Ph.D. Computational & Data Sciences (Schmid College of Science and Technology)
University of California, San Diego
B.S. Physics w/ Specialization in Computational Physics; Minor in Computer Science
Los Gatos Research
Control Systems Engineer
Design, simulation, development, programming, and construction of sensitive control system modules for high-performance applications. Worked with the designing of hybrid Analog-Digital systems. Acquired experience in seeing through a complex engineering project from start to finish.Jun '13 to Sep '13
Los Gatos Research
Full-Time Scientific SBIR Research
Team member in multiple Small Business Innovation Research (SBIR) groups; full-time position in numerical computation, modeling and analyzing complex non-linear systems. Worked in embedded systems programming, deployment, and stress testing. Acquired comfort in a research environment with its goals and deadlines.Jul '12 to Sep '12
Harbor Church College Ministry
Core Leadership/Logistical Coordinator
Practical experience in positions of head leadership over a large student organization. Dealt with working with and leading diverse teams, effective listening, and complex logistical coordination, and strategies for effective communication.Sep '11 to Jun '12
UCSD Department of Physics
Back-end Testing Consultant
Offered consulting services for the construction of regression testing system for the scheduling manager and interface for a massively parallel grid computing network.Sep '10 to Feb '11
Nexa Technologies, Inc
Quality Assurance Division Intern
Assisted with the architecture and implementation of a large-scale automated regression testing framework. Tackled practical issues of scaling, research and integration of software libraries, and working with large teams, as well as sheer amounts of heavy scripting and programming.Oct '09 to Apr '10
- Hands-on Experimental Lab Work
- Computational Modeling
- Nonlinear Optics
- Circuit Design/Fabrication
- Object-Oriented Design
- Server Administration
- Artificial Neural Networks
- Hidden Markov Models
- Bayesian Probability Networks
Monophonic Analog Synthesizer
Musical synthesizer, with adjustable and modular low-frequency oscillator, built from scratch with fundamental/simple circuit components (resistors, capacitors, tansistors, and operational amps). Could proudly carry a decent tune.
Machine Learning / Clustering
Applying physical models to generate visualizations of complex multi-dimensional relational graphs as projections onto a two-dimensional mapping, based on self-organizing emergent principles, and recovering distinct clusters from the data.
Machine Learning / Neural Networks
Neural Network-Based AI Game Player
A modular construct/system for applying principles of Artificual Neural Networks to different games — of both deterministic/non-deterministic and perfect/imperfect information varieties.
Strong ethic of accountability, integrity, self-drivenness and perseverance, eagerness to learn and acquire new skills, developed problem-solving mindset, adaptability.
Experience with high- and low-level programming, scripting, dealing with people, constantly changing and irregular work environments, simulations and modelling, short deadlines
Phys 120A, Phys 121
Practical Electronics and Experimental Techniques
Working with technologies such as LabView; experience with circuit design and construction; learned practical design principles of PID feedback systems and control theory.
Computational and Mathematical Physics
The theory of differential equations and practical knowledge of numerical computation necessary for working with advanced physical theory and application.
Artificial Intelligence and Machine Learning
Expansive coverage of the ongoing fields of research in Machine Learning, including in-depth study in construction, training, and applications of Hidden Markov Chains, Bayesian Networks, and Artificial Neural Networks.
Numerical Analysis, Matrix Computation & Computational Theory
Explored the theory and limits behind numerical computation; studied current advanced numerical methods and algorithms for optimizing large-scale scientific computing.
Statistical Mechanics and Thermodynamics
Advanced understanding of stochastic and thermal ensembles, emphasizing interdisciplinary applications in information theory and computational methodologies.