About me

I am a passionate and results-driven Computer Science Graduate Student at the New Jersey Institute of Technology, specializing in Big Data, Cloud Computing, and Machine Learning. With a strong foundation in software engineering and hands-on experience in building scalable systems, I thrive on solving complex problems and leveraging cutting-edge technologies to deliver impactful solutions.


Currently, I am working as a Graduate Research Assistant, where I design and optimize Hadoop-based pipelines to process and analyze massive datasets, achieving significant improvements in data aggregation efficiency and cost savings. My expertise spans across AWS, Docker, Kubernetes, and distributed systems, enabling me to architect robust, cloud-native applications.


Previously, as a Deputy Manager - Software Engineer at Jio Platforms Limited, I led the automation of CI/CD pipelines, containerized legacy systems, and architected serverless microservices, resulting in improved system performance and operational efficiency. My ability to collaborate across teams and mentor peers has consistently driven success in fast-paced, Agile environments.


I am deeply passionate about open-source contributions, hackathons, and continuous learning. Whether it’s building a personal finance tracker, optimizing vehicle routing algorithms, or developing secure password managers, I enjoy tackling challenges that push the boundaries of innovation.


When I’m not coding, you can find me solving puzzles, participating in hackathons, or exploring the latest advancements in technology. I’m always eager to connect with like-minded professionals and collaborate on exciting projects.


Let’s build something amazing together!

What i'm doing

  • design icon

    Cloud Solutions Architect

    As Cloud Solutions Architect, I am deeply passionate about designing and implementing scalable, secure, and cost-effective cloud solutions. With hands-on experience in AWS, Docker, Kubernetes, and serverless architectures, I specialize in building cloud-native applications that drive efficiency and innovation. Whether it’s migrating on-premises systems to the cloud, optimizing infrastructure, or automating CI/CD pipelines, I thrive on solving complex challenges and delivering impactful results. Let’s architect the future of cloud computing together! ☁️🚀

  • ML icon

    Machine Learning

    Being ML Enthusiast, I excel in technologies such as TensorFlow, Keras, and Python to design, implement, and maintain robust machine learning models. I specialize in supervised and unsupervised learning processes, ensuring efficient model training, validation, and deployment, contributing to the creation and maintenance of scalable and reliable AI systems.

  • SD icon

    Machine Learning

    As software developer, I am responsible for designing, coding, testing, and maintaining software solutions, ensuring efficient and reliable mainframe in alignment with business requirements.

5G R&D Software Engineering @Jio Platforms Limited

Resume

Experience

  1. Graduate Research Assistant @ New Jersey Institute of Technology

    January, 2024 — May, 2024 (5 Months)

  2. - Engineered Hadoop-based pipelines to process and analyze 10+ TB of research datasets, implementing MapReduce workflows to improve data aggregation efficiency by 35%.
  3. - Leveraged Hadoop Ecosystem tools (Hive, Spark) to build scalable machine learning models, reducing prediction latency by 25% while maintaining 99% accuracy in cross-validated results.
  4. - Migrated on-premises Hadoop clusters to AWS EMR (Elastic MapReduce), cutting computational costs by 20% and enabling seamless integration with S3 for terabyte-scale storage.

  5. Deputy Manager - Software Engineer @ Jio Platforms Limited

    June, 2022 — August, 2023 (1.3 years)

  6. - Automated Jenkins pipelines for Kubernetes deployments, achieving 99.9% uptime and reducing post-deployment bugs by 20% via Selenium/JUnit test suites.
  7. - Containerized legacy 4G monitoring tools using Docker, accelerating migration to cloud-native 5G infrastructure by 2 months.
  8. - Architected a serverless microservices solution (Spring Boot, AWS Lambda) with Redis caching, reducing API response times by 40% and data extraction time by 35% through query optimization.
  9. - Engineered RESTful APIs to handle 5K+ concurrent requests/sec using connection pooling and Redis caching, improving geo-location accuracy by 5 meters for 10M+ users.
  10. - Collaborated with network engineers to resolve infrastructure bottlenecks via data-driven analysis, boosting operational efficiency by 18%.
  11. - Mentored engineers on Agile/DevOps practices, improving sprint velocity by 15% and reducing onboarding time by 50%.

