Overview
I am a creative thinker, who is always eager to learn new technologies, tools and approaches, research new concepts, and become better at what I do. I am a team-player and I like to be constantly challenged. I have strong problem-solving, analytical, communication, and presentation skills. I like working in a supportive and innovative environment, where I can impact many people positively through my work. I appreciate workplaces that are welcoming and open-mindedness to diversity.
I graduated with a Bachelor's degree in Computer Science from Columbia University in the City of New York in May 2020 and am a Software Engineer. I worked full-time throughout my education at Columbia University, which shows how hard-working I am.
I graduated with a Bachelor's degree in Computer Science from Columbia University in the City of New York in May 2020 and am looking for a software engineering, product management, project management, or technical account management opportunity. I worked full-time throughout my education at Columbia University, which shows how hard-working I am. As a United States citizen, I am also eligible for government jobs.
Technical Skills:
- Python, Go, Ruby, JavaScript, Node.js, React, Amazon Web Services (AWS), HTML/CSS, Django, Flask, NLTK, TensorFlow, PyTorch, Keras, Pandas, Numpy, Scipy, Java, C, C++, NoSQL, MongoDB, Redis, Git, Spark, Flink, Docker, Kubernetes, Swift
Education
Columbia University in the City Of New York
Bachelor of Arts, Computer Science (September 2015 - May 2020)
Coursework
- Artificial Intelligence in Python; Natural Language Processing in Python; Advanced Programming in C/C++; Algorithmic Trading in Python (audit); Data Structures in Java; Cloud Computing and Big Data with Amazon Web Services in Python, JavaScript, HTML/CSS; Introduction to Cryptography; Fundamentals of Computer Systems; Linear Algebra; Building a Technology Startup; Computer Science Theory
Projects
Full-Stack Live Calculator Web App with AWS Beanstalk, AWS CodePipeline, Node.js, and Socket.io
(October 2020 - October 2020)
- Real-Time App: Created live calculator app that can be accessed from any browser and by any number of users to perform calculations and store last 10 calculations visible by all users in real time.
- Front-End and Back-End: This web app uses Node.js, Pug, and CSS for front-end, and Socket.io and Express for back-end. It also uses AWS Elastic Beanstalk along with AWS CodePipeline for deployment.
Node.js Miscroservices in Service Oriented Architecture
(June 2020 - July 2020)
- Node.js: Created a distributed system architecture with Node.js, delegating responsibility for various tasks to separate applications and to communicate between services
- REST APIs: Applications communicated with each other by exposed REST APIs, manipulating only the data it is responsible for and could be maintained, extended, and deployed without involving the other service
Artificial Intelligence in Python
(January 2020 - May 2020)
- Machine Learning: implemented Perceptron, Linear Regression, Clustering Machine Learning algorithms for data separation, prediction, and RGB values
- N-Puzzle Board Game: Implemented and compared breadth-first, depth-first, A-star search algorithms
- Sudoku: Implemented backtracking search with minimum remaining value heuristic to reduce variables domains
- 2048-Puzzle Game: Implemented an adversarial search agent to play using expectiminimax and alpha-beta pruning
Advanced Programming in C and C++
(January 2020 - May 2020)
- Web Server: Wrote HTTP 1.0 web server that served static HTML and image files
- Generic Singly Linked: Implemented a generic singly linked list that could hold any data type
Algorithmic Trading in Python
(September 2019 - December 2019)
- Model-Based Trading: Implemented model-based trading, execution strategies with market data, tolerance functions, factor models
- WRDS Tick Data Redux, VWAP Algorithm, Lee Ready Algorithm: Worked on WRDS Tick Data Redux, VWAP algorithm, Lee Ready algorithm, transaction cost analysis, risk factors, and roll model to reduce risk and increase predictability and profit
Cloud Computing and Big Data with Amazon Web Services in Python, JavaScript, HTML/CSS
(September 2019 - December 2019)
- Dining Concierge Chatbot: Implemented Dining Concierge chatbot, a serverless, microservice-driven web application, which sent users restaurant suggestions given a set of preferences provided to the chatbot through conversation
- Smart Door Authentication System: Implemented a Smart Door authentication system using Kinesis Video Streams and Amazon Rekognition to build a distributed system that authenticated people and provided them with access to a virtual door
- Photo Album Web Application: Implemented a photo album web app, searchable using natural language through both text and voice. Used Lex, ElasticSearch, and Rekognition to create an intelligent search layer to query photos for people, objects, landmarks, etc.
Natural Language Processing in Python
(May 2019 - July 2019)
- Trigram Language Model: Implemented a trigram language model to extract, count, and obtain raw probabilities for n-grams
- CKY Algorithm: Implemented CKY algorithm for CFG and PCFG parsing and retrieved parse trees from a chart with tree data structures
- Neural Network: Trained a feed-forward neural network to predict transitions of an arc-standard dependency parser with TensorFlow
- Lexical Substitution Task: Worked on a lexical substitution task, using both WordNet and pre-trained Word2Vec word embeddings with NLTK
Experience
- Help digitize thousands of tenancy agreements from office visit paper-signing to online digital signing via DocuSign
- Write thousands of rental verification letters as a landlord for current and previous tenants to help them get housing
Itemize Corp.
Software Engineer Intern (February 2013 - September 2013) New York, New York
- Collaborated with Product Manager, ML Engineer, Front-End and Back-End Engineers to come up with algorithms to parse various details such as vendor category, amount, currency, location, and business name from over 100,000 customer receipts and other financial documents in formats from over 100 countries using Python and Machine Learning
- Queried over 1,000 financial records every week with SQL and Amazon RDS in Python for rapid access through phone apps
Volunteer Activities
LGBT Mentorship Program, Columbia University
Mentor (January 2017 - Present)
- Mentored incoming LGBT Columbia students to help them use maximum resources and be successful
End of Resume
