Work under David Ayala concerning aspects of factorization homology, especially over the circle and the torus. The factorization homology over the circle is a generalization of Hochschild homology while the factorization homology of surfaces can be used generalize the (Kauffman bracket) skein category on that surface. There is a combinatorial definition of the factorization homology over a circle which was used to calculate the Hochschild homology of any Reedy category. There is not yet a combinatorial definition of the factorization homology over a surface, but it is being developed as a part of this work.
Work under Kathleen Hamilton investigating whether LC equivalent graph states are connected by low loss valleys in the loss landscape of a Quantum Circuit Born Machine model.
Youngstown State University. (2017-2020) Work under Alicia Prieto Langarica in agent-based modelling.
Youngstown State University. (2018-2021) Work under Alina Lazar attempting to automatically tag StackOverflow questions using deep learning.
Youngstown State University. (2018-2022) Work under Donald Priour studying perolation, specifically around toriodal inclusions.
Lawrence Berkeley National Laboratory. (Summer 2018) Work with Alina Lazar, Alex Sim, Kesheng Wu mitigating the effects of missing values in joint sequence analysis.
Lawrence Berkeley National Laboratory. (Summer 2019) Work with Daniel Ladiges and Andy Nonaka modeling graphene squeeze-film pressure sensors.
Lawrence Berkeley National Laboratory. (2020-2022) Work with Xiangyang Ju, Daniel Murnane, Paolo Calafiura, and others in the Exa.TrkX group comparing the performance of calorimeter clustering algorithms.
Machine Learning for Prediction of Mid to Long Term Habitual Transportation Mode Use. Joint with Ling Jin, Anna Spurlock, Alexander Sim, Kesheng Wu, and Alina Lazar. IEEE (2019)
Agent-Based Modeling in Mathematical Biology: A Few Examples. Joint with Lindsey Chludzinski and Alicia Prieto-Langarica. Chapter pp 273–298 (2020).
Percolation through Voids around Toroidal Inclusions. Joint with Payton Linton and Donald Priour. Physical Review E (2023).
Reconstruction of Large Radius Tracks with the Exa.TrkX pipeline. Joint with Chun-Yi Wang et.al. Journal of Physics: Conference Series (2023).
Accelerating the Inference of the Exa.TrkX Pipeline. Joint with Alina Lazar et.al. Journal of Physics: Conference Series (2023)
Performance of a Geometric Deep Learning Pipeline for HL-LHC Particle Tracking. Joint with Xiangyang Ju et. al. The European Physical Journal C (2021)
Physics and Computing Performance of the Exa.TrkX TrackML Pipeline. Joint with Xiangyang Ju et. al. Fermilab (2021).
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