I recently finished my MS in Computer Science & Engineering. I dabbled in market design during my first programming job and later my first publication regarding front-running in decentralized exchanges on blockchains. My undergraduate background was in Computer Engineering with an emphasis in robotics and for a while I was consumed with robotic tinkering (i.e drones/AVs). This led me grad school under the assumption I would pursue robotics + reinforcement learning, but my focus switched towards security/privacy after learning about the potentials of blockchain. My interest now is in verifiable computing which is the focus of my PhD. I use Chisel to build open source software libraries that generate hardware accelerators for expensive cryptographic operations (i.e Fully Homomorphic Encryption and Zero Knowledge Proofs). My research involves prototyping in Python and then designing hardware generators in Chisel/Scala to target FPGAs. My MS thesis was on building a Number Theoretic Transform hardware accelerator for the expensive polynomial operations used in many cryptographic primitives. I consider myself lucky because Chisel enables Agile hardware development, meaning I get to practice software engineering skills while designing hardware. I am very grateful that I get the opportunity to research target domains outside of my direct field when designing hardware accelerators. I enjoy teaching and have TA'd for the undergraduate Computer Architecture course at UCSC for multiple quarters. Other interests involve Automatic Theorem Provers, deep RL, quantum computing, cellular automata, and using Jupyter Notebooks for everything I can.