Arkin Gupta
arkin dot gupta at gmail dot com

I am a second-year undergraduate at UC San Diego pursuing a Bachelor of Science in mathematics and computer science. I'm specializing in machine learning, mathematical finance and statistics/probablity.

I am a member of the Mathematical Neuroscience lab advised by Gabriel Silva, where I am researching adaptive and dynamic neural networks. This summer, I'm interning at CareFusion BD as a data scientist working on time-series forecasting and machine learning models.

Blog  /  CV  /  GitHub  /  LinkedIn





News

•   August 2017: Started my technical blog - I'll be writing about machine/deep learning, neural networks, algorithms and math.
Experience
CareFusion BD (Becton Dickinson)
Data Scientist Intern
San Diego, CA • June 2017 - September 2017

Developed time-series forecasting, machine learning models to predict drug shortages, and price changes. Effectively analyzed and visualized datatsets with more than 10 Million drug usage and transaction records. Used dimension-reduction techniques (PCA, SVD, LDA), fourier and log transformations and resampling techniques (bagging, boosting) to identify correlations between variables and extract underlying patterns of the data. Worked with multiple regression and classificatoin models - linear models, ARIMA, boosted trees (xgboost), random forests and SVMs.

UCSD Computer Science & Engineering Department
Tutor / Undergraduate Teaching Assistant
La Jolla, CA • April 2017 - Present

Tutor for Object-Oriented Programming (CSE 11). Worked with the instructor to design and write programming assignments and their specifications. Held office hours and led review sessions to explain programming concepts and assist students in implementing programming assignments by analyzing and debugging their code. Graded homework, exams and wrote submission/grading scripts for programming assignments.

Learning Equality
Software Engineer Intern
La Jolla, CA • January 2017 - March 2017

Wrote python scripts to setup a Continuous Integration server to automate package builds. Developed multiple native Linux (Ubuntu, CentOS, Debian) packages using bash and python for Kolibri - Learning Equality's flagship application. Optimized software setup on all platforms by implementing efficient installation scripts.

Center for Cyber-Archaeology @ UCSD
Software & Database Developer
La Jolla, CA • November 2016 - February 2017

Developed a user-friendly, sustainable web-application for processing and storage of archaeological data. Implemented multiple features in Ruby on Rails, including auto-complete site search and backups. Worked extensively with legacy code, debugged JavaScript bugs and re-factored the SQL database.

Research

My reserach interests include statistical machine learning, stochastic processes, non-convex optimization and neural networks. In particular, I'm interested in research applicable to computer science, finance, economics, robotics and neuroscience.
Center for Engineered Natural Intelligence (Mathematical Neuroscience lab)
Undergraduate Research Assistant

Developing neural derived and neuromimetic (i.e. neural imitating) algorithms for non-biological engineered systems. Currently researching data assimilation training methods for dynamic and adaptive neural networks. Applying non-linear transfer functions between neurons and layers to create complex dynamic geometric networks.

Projects

Open-source, group projects I worked on at hackathons and for courses.
Gentrification in San Diego - Analyzing negative effects of gentrification in San Diego
May 2017 • Final project for UCSD COGS 108 (Data Science in Practice)

Analysis of the negative effects of Gentrification in San Diego in the 21st Century. Visualized the change in demographics of all neighborhoods in San Diego using heat maps. Identified neighborhoods effected the most by Gentrification and found patterns between multiple socio-economic factors such as Poverty, Population, Uninsurance and Property value. Languages/Tools Used: Python (Pandas, NumPy, Matplotlib, Patsy), Jupyter Notebooks.

SentiMedia - Sentiment analysis for YouTube comments
April 2017 • Honorable Mention - HackTech, California Institute of Technology

Data science powered web application to perform sentiment analysis on YouTube comments. Applied machine learning techniques on the model using a training dataset of 1 Million tweets. Wrote python scripts for web scraping and performing sentiment analysis on the comments. Languages/Tools Used: Python, Natural Language Toolkit, Flask.

Intersect - Mobile app to unify connecting with people on multiple social media
November 2016 • NEC Sponsor Prize - CalHacks, UC Berkeley

Android application to ease the process of connecting with people on multiple social media. Integrated database, added Location tracking and developed the app structure. Languages/Tools Used: Java (Android), XML, Google Firebase.

Trivents - Web application to attend and create location-based events
October 2016 • DocuSign Sponsor Prize - SDHacks, UC San Diego

Web application to pull and display events from Facebook & Eventbrite based on location and time. Developed unique QR generation, routing, sorting of events and designed the UI. Languages/Tools Used: JavaScript, HTML/CSS, MongoDB.

Teaching Assisting / Tutoring
UC San Diego

CSE 11 - Object-Oriented Programming
UC San Diego, Spring 2017

Selected Coursework   (at UC San Diego)



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Website cloned from here.