Dissertation Award, The University of Texas at El Paso, 2014
Academic Excellence Award, The University of Texas at El Paso, 2013
Ph.D. in Computational Science, The University of Texas at El Paso, 2013
M.S. in Computational Science, The University of Texas at El Paso, 2011
B.S. in Mathematics, Universidad del Valle, Cali, Colombia, 2008
Supervised and Unsupervised Learning
Data Mining and Text Mining
Data Science Education
Member, Institute for Operations Research and the Management Sciences (INFORMS) Education
Outreach Committee, 2020-current
Conference Associate Chair, IEOM North America Conference, 2022
Chair, Curriculum and Assessment Committee Florida Poly Data Science and Business
Member, Institute of Electrical and Electronics Engineers (IEEE), 2018-present
Member, Society for Industrial and Applied Mathematics (SIAM), 2011-present
Dials, J., Demirel, D., Sanchez-Arias, R., Halic, T., Kruger, U., De, S., & Gromski,
M. A. (2023). “Skill-level classification and performance evaluation for endoscopic
sleeve gastroplasty”. Surgical Endoscopy, 1-12.
Dewey, J., Ingram, C., & Sanchez-Arias, R. (2022) “A Supervised Learning Approach
to Assessing Accounts Receivable Risk in Small-to-Medium Enterprises”. Proceedings
of the 7th North American Conference on Industrial Engineering and Operations Management
(IEOM), pp. 1805-1815.
Dewey, J., Kindle, K., Vadlamani, S., & Sanchez-Arias, R. (2021). “State Marijuana
Laws and Traffic Fatalities”. Review of Regional Studies, 51(3), 246-265.
Sanchez-Arias, R., Batista, R., Nicklas, L. C., & Akioyamen, P. (2021) “Dimensionality
Reduction and Text Mining for Smart Content Filtering of an Online Health Forum”.
Proceedings of the 6th North American Conference on Industrial Engineering and Operations
Management (IEOM), pp. 2367-2374.
Batista, R. W., & Sanchez-Arias, R. (2020). “A Methodology for Estimating Hospital
Intensive Care Unit Length Of Stay Using Novel Machine Learning Tools”. 19th IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 827-832.
Akioyamen, P., Nicklas, L. C., & Sanchez-Arias, R. (2020). “A Framework for Intelligent
Navigation Using Latent Dirichlet Allocation on Reddit Posts About Opiates”. Proceedings
of the 2020 the 4th International Conference on Compute and Data Analysis, pp. 190-196.
Sanchez-Arias, R., & Batista, R. W. (2019). “Unsupervised Learning on the Health and
Retirement Study using Geometric Data Analysis”. 18th IEEE International Conference On Machine Learning And Applications (ICMLA), pp. 335-340.
Goss, Q., Akbaş, M. İ., Jaimes, L. G., & Sanchez-Arias, R. (2019). “Street Network
Generation with Adjustable Complexity Using K-Means Clustering”. 2019 IEEE SoutheastCon,
Aguilar-Bonavides, C., Sanchez-Arias, R., & Lanzas, C. (2014). “Accurate Prediction
Of Major Histocompatibility Complex Class II Epitopes By Sparse Representation via
l1-minimization”. BioData Mining, 7(1), 1-14.
Sanchez, R., Argáez, M., & Guillén, P. (2011). “Sparse Representation via l1-minimization
for Underdetermined Systems in Classification of Tumors With Gene Expression Data”.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 3362-3366.