Hi, I'm a recent graduate from NC State, where I was pursuing a Ph.D. in nuclear engineering.
My dissertation, which is on probabilistic circuit simulation, demonstrates that PRA models spanning millions of events can be quantified on consumer GPUs in a matter of seconds.
The research in one, a few, and not-so-few pages.
In 2024, I was part of a NCSU lead research effort that developed a limited-scope, pre-conceptual design PRA model for the Aalo Atomics microreactor, following the process defined in NEI 18-04.
I completed my Masters in August 2023, also in nuclear engineering.
During the summer of 2021, as part of my MS thesis, I interned at Idaho National Laboratory (INL), developing model checking tools for assessing the reliability of autonomous digital instrumentation & control systems for fission batteries.
Between 2018 and 2020, I worked as a PRA software engineer at The B. John Garrick Institute for the Risk Sciences, UCLA on a collaborative project with NASA's Jet Propulsion Laboratory (JPL), led by Dr. Ali Mosleh. I served as the PRA software development team lead for part of that time.
I completed my undergrad studies in 2017. Research was a big part of my undergraduate experience. I enjoyed working with grad students at UCLA SmartHealth, building cloud/edge machine learning tools for smartwatch-based health monitoring.
From 2014 through 2015, I worked on embedded systems research in Dr. Majid Sarrafzadeh's lab in the Computer Science department at UCLA.
Estimates probabilities for massive PRA models using GPUs. Handles rare-events using importance sampling.
A tensorflow-based tool for estimating functional event probability distributions in an event tree to match target end-state frequencies.
A collaborative, web-based PRA tool with advanced time-to-failure models, importance measures, and uncertainty quantification.