Joaquin Carbonara

Education

Ph.D., Mathematics - Combinatorial Algorithms and Representation Theory (University of California San Diego)

M.S., Computer Science (SUNY University at Buffalo)

M.A., Mathematics (San Diego State University)

B.A., Mathematics with a minor in Italian (San Diego State University)

Extensive musical training as part of El Systema (Caracas, Venezuela)

Research Focus

• Transdisciplinary applications of Mathematics in Machine Learning
  • Mathematics as a tool for explainability
  • Data Ethics, Culture, Strategy and Governance
  • Modern Mathematical tools in ML that go beyond traditional math approaches
  • Translation and infusion of Mathematical DSA tools to other disciplines
     
• Dissemination of Data Science and Analytics (DSA) as the literacy of the 21st century
  • Creation of effective and relevant DSA curriculum across disciplines in academia
  • Connections between academia and industry
  • Creation of learning communities, centers, startups and more
  • Future Thinking and scenarios based on current and relevant discoveries in DSA
     
• Combinatorial Algorithms
   
• Fractals theory and applications
  • Fractal dimensions as features in a data set
  • Discrete Mathematical models

Modes of Research

• Computational paradigm applications: Machine Learning, Convoluted Neural Networks, Natural Language Processing, Reinforced Learning, Explainability, AI Ethics.
• Computational tools: Python, Cloud Computing.
• Transdisciplinary Team Discovery.

CISNN-specific Research:

Dr. Carbonara focuses is on accelerated research, discovery and visualization on a transdisciplinary environment leveraging the AI tools (ML, CNN, etc.).

CISNN specific publications, white papers, grants, and other resources:

• Carbonara, Ahmed*, et al. “A Machine Learning Approach to Delineate Impact of Materials Properties on Solar Cell Device Physics”, ACS Omega, JUST ACCEPTED, May 2022. {Clean Energy: Device Physics, Computation, ML, Ethics}
• Carbonara, Ahmed*, et al. “Supervised Machine Learning-Aided SCAPS-Based Quantitative Analysis for the Discovery of Optimum Bromine Doping in Methylammonium Tin-Based Perovskite (MASnI3−xBrx)”, ACS Applied Materials and Interfaces, published December 2021. {Clean Energy: Device Physics, Computation, ML, Ethics}
• Carbonara, Ahmed, Biswas* “Superoxide Mediated Transition Metal Oxides for Aerobic Oxidation Reactions”, DOE White Paper, 2022 (did not ultimate get invited) {Catalysis, Energy and Reaction Engineering: Experiment, Computation, ML}
• Ettestad, David; Carbonara, Joaquin, The Sierpinski Triangle Plane, Fractals Vol. 26, No. 01 (2018).

Synergistic activities in DSA

Academics

• Chair of the Data Science and Analytics MS at SUNY Buffalo State (2019 – current)

Conference organizer

• Co-chair of the conference Buffalo CIO Panel. Buffalo State Alumni Center. April 3, 2019.
• Co-chair of the conference Data Strategy and Governance. Buffalo State Alumni Center. November 2, 2018.
• Chair of the conference Data Analytics Across Disciplines. Niagara Fall Convention Center. There were 30 presentations and 110 attendees from all over the U.S, May 18-19, 2016.
• Co-Chair (with Dr. Reneta Barneva from Fredonia) of the conference Buffalo SAS Day. There were 70 attendees. Spring 2016.
• Chair of the National Professional Science Master’s Association annual conference. Arlington VA, Nov 2015.
• Co-chair of the conference Opportunities in Data Sciences. Worcester, MA, MAY 28-29, 2013.