Aarav Makadia 👋

I'm a Computer Science Student at Rutgers University - New Brunswick! If you have any questions, interests, or just want to connect, don't hesitate to shoot me an email!

My research interests encompass Broad AI (Reinforcement ML, Robotics, DL), Statistics and Data, IoT and Autonomy, and Economics/Business in AI! I have had the privilege of working with esteemed academics at Harvard Business School, Northwestern Kellogg School of Management, and The Wharton School!

Currently, my research is jointly funded by the National Science Foundation, and Rutgers School of Engineering :)

• Software Engineer/Python Code Reviewer 👨‍💻

  Bloomberg LP

  January 2024—Current

  Worked on Technology Infrastructure: Training and Documentation/Developer Solutions • Conducting in-depth code reviews in Python, C, C++, BAS, and Comdb2 projects created by Entry-Level Software Engineers, ensuring code correctness, adherence to industry best practices, and compliance with language-specific style conventions. • Providing mentorship and continuous feedback to entry-level trainees during their Python and C training, focusing on enhancing their programming skills, improving code quality and concision, and advancing their understanding of low-level programming concepts. • Engaging in firm-wide product support and development in Python, BAS, R+, and Comdb2, addressing critical issues and improving system stability for 5+ engineering training and technology infrastructure teams.

• Software Development Engineer (Jr. SDE) 👨‍💻

  Amazon.com

  February 2024—Current

  Worked on Amazon Kindle/Books: ComiXology (Worldwide Comics at Amazon) • Implementing advanced logic in Java, TypeScript and C to reconfigure book filter system for the public global Amazon comics store and refine filter functionality and improve accessibility and navigation. • Performed integration testing, pipeline maintenance for comics store environments to production. • Led Java and TypeScript code deprecation plans to clean up amazon.com/comixology codebases, affecting 15+ internal team workflows.

• Machine Learning Engineering Intern 👨‍💻

  Bloomberg LP

  July 2024—September 2024

  Worked on Artificial Intelligence Research Group: Communications, Repos and Intent • Applied Python, Scikit-learn, Pandas, Numpy, Matplotlib, and R to reconfigure and cleanse 4+ dataset re-annotations into a singular four-way classification data source for intent behind messages within Bloomberg Terminal. • Evaluated refined data source against BiLSTM model and client rules to analyze performance statistics and train neural network on four-way classification dataset with less labeling. • Improved usability and support across 5+ internal AI teams, addressed product negligence with 2+ internal clients, and promoted sales across 4+ external clients.

• Louis Stokes Research Scholar 🔬

  National Science Foundation

  September 2023—June 2024

  Worked on Artificial Intelligence Aided Next Generation Intelligent Transportation Systems under Prof. Xiang Liu • Employed Python, data processing tools, and statistical analysis to dissect extensive datasets related to AI applications in transportation, with a primary focus on harnessing NJ Transit data. • Innovatively devised methodologies to derive novel insights, enhancing the efficiency and effectiveness of next-generation transportation systems. • Played a pivotal role in generating strategic findings aimed at revolutionizing the transportation industry.

• Software Engineer Intern 👨‍💻

  Bloomberg LP

  May 2023—August 2023

  Worked on Markets, Community, and AI: Insights Framework Team • Employed Python, Jenkins, Groovy, and YAML to craft automated sandbox testing environments for insight generation. • Utilized Comdb2/SQLite databasing in tandem with Python and Jenkins to optimize sandbox deletion and automate sandbox configurations within Bloomberg's RapidUI front-end framework. • Led initiatives to boost sandbox adaptability, which expedited insight deployment and elevated performance for over 20 internal teams, serving 300k+ global clients.

• Software Engineer Intern 👨‍💻

  Bloomberg LP

  May 2022—August 2022

  Worked on Markets, Community, and AI: Insights Framework Team • Utilized Python, Node.js, SCSS, and YAML to build a strong data model through dynamic webpages on Bloomberg Insights Platform. • Managed version control via BBGitHub/Git and efficiently handled Linux CLI, ensuring smooth collaboration and code maintenance. • Designed scalable distributed systems with Comdb2 databasing and Python, integrating web visuals into Bloomberg's RapidUI front-end. • Boosted BLP Terminal's data performance by enhancing visualizations for mill and insight dependencies, benefiting a global 300k+ client base.

• Research Assistant 🔬

  Harvard Business School

  January 2023—September 2022

  Worked under HBS Finance Unit Faculty Member • Used R to reconstruct statistical algorithms, compiling data from a dataset of more than 300 case documents. • Utilized R for analysis, drawing significant conclusions from the study focused on consolidated harassment-based arbitration settlements within a securities organization. • Assumed a leadership role in executing data cleaning, feature engineering, and statistical analysis using R, showcasing adeptness in processing and extracting essential insights from a varied dataset.

• Research Assistant 🔬

  The Wharton School

  December 2020—December 2021

  Worked under Wharton Operations, Information and Decisions Faculty Member • Applied a linear classifier, Reinforcement Machine Learning, and Python with Soft Vector Margin (SVM) to investigate behavioral decision-making in an inmate trial appearance study. • Conducted cross-referencing of pertinent academic papers on decision-making to rederive the SVM equation, incorporating characteristic variables such as age, racial background, sentence type. • Utilized Python and SVM in the context of a study focused on inmate trial appearances, enhancing the understanding of behavioral decision-making processes.

CS 111 Intro to Computer Science (Java), CS 142 Data 101 (R), CS 112 Data Structures (Java), MATH 250 Linear Algebra, CS 211 Computer Architecture (C), CS 205 Discrete Structures I, CS 214 Systems Programming (C), CS 210 Data Science for Data Management (R)

• Java
• Python
• TypeScript
• JavaScript
• Node.js
• React Native
• Next.js
• Jenkins
• SQLite
• React.js
• Node.js
• CSS
• Flask
• Google Cloud
• R
• Docker
• NPM
• R Studio
• Vim
• Git
• PostgreSQL
• MongoDB
• AWS
• Bash
• Figma