JC

Joaquin O. Carbonara

Professor of Mathematics & Director, Data Science and Analytics
SUNY Buffalo State University
Full CV Google Scholar Academia.edu ResearchGate DBLP Math Genealogy GitHub carbonjo@buffalostate.edu

About

Dr. Joaquin O. Carbonara is Professor of Mathematics at SUNY Buffalo State, where he directs the Data Science and Analytics program. He earned his Ph.D. in Mathematics from the University of California, San Diego, and an M.S. in Computer Science from the University at Buffalo. He is passionate about translating AI advances into both scholarship and pedagogy, applying these methods to develop novel curricula and community-engaged workshops in augmented human intelligence.

As an active leader in academic and professional circles, he has been invited to review grants for the National Science Foundation and the National Institutes of Health, review Data Science programs for universities, serve as external evaluator for Data Science programs, and co-chair major conferences.

His recent work explores the intersection of machine learning, large language models, and statistical methodology. He founded the Professional Science Master's in Computational and Applied Mathematics (2010) and the Professional Science Master's in Data Science and Analytics (2020) at Buffalo State.

Research Metrics

9
h-index (All Time)
6
h-index (Since 2021)
368
Citations (All Time)
257
Citations (Since 2021)
8
i10-index (All Time)
28
Peer-Reviewed Publications
$1.5M+
External Funding (PI)

★ Source: Google Scholar (verified April 2026) · ResearchGate

Citations per Year (Google Scholar)
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Research Areas

Machine Learning & AI Large Language Models Data Science Algebraic Combinatorics Schur Functions & Symmetric Functions Cellular Automata Fractals Perovskite Solar Cells Biomathematics Geoinformatics Clean Energy Analytics Statistics

