CV

Visiting Research Scientist

Schaffer Lab, Icahn School of Medicine at Mount Sinai

Gradient clipping, transfer, and task-feature learning in recurrent networks.

• Studying how gradient clipping shapes nonconvex RNN training dynamics, with a focus on transfer and task-feature learning.
• Characterizing how clipping thresholds and model parameters govern learned solutions and training complexity, toward understanding altered learning in neurological and psychiatric disorders.

Graduate Researcher, M.S. Thesis

Courant Institute of Mathematical Sciences, New York University

Dynamical systems models of PP1/PP2A regulation in LTP formation.

• Developing phenomenological dynamical-systems models of PP1/PP2A regulation of CaMKII-dependent LTP formation; manuscript in preparation.
• Performing numerical bifurcation analysis (continuation, Jacobian spectral analysis) in Python and TensorFlow across kinase, phosphatase, and calcium parameters.
• Identified tristable regimes set by T286/T305 phosphorylation, and phosphatase thresholds governing calcium-driven LTP/LTD switching.

Teaching Assistant

Courant Institute of Mathematical Sciences, New York University

• Lead recitations, hold office hours, and develop problem sets and review materials for Calculus I, Calculus II, and Linear Algebra.

Mathematics Research Assistant

Department of Mathematics, University of South Carolina

Coarse-grained event tree analysis of GLIF neuronal networks (Advisor: Dr. Yi Sun).

• Built a Python event tree analysis (ETA) framework for GLIF networks to quantify network dynamics and input discriminability.
• Used conditional probability distributions over event chains to measure sensitivity to small input perturbations.
• Showed that synaptic conductance and Gaussian noise critically shape excitability thresholds.

Undergraduate Teaching Assistant

Department of Mathematics, University of South Carolina

• Assisted instruction and grading and led problem-solving sessions for Ordinary Differential Equations and Calculus II.

Undergraduate Research Assistant

Department of Mathematics, University of South Carolina

GLIF modeling and simulation (Advisor: Dr. Yi Sun).

• Implemented a GLIF model bridging LIF and Hodgkin-Huxley dynamics for large-scale networks.
• Built a simulation pipeline for neuronal responses under variable noise and synaptic coupling; supported by the UREP Grant and Magellan Fellowship.

Machine Learning Intern

Moving Image Research Collections, University of South Carolina

• Benchmarked image-reconstruction models on NVIDIA GPU clusters, optimizing latency and throughput.
• Developed C++/OpenGL tooling for automated film restoration.

Software Engineering Intern

Department of Technology, University of South Carolina

• Integrated machine-learning image classifiers into an NSF-funded remote-sensing app for mosquito egg abundance.

Undergraduate Research Assistant

Artificial Intelligence Institute, University of South Carolina

DRAX group (Dr. Forest Agostinelli).

• Applied tensor decomposition to PyTorch deep and reinforcement learning models to improve training efficiency in high-dimensional environments.

M.S.

New York University, Courant Institute of Mathematical Sciences

Mathematics, Applied Mathematics Thesis Track

• Thesis: Phenomenological Models of PP1/PP2A Regulation in LTP Formation: A Dynamical Systems Analysis (working title).
• Advisor: David McLaughlin.

B.S.

University of South Carolina

Computer Science and Mathematics

• Minor in Data Science.
• Capstone Scholar.