Troy, New York, United States
Multidisciplinary computational physicist with seven years of research experience, including at DOE-funded laboratories and in a research university environment. Familiarity with biophysics, astrophysics, nuclear physics, and particle physics, with a focus on the application of AI/ML techniques to physical sciences. Passionate about education and mentorship, as well as the intersection of science with public policy.
Chen Lab - Research in physics-informed structure modeling and dynamics simulation
See description below - continuation of same project as a salaried technical intern at PNNL.
Department of Energy Science Undergraduate Laboratory Internship (SULI) | Machine Learning for Systems Biology from High-throughput Data with CellBox | Advisor: Dr. Margaret Cheung · Used the CellBox hybrid machine learning model to conduct studies of multiple synthetic dynamical systems as well as real-world cyanobacteria data from the National Center for Biotechnology Information · Developed models of nonlinear dynamical systems with SciPy and SBbadger in physical and biological regimes · Constructed an automated pipeline in Python that processed model prediction files, generated their counterparts in the known system, and produced fitted correlation plots with Pearson’s r without human intervention · Presented findings orally at the end-of-SULI symposium, and produced a research paper and general-audience abstract · Manuscript currently under peer review for a paper based on this research, as co-first author
Clover Chern-Simons With Lattice Gauge Theory Methods | Advisor: Dr. Joel T. Giedt · Began exploratory study for implementation of Monte Carlo simulation code in C++ for a non-Abelian Chern-Simons lattice gauge theory action in three spatial dimensions, using the clover leaf Yang-Mills field strength and updates through the Metropolis algorithm; such would represent a first-ever study of Chern-Simons theory with lattice methods
PHYS 1250 Introduction to Electromagnetic Theory · Worked with 20-30 students in weekly labs to ensure their completion of assigned work · Educated students in how to set up Jupyter notebooks and perform basic scientific tasks in Python · Hosted weekly office hours for students to receive help on laboratory work
Studying Effects of Large Magellanic Cloud (LMC) Gravity on Orphan Stream Simulations | Advisor: Dr. Heidi Jo Newberg · Used the Milky Way @ Home distributed computing software in order to compare and contrast the effects of new n-body simulation code meant to introduce LMC gravitational perturbations on simulations of galactic orphan streams · Synthesized previous research on matching simulated orbit tracks of the Orphan-Chenab stream with new methods developed in-group, working in Python · Presented findings orally at a formal group meeting, as well as completing an end-of-semester research paper
I-PERSIST Mentorship Program | PHYS 1100 Physics I · Taught common problems in introductory physics to upwards of thirty students, as well as exam-taking and study skills · Proctored practice exams and solved problems in review with students · Participated in weekly meetings to coordinate instruction curricula with other mentors and faculty · Aided in the transition of incoming freshmen to a rigorous college environment, socially and academically
Generating Cherenkov Ring Events with Neural Networks | Advisors: Dr. Chiaki Yanagisawa, Dr. Cristovao Vilela · Developed means for displaying the evolution of network accuracy via the machine learning method’s loss function · Discovered the locations of important milestones in the network’s learning and accuracy to experimental data · Analyzed trends in simulation output with respect to event energy and neutrino typing