Select Publications
EG3D: Efficient Geometry-aware 3D Generative Adversarial Networks
November 2021
Co-first author
Submitted to a top ML/Vision conference
Created in collaboration with Stanford PhD candidates and NVIDIA
computer vision researchers
Work Experience
Computer Vision Researcher
Stanford Computational Imaging Lab
2021
Stanford, California
Published EG3D, as seen above
Focus primarily in the field of 3D-aware generative models,
specifically GANs and probabilistic diffusion
Design, implement, train and test complex models including
classifiers, autoregressive models, transformers, diffusion models, and generative
adversarial networks
Read, analyze, interpret, and implement state-of-the-art technical
research papers
Software Engineering Intern
NASA-Caltech Jet Propulsion Laboratory
2019-2020
Pasadena, California
2nd year: Designed and built a monte-carlo based terrain
simulation API currently used by mission planners to evaluate risk functions of autonomous
rover navigation based off orbital terrain data
1st year: Collaborated with active Mars Rover Sequencing and
Simulation teams; used Docker and Amazon ECS to upgrade, extende, and migrate robotic
simulation and computational systems to cloud servers via REST APIs
Galaxy Summer Camp LLC Founder
Galaxy Robotics LLC
2012-2018
SF Bay Area, California
Taught robotics and programming to 1300+ students with ages ranging from grade 4 through grade
12
Gross revenue from $0 to $340,990 over 6 summers
Hired and trained 12 independent counselors
Developed comprehensive curriculums for all experience levels of
robotics and programming classes
Education
Mathematics, B.S.
University of Maryland,College Park
2018-2021
Major GPA
3.94
/ 4
Computer Science, B.S.
University of Maryland,College Park
2018-2021
Major GPA
3.89
/ 4
Technical Skills
Well-Versed Languages
Python
SQL
C
elixir
Java
OCaml
C++
HTML/CSS
Technologies
Pytorch / Tensorflow
Linux / Unix
MySQL
Tableau
GANs
Jenkins CI
AWS / ECS
Docker
Flask / gunicorn
Course Highlights
Dynamic Programming, Algorithm Analysis & Optimization
Advanced algorithms I, II
Linear Systems, SVD & Jordan Decompositions
Theoretical linear algebra I, II
Probability Theory
Number theory I, II & Combinatorics & Statistics
Search Algorithms, ML, Neural Networks & Reinforcement
Learning
General AI & Computer vision
Computer Security & Encryption Techniques
Computer Security I & Cryptography
Logic & Optimization
Real Analysis I, II