I'm currently a postdoc at Berkeley National Lab in the Machine Learning for Fundamental Physics group.
I use machine learning for data deconvolution, differentiable detector design, and generative modeling .
I earned my PhD in Physics from UC Berkeley working in experimental Nuclear and High Energy Physics as a member of the ALICE experiment at CERN.
I love lifting, technology, design, and comedy.
I am currently a postdoctoral research fellow in the machine learning for fundamental physics group, led by Benjamin Nachman. I work on detector data deconvolution, differentiable detector design, and generative modeling for collider data. I collaborate on projects at the intersection of physics and deep learning. Joint work focused on training Generative score based diffusion models to speed up High Energy Physics simulation.
I conducted my PhD research as a member of the ALICE collaboration at CERN. I worked on identifiyng "deep photons" where we used modern ML techniques to identify direct photons produced in the initial hard scattering. My physics analysis was focused on studying parton fragmentation by measuring isolated $\gamma$-hadron correlations in pp and p–Pb collisions
I spent five years at UC Berkely working with the relativistic nuclear collider group at LBNL. My advisor was the wonderful Barbara Jacak. I developed software for a blazingly fast data correction framework and data processor for storing data at LBNL. I was a teaching fellow for two years, followed by a Nuclear Science and Security Consortium fellow for two years. I spent a summer at Livermore national lab working on jet callibrations for sPHENIX. In my last year, studied potential of jet measurements at the future Electron Ion Collider.
I graduated from Stony Brook in 2016 with a major in Physics. During my undergraduate studies, I worked across different research fields, including Ring Imaging Cherenkov Detectors, Time Projection Chambers, PHENIX data analysis of Pi-zero backgrounds, and PHENIX pre-shower detector manufacturing.
I teach machines using:
PyTorch, Keras, and TensorFlow.
I often write in: ,
,
,
and $\LaTeX$ .
I sometimes program in:
,
Lua,
LabView, and ROOT.
is awesome.
Thorough knowledge of:
Group Theory, Field Theory,
Linear Algebra, Calculus,
Statistics, and Data Analysis
from academic coursework and
research experience.
Effective Communication, Active Listening,
Mentoring, Onboarding,
Resilience, Critical Thinking.
Would you like to know more about my skills and experience?
Feel free to contact me via email or follow me on social media using the links below.