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
Software Engineer
IIT-DB Group Research Lab | Python, PostgreSQL, AWS
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
Application Engineer
Hindustan Times (Four C Plus Internet Co. Ltd.) | Java, Spring Boot, REST APIs
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
Open Source Contributions
Microsoft C++ Standard Library (STL)
C++, Python, CMake
Microsoft
Microsoft C++ Standard Library (STL)
C++, Python, CMake
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
Spotify Backstage Framework
TypeScript, React, Node.js
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
Elastic UI
TypeScript, Chroma.js, CI/CD
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
Graduate Pathway Scholarship
Illinois Institute of Technology
Founding Member, ML Club @ IIT
Illinois Institute of Technology