CV

Education

Stony Brook University (May 2021)

Bachelor of Science, Applied Mathematics, Physics (2^nd Major)

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Florence University of the Arts (Fall 2018)

Study Abroad

Research Experience

Technergetics, Utica, NY (June 2023 – Present)

Quantum Communications Research Engineer, Air Force Research Laboratory

• Research in machine learning applications of quantum algorithms.
• Heading research designing novel quantum graph neural networks for particle interaction simulation.

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Griffiss Institute, Rome, NY (May 2021 – May 2023)

Research Associate, Air Force Research Laboratory

• Research in machine learning applications of quantum algorithms.
• Headed research designing novel quantum graph neural networks for particle interaction simulation. Resulted in a 1^st author publication by the journal AVS Quantum Science.
• Created three varieties of graph neural networks based in Python. Created a classical graph neural network utilizing complex implementations of TensorFlow and Sonnet. Created two unique realizations of quantum graph neural networks utilizing complex implementations of Pennylane and Sonnet.

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Stony Brook University, Stony Brook, NY (Sept. 2020 – May 2021)

Student Researcher

• Research in high energy accelerator simulators.
• Utilized C++ to compare the efficiencies of the simulation software BeAGLE and FLUKA in modeling the fission and evaporation processes following the deep inelastic scattering of rare/exotic nuclei. Resulted in a contribution to the Science Requirements and Detector Concepts for the Electron-Ion Collider: EIC Yellow Report.

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Griffiss Institute, Rome, NY (Summer 2019, June 2020 – May 2021)

Intern, Air Force Research Laboratory

• Research in ion trapping and machine learning applications of quantum algorithms.
• Designed input data and amplitude encoding software using Qiskit for a project exploring information loss in quantum data compression, in the context of quantum autoencoders. Resulted in a 2^nd author publication by the journal Physica Scripta.
• Designed noise modeling software for quantum Bayesian networks, utilizing in-depth implementation of Qiskit. This became the base of a Bayesian network UI that is currently in development.
• Aided in the construction of a dust trap and the development of simulation software for surface ion traps.

Relevant Papers

• Collis, B., Patel, S., Koch, D., Cutugno, M., Wessing, L., & Alsing, P. (2022). Physics Simulation Via Quantum Graph Neural Network. . AVS Quantum Science. https://doi.org/10.1116/5.0145722

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• Patel, S., Collis, B., Duong, W., Koch, D., Cutugno, M., Wessing, L., & Alsing, P. (2023). Information loss and run time from practical application of quantum data compression. Physics Scripta. https://iopscience.iop.org/article/10.1088/1402-4896/acc492

Programming Languages & Relevant Software Packages

(Novice->Intermediate->Proficient->Advanced)

Python (Proficient), including

• Tensorflow (Advanced)
• Keras (Advanced)
• Qiskit (Proficient)
• Pennylane (Intermediate)

C++ (Intermediate)

LaTeX (Proficient)

Windows (Advanced)

Linux (Intermediate)

Microsoft Office Suite (Advanced)

Honors and Awards

Dean’s List (Fall 2017 – Spr. 2018, Spr. 2019)

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Stony Brook University Presidential Scholarship (2017)