Publications

2025
1
Augmenting intelligence: The convergence of ML/LLMs and statistics
Carbonara, J. & Fokoue, E. · Stat, 14(1), e70043 · Wiley, 2025
Machine LearningData Science
2
Machine learning analysis of New York clean energy trends
Gokavarapu, K.N., Gore, N.A., Ohri, C., Carbonara, J., Ahmed, S. · Energy Economics, 152, 109039 · 2025
Machine LearningData Science
2023
3
Data-driven design for enhanced efficiency of Sn-based perovskite solar cells using machine learning
Rumman, A.H., Sahriar, M.A., Islam, M.T., Shorowordi, K.M., Carbonara, J., Broderick, S., Ahmed, S. · APL Machine Learning, 1(4): 046117 · AIP, 2023
Machine Learning
4
An Integrated Assessment of Next Generation PV Technologies
Wikar, J., White, N., Body, T., Vullo, M., Tse, L., Biswas, S., Carbonara, J., Ahmed, S. · American Journal of Energy Engineering, 11(4), pp. 100–109 · 2023
Machine Learning
5
Effect of bromide incorporation on the electronic & photovoltaic properties of Sn-based perovskite devices
Rauf, A., Sarker, S., Islam, M.S., et al., Carbonara, J., Ahmed, S. · Solar Energy, 253, pp. 375–388 · 2023
Machine Learning
2022
6
Machine Learning Approach to Delineate the Impact of Material Properties on Solar Cell Device Physics
Islam, M.S., Islam, M.T., Sarker, S., et al., Carbonara, J., Ahmed, S. · ACS Omega · 2022
Machine Learning
2021
7
Investigation of non-Pb all-perovskite 4-T mechanically stacked and 2-T monolithic tandem solar devices utilizing SCAPS simulation
Islam, M.T., Jani, M.R., Rahman, S., et al., Carbonara, J., Ahmed, S. · SN Applied Sciences, 3, 504 · 2021
Machine Learning
8
A Supervised Machine Learning Approach towards Accelerating the Development of High-performance non-Pb Perovskite Solar Devices
Islam, M.S., et al., Carbonara, J., Ahmed, S. · Computational Materials Science · 2021
Machine Learning
9
Supervised machine learning aided SCAPS-based quantitative analysis for the discovery of optimum bromine doping in methylammonium tin-based perovskite (MASnI₃₋ₓBrₓ)
Al Jame, H., Sarker, S., Islam, M.S., et al., Carbonara, J., Ahmed, S. · ACS Applied Materials & Interfaces, 14, pp. 502–516 · 2021
Machine Learning
10
Numerical simulation studies of Cs₃Bi₂I₉ perovskite solar device with optimal selection of electron and hole transport layers
Islam, M.T., Jani, M.R., Shorowordi, K.M., et al., Carbonara, J., Ahmed, S. · Optik, 231, 166417 · 2021
Machine Learning
2019
11
Distinguishing Between Sierpinski Triangle Constructions
Ettestad, D. & Carbonara, J. · Fractals · World Scientific, 2019
Fractals
2018
12
The Sierpinski Triangle Plane
Ettestad, D. & Carbonara, J. · Fractals, 26(1) · World Scientific, 2018
Fractals
2015
13
Extending the Sierpinski Property to all Cases in the Cups and Stones Counting Problem by Numbering the Stones
Ettestad, D. & Carbonara, J. · Journal of Cellular Automata, 10(1–2), pp. 23–51 · 2015
FractalsCellular Automata
2011
14
The Cups and Stones Counting Problem, the Sierpinski Gasket, Cellular Automata, Fractals and Pascal's Triangle
Ettestad, D., Carbonara, J., Jansma, M., Rua, M., Sember, K. · Journal of Cellular Automata, 6, pp. 421–437 · 2011
FractalsCellular AutomataCombinatorics
2010
15
Formulas for the Number of States of an Interesting Finite Cellular Automaton and a Connection to Pascal's Triangle
Ettestad, D. & Carbonara, J.O. · Journal of Cellular Automata, 5(1/2), pp. 157–166 · 2010
Cellular AutomataCombinatorics
16
Two-compartment model interacting with proliferating regulatory factor
Shojania-Feizabadi, M. & Carbonara, J. · Applied Mathematics Letters, 23(1), pp. 30–33 · January 2010
Biomathematics
2009
17
Woody Plants Modulate The Temporal Dynamics of Soil Moisture in a Semi-Arid Mesquite Savanna
Potts, D., Scott, R., Bayram, S., Carbonara, J. · Ecohydrology · Wiley, 2009
Ecology
18
Feature Shape and Elevation Based Road Classification and Extraction on High Spatial Resolution Remote Sensing Imageries
Tang, T., Shi, Z., Carbonara, J., Wang, X. · Geoinformatics 2009 Proceedings · August 2009
Geoinformatics
2006
19
Fractal Properties of the Matrix for the Cups and Stones Counting Problem
Carbonara, J.O. & Ettestad, D. · International Journal of Pure and Applied Mathematics, 29(1), pp. 81–106 · 2006
FractalsCombinatorics
2003
20
Trace Cocharacters and the Kronecker Products of Schur Functions
Carbonara, J.O., Carini, L. & Remmel, J. · Journal of Algebra, 260, pp. 632–656 · 2003
Algebraic CombinatoricsSchur Functions
1998
21
Enumerative Questions on Weighted Rooted Necklaces
Carbonara, J.O. & Green, A. · Advances in Applied Mathematics, 21, pp. 405–423 · 1998
Combinatorics
22
A combinatorial interpretation for the inverse t-Kostka matrix
Carbonara, J.O. · Discrete Mathematics, 193, pp. 117–145 · Elsevier, 1998
Algebraic CombinatoricsSymmetric Functions
1995
23
A Combinatorial Proof of the Equivalence of the Classical and Combinatorial Definitions of Schur Functions
Carbonara, J.O., Kulikauskas, A. & Remmel, J.B. · Journal of Combinatorial Theory, Series A, 72(2) · Academic Press, 1995
Algebraic CombinatoricsSchur Functions
24
A Combinatorial Rule for the Schur Function Expansion of the Plethysm s(1a,b)[pk]
Carbonara, J.O., Remmel, J. & Yang, M. · Linear and Multilinear Algebra, 39, pp. 341–373 · 1995
Algebraic CombinatoricsSchur Functions

24 refereed journal articles listed above. For books, book chapters, and complete details see the full CV page.

Selected Grants & Awards (PI)

NSF SMP: Professional Applied and Computational Mathematics M.S. (Award NSF SMP 10-11166)
National Science Foundation · PI · 2010–2013
$697,039
NSF Collaborative Research: CSUMS: URGE to Compute (Award #0802964)
National Science Foundation · PI · Collaborative with UB · 2008–2013
$300,549
NASA Education and Public Outreach Program
NASA · Co-I · 2010–2012
$270,355
NSF ILI: Group Discovery and Communication: A Computer Lab Approach (Co-PI)
National Science Foundation · Co-PI · 1993
$76,676
SUNY Performance Improvement Fund — Professional Science Master's in Data Analytics
SUNY · PI · 2018–2019
$160,000
Roswell Park Comprehensive Cancer Center
PI · 2022
$60,000
Glenn Bayley W Foundation
PI · December 2023
$50,000
Cummings Foundation
PI · May 2023
$40,000

Total external funding as PI/Co-PI: $1.5M+ · Full grant history →