Overview

I am currently a software engineer at Cisco Systems in San Jose, CA. I graduated from Arizona State University with a B.S in Computer Science in 2019. I primarily work on backend web development but also have experience in machine learning. Outside of my career, I enjoy stand up comedy, traveling, and making new friends!

Current Job

Cisco Systems Software Engineer Full time (2019 - Present)

After Graduating from college, I joined Cisco as a fulltime software engineer on their Customer Experience Machine Learning team. I work on a team that is a building a No-Code platform that enables users to develop chatbots capable of complex conversations. Working here, I have developed a deep understanding of distributed systems, deploying highly scalable machine learning models in production environments, and RESTful API development. I use python, java, elasticsearch, rasa, keras, docker, and kubernetes extensively in my day-to-day activites.

Past Experiences

Cisco Systems Software Engineer Intern (2018 - 2019)

I first joined Cisco during my junior year summer. Over the summer I developed a machine learning pipeline that enabled data scientists to run four different classifier models over any numberical or text-based datasets. The pipeline would run traditional data-cleansing techniques and store the results of the classification models into a database. I also developed a polynomial regression model that enabled my team to predict the average labor cost for installation of Cisco hardware in various client facilities. This experience exposed me to various machine learning techniques and enabled me to contribute to production-grade applications that had millions of users. These projects eventually led to me being offered a full time role on my team.

Nationwide Insurance Undergraduate Computer Science Researcher (2018 - 2019)

For my undergraduate capstone project at Arizona State University, I led a team of seven students to work with Nationwide Insurance to develop an application that predicted forest-fire prone regions across California. Our team developed a unary classifier that could predict the likelihood of a forest-fire for a particular longitude-latitude coordinate in California with a 70% accuracy. We also developed a web application that enabled Nationwide field engineers to interact with our model.

Symphony Health Solutions Software Engineer Intern (2017 - 2018)

During my sophomore year summer I interned at a startup which got acquired by Symphony Health Solutions. Here worked on developing a webscraper that collected and indexed data on millions of doctors across the United States. Working at a startup enabled me to have complete control over my product. I learned an immense amount of knowledge on common web scraping techniques, RESTful API development, python, and unit test cases. This experience solidified to me that I wanted to become a software engineer.

Education

Arizona State University B.S Computer Science (2015 - 2019)

I got B.S in Computer Science from Arizona State University. As a part of my major I took fundamental software engineering courses such as data structures and algorithms, database management, artificial intelligence, theortical computer science, statistics and probability, and discrete mathematics. I also tried to be an active part of the school by joining various clubs. I joined the software development club (SODA), the exploration and development of space club (seds), and even tried my hand in the comedy club.

Undergraduate Thesis

For my undergraduate thesis, I worked with Professor Heni Ben Amor to research the use of LSTM networks to generate song lyrics in the style of different artists. We also determined whether LSTMs could be used for the classification of songs by genre. This experience exposed me to implementing machine learning techniques from scratch. I was also exposed to traditional data cleansing techniques. More information on my thesis can be seen here.

Publications