  12. Frontend Development Intern @ FindMind Analytics

    March, 2021 — May, 2021 (3 Months)

  13. - Modernized 10+ legacy UI modules using Webpack (lazy loading, asset bundling) and integrated Firebase for authentication/real-time storage, reducing page load time by 25% and backend latency by 30%.
  14. - Developed a dynamic dashboard with RESTful endpoints and Chart.js, enabling real-time tracking of 500+ legal cases and cutting data retrieval time by 40% through optimized API design.
  15. - Delivered frontend milestones 2 weeks early in a 4-member Agile team, accelerating product launch by 15% while ensuring cross-browser compatibility for 1,000+ users.

My skills

  • Java
    80%
  • Python
    80%
  • Machine Learning
    70%
  • AWS
    90%
  • Terraform, AWS CloudFormation
    75%
  • CI/CD Pipelines & DevOps
    75%
  • Containerization & Orchestration
    70%
  • Serverless & Cloud-Native Solutions
    80%
  • Cloud Security & Compliance
    90%
  • Monitoring & Observability
    70%
  • Database & Storage Solutions
    85%

Education

  1. Masters's in Computer Science || New Jersey Institute of Technology, NJ, USA

    2023 — 2025

    Pursuing a Master of Science in Computer Science from the New Jersey Institute of Technology (2023 - 2025).


    Achievements:

  2. - Won a prize for Best Accessibility Hack from Fidelity company in Girlhacks'23 organized by WICS NJIT.


    3. Courses:

  3. - Machine Learning
  4. - Artificial Intelligence
  5. - Data Structures and Algorithms
  6. - Operating Systems
  7. - Data Management Systems and Design
  8. - Software Product Management


    9. Projects:

  9. Twitter Sentiment Analysis (Oct 2023 - Dec 2023):

    This project performs sentiment analysis on Twitter data using pre-trained models and fetches additional information from Wikipedia and related news articles on the specified topic. It combines natural language processing (NLP) techniques for sentiment analysis, Wikipedia API for information retrieval, and a news API for fetching relevant news.

  10. SpaceSaver (Sep 2023):

    SpaceSaver is a smart parking reservation application designed to simplify the parking experience at NJIT. Users can secure their parking spot in advance through a user-friendly interface and easily locate their parked car.


    11. Research:

  11. New York City: Air Quality Analysis and Forecasting Using Artificial Intelligence:

    Currently working on a paper under the supervision of my AI professor, focusing on analyzing and forecasting air quality in New York City using advanced AI techniques.


  1. Bachelor's in Computer Science || VIT University, TN, INDIA

    2018 — 2022

    Graduated from Vellore Institute of Technology with a B.Tech in Computer Science, specializing in software development and machine learning (Aug 2018 - Sep 2022).


    Achievements:

  2. - Secured 2nd place in "Entrepreneurship Drive" organized by E-Cell VIT.
  3. - Secured 7th place in "Beyond The Limit" organized by IEETEMS VIT.


    4. Notable is my capstone project: "Classification of Cerebral Diseases Along With MRI Estimates" (Dec 2021 - May 2022). I led a dynamic team in designing and implementing a deep learning model using convolutional neural networks (CNNs) to classify cerebral MRI images into three categories: normal, Alzheimer's disease (AD), and Mild Cognitive Impairment (MCI). The project also estimated the age of the brain from these images, demonstrating the potential of neuroimaging data as a biomarker for age-related diseases.


    Achievements include effectively training the CNN model for accurate classification and age estimation, and ensuring seamless integration with the MRI dataset. This project deepened my expertise in AI and machine learning, fostering problem-solving and collaboration skills. I am excited to leverage these experiences in future computer science endeavors.

Contact

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