Arup Chauhan

Arup Chauhan

MSCS, Software Engineer & Researcher

About Me

Pursuing an MS in Computer Science from Illinois Institute of Technology, where I am currently part of the IIT-DB Group Research Lab. My work focuses on optimizing database queries using Machine Learning and Deep Learning to improve efficiency and performance in data-driven systems.

My experience includes developing backend systems that process large amounts of data efficiently, improving how data is stored and retrieved, and ensuring applications run smoothly on cloud platforms.

I focus on designing fast and reliable systems, building APIs, and making databases work more efficiently. I also have experience in full-stack development and actively contribute to open-source projects like Microsoft STL and Spotify Backstage to improve enterprise grade codebases.

Outside of work, I enjoy following footwear tech and reading about culinary history, as well as cooking and music.

Experience

Software Engineer

IIT-DB Group Research Lab | Python, PostgreSQL, AWS

Chicago, IL
May 2024 - Present

Working on optimizing how databases execute queries by using machine learning to predict better execution strategies. This involves training models to analyze past query patterns and adjust execution paths dynamically for improved efficiency.

Building and deploying cloud-native pipelines that integrate with PostgreSQL systems, automating decision-making for complex queries. The goal is to make databases self-optimizing, reducing manual tuning and allowing them to handle unpredictable workloads more effectively.

Application Engineer

Hindustan Times (Four C Plus Internet Co. Ltd.) | Java, Spring Boot, REST APIs

New Delhi, India
Jul 2018 - Apr 2022

Designed and maintained backend services for a high-traffic digital publishing platform, implementing scalable microservices architecture using Java and Spring Boot. Focused on improving request handling, database interactions, and API reliability to support millions of users.

Developed and optimized RESTful APIs for content ingestion and distribution, implementing authentication layers with OAuth2 and JWT. Refactored legacy services to improve database query efficiency, reducing system load and enabling faster content retrieval across distributed systems.

Education & Skills

Education

Master of Science - Computer Science

Illinois Institute of Technology | Chicago, IL

Bachelor of Technology - Computer Science & Engineering

Dr. A.P.J. Abdul Kalam Technical University | Lucknow, India

Skills

Python
Java
C++
Golang
TypeScript
JavaScript
Flask
Django
Node.js
React
Next.js
PostgreSQL
MySQL
AWS RDS
MongoDB
Firebase
Amazon DynamoDB
Docker
Kubernetes
AWS
GCP
Azure
Git
GitHub
CI/CD
Microservices
SDLC
TDD

Open Source Contributions

Microsoft

Addressed memory leaks in thread management within embedded C runtime library. Optimized flat_map and flat_set for code conformity.

Spotify Backstage Framework

TypeScript, React, Node.js

Backstage by Spotify

Implemented search functionality to enhance user discoverability. Fixed navigation flow by improving routing context in distributed setups.

Elastic UI

TypeScript, Chroma.js, CI/CD

Elastic

Developed a shared utility for color contrast logic in Elastic UI, ensuring accessibility improvements across EuiAvatar and EuiBadge components.

Projects

Golang, MySQL, Redis, Docker

Engineered a real-time notification system with event-driven messaging using Redis and MySQL. Implemented an efficient pub-sub architecture to ensure low-latency event propagation while maintaining consistency across distributed services.

Python, Django, Scikit-Learn, MongoDB, AWS

Built a focused search engine leveraging TF-IDF and Scrapy for automated data indexing, enabling scalable real-time querying. Integrated AWS services for CDN-based distribution, optimizing API response times and search efficiency.

JavaScript (React), Node.js, Redis, Docker

Developed an adaptive route optimization system using Dijkstra’s Algorithm, enabling real-time, high-performance path computations. Leveraged Redis for in-memory caching to achieve instant re-routing with minimal computation overhead.

C++, Qt Framework

Designed a Qt-based image processing tool to enhance OCR efficiency by analyzing dark pixel density and connected components. Enabled robust document preprocessing and feature extraction for downstream text recognition tasks.

Achievements

Dan Kohn Scholarship

The Linux Foundation

2024

Graduate Pathway Scholarship

Illinois Institute of Technology

2023

Founding Member, ML Club @ IIT

Illinois Institute of Technology

2023