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Software Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Architecting and building complex software systems end-to-end.
University of Southern California
Bachelor of Science - BS, Computer Science and Informatics
January 1, 2018 – January 1, 2022
Jesuit High School
High School
January 1, 2014 – January 1, 2018
Amazon
Software Engineer
December 1, 2024 – Present
Redmond, Washington, United States · On-site
Intel Corporation
GPU Software Engineer Intern
January 1, 2021 – August 1, 2021
Hillsboro, Oregon, United States
Intel Corporation
Systems Software Engineer Intern
May 1, 2020 – August 1, 2020
Hillsboro, Oregon, United States
Legacy Health
Volunteer
June 1, 2017 – July 1, 2017
Legacy Research Institute
University of Portland
Environmental Studies Intern
June 1, 2015 – August 1, 2015
North Portland Area
National Museum of Education
National Director of the Student Board
April 1, 2015 – April 1, 2018
OHSU | Oregon Health & Science University
Programmer/Decoder for Brain Single-Cell Gene Expression Project
April 1, 2015 – April 1, 2017
Portland, Oregon Area
Oregon Chess Tutoring Company
CEO, Co Founder
June 1, 2013 – August 1, 2020
Portland, Oregon Metropolitan Area
Portland State University
Independent Researcher/Machine Learning
May 1, 2012 – May 1, 2018
Portland, Oregon Metropolitan Area
Web App, AWS Serverless Backend
February 1, 2023 – June 1, 2023
Led the development of a serverless backend, deployable with the AWS SAM CLI. Features implemented: Authentication, REST API, In-app Messaging, Image Storage, NoSQL Database.
Mobile App (Undisclosed)
December 1, 2022 – October 1, 2024
Tackling growing problems of social health and agency in the present era of mass information, social media, and entertainment. Strengthening bonds between people in both social & professional capacities.
ELC Resolve
August 1, 2022 – December 1, 2022
Developed a web application for the Experiential Learning Center of USC’s Marshall School of Business. Provides a platform to simulate conflicts and problems in the workspace and guides students to practice communication, work as a team, and reflect on how such issues may be handled in a real work setting.
A Novel Approach to Machine Learning Combining Classical Occam's Razor Learning with Vapnik's Modern Statistical Theory
September 1, 2016 – April 1, 2017
Approaches the classification problem from a new angle with a novel machine learning method, Hybrid Tree Classifier (HTC), that combines Occam’s Razor with VC Theory by first decomposing complex datasets into smaller subsets with Decision Trees before other methods are applied to these subsets. This addresses the critical problem of data being too large and complex to handle, while maintaining the fundamental principles of VC Theory.
A Novel Machine Learning Approach to Proteomics Analysis of HIV-1 Protease Interactome for Effective Combative Drugs Development
December 1, 2015 – April 1, 2016
The development of combative drugs for HIV-1 requires knowledge regarding the complex interaction between its protease and substrate. The specificity of the substrate was analyzed using machine learning methods. New, easily applicable rules were discovered, helping to enable HIV-Drug development and providing proof of concept for combative drug development in the medical field as a whole.
Mitigating Local Industrial Air Pollutant Movements by Monitoring Temperature Inversion Patterns in North Portland
June 1, 2015 – August 1, 2015
The purpose of this project is to develop a way to forecast temperature inversion patterns which would allow us to mitigate the movements of local air pollutants from industrial activities in the area, minimizing any harm done to the local population. Monitored weather conditions at different elevations in the North Portland area. Designed a way to collect data from flying a drone and/or weather balloon with a Kestrel sensor attached, enhancing the ability to detect and predict temperature inversions.
Performance of a Vegetated Roof with Xeric Species in Portland, OR
June 1, 2015 – August 1, 2015
Experimented with Xeric plant species on rooftops to develop the optimal green roof for the University of Portland. Won Murdock Poster Prize in Environmental Science
Development of A Novel Forest Fire Prediction Tool Utilizing Historical Data and Machine Learning Methods
May 1, 2014 – July 1, 2017
Developed a program in Python using the data mining and Machine Learning tool Orange for wildfire magnitude prediction. Studied machine learning methods: Support Vector Machines, Naive Bayes, Decision Trees, Disjunctive Normal Form. 98% accuracy yielded by Disjunctive Normal Form based method and 10 fire weather attributes.
Development of a Forest Fire Prediction Tool For the State of Oregon
May 1, 2013 – April 1, 2014
Developed a tool in Matlab using Support Vector Machines to predict the area burned by a given wildfire. Contacted American Meteorological Association for Historical Fire Weather Database of more than 20 years of wildfires. Integrated and performed statistical analysis on database to determine the most efficient method for forest fire prediction through the testing of various fire weather attributes and Support Vector Machines.
Cultural Fit Analysis
The candidate's background shows a strong inclination towards research, problem-solving, and leadership. The variety of projects, from environmental science to machine learning and web development, suggests a broad interest and ability to adapt to different domains. The experience at Intel and Amazon (future role) indicates a fit for structured, high-performance environments. The target role of 'Mobile Developer' is not directly supported by explicit mobile development projects or skills in the provided data, which might be a gap in cultural fit for a specialized mobile team.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical and research skills through numerous academic projects and internships. Leadership roles suggest initiative and responsibility. The diverse project portfolio indicates adaptability and a willingness to tackle varied challenges. However, specific communication skills cannot be fully assessed without an English test score or direct interaction data.