About me

I am a driven and passionate professional with a Master's degree in Software Engineering from Arizona State University. With a diverse background in both AI and Software Development Engineering, I have cultivated a deep expertise in building efficient, scalable, and innovative solutions. My journey started with a B.Tech in Electronics and Communication Engineering from Vellore Institute of Technology, where I developed a strong foundation in problem-solving and software engineering principles.

In my professional experience, I have had the opportunity to work in dynamic roles, including an AI-ML/Back-End Engineer Intern at Flow Global Software Technologies, where I spearheaded web scraping automation and developed AI-based solutions. I also contributed as a Technology Analyst at Infosys, leading backend API development, data visualization projects, and enhancing database architectures. These roles have allowed me to gain hands-on experience with a variety of technologies, including Python, Java, Spring Boot, TensorFlow, Docker, AWS, and MongoDB, while also optimizing workflows and reducing manual efforts in data management tasks.

Throughout my career, I have taken on challenging projects such as designing AI-based assistants for automating domain identification tasks and enhancing the performance of outdated systems using modern tech stacks like MERN. These projects have sharpened my technical and problem-solving skills, and have given me valuable insights into scaling systems and ensuring operational efficiency.

Outside of my professional pursuits, I enjoy continually expanding my knowledge base and applying new learnings to solve real-world problems. I am excited about the future, eager to embrace new challenges, and committed to contributing meaningfully to every opportunity that comes my way.

What Am I Skilled At?

  • Front-End Development

    Front-End Development

    Developed responsive and accessible web interfaces using React.js and Bootstrap, optimizing performance and ensuring mobile responsiveness

  • Back-End Development

    Back-End Development

    Designed and optimized scalable RESTful APIs using Java Spring Boot and Django, effectively managing data, sessions, and error handling

  • Machine Learning

    Machine Learning

    Applied machine learning techniques for practical applications, improving 5G network security using models like XGBoost, GAN and ANN. Experienced with NLP and data science.

  • Algorithms and Database Management

    Algorithms and Database Management

    Leveraged MongoDB and PostgreSQL to optimize data retrieval. Developed algorithms and applied Random Forest for feature selection to reduce the training time.

    • Experience

    Flow Global Software Technologies LLC

    1. Backend Engineer/ AI Intern

      June 2024 - Present

      1. Automated CSV header standardization using SentenceTransformer's roberta-base, reducing manual header mapping by 85% and achieving a 92% match rate with predefined headers.

      2. Enhanced data processing speed by 30% with pandas and regex for cleaning and transformation tasks.

      3. Implemented a time-decorator function, reducing execution time by 20% in similarity matrix computation and header renaming processes.

      4. Built API with Python 3.11 and FastAPI, improving request-handling by 25-30% through asynchronous operations.

      5. Integrated BeautifulSoup, Selenium, and Langchain for web scraping and text classification, followed by LLM Llama 3.18b and prompt engineering to automate company domain generation, reducing manual effort by 70% and boosting performance by 15-20%.

    Infosys Limited

    1. Technology Analyst

      February 2021 - June 2022

      1. Implemented Nginx as a reverse proxy and load balancer for a Django and PHP application, optimizing static file serving and reducing server load by 20%, improving request handling and response times.

      2. Integrated Kafka for real-time event streaming and asynchronous task handling in Django and PHP services, leveraging kafka-python and PHP Kafka clients, reducing event processing latency by 30%.

      3. Deployed and managed both Django and PHP applications on Kubernetes, containerizing with Docker and using Kubernetes for orchestration, achieving 99% uptime and enabling auto-scaling for high traffic periods.

      4. Optimized the backend database with PostgreSQL for Django and MySQL for PHP, reducing query execution times by 15% while ensuring both systems scaled effectively with growing data volumes.

      5. Developed a responsive frontend using React.js for Django and PHP templates, enhancing user experience with a 12% increase in session duration, and streamlined deployments using CI/CD in Kubernetes, reducing deployment time by 40%.

    1. Senior Systems Engineer

      February 2020 - January 2021

      1. Developed a server-side application using Java Spring Boot and REST controllers, enabling efficient communication with databases through RESTful web services and JSON, increasing delivery efficiency by 15%.

      2. Implemented a CI/CD pipeline leveraging Jenkins, reducing release cycles by 20% and improving deployment efficiency by 30%, leading to faster time-to-market.

      3. Enhanced software testing by creating unit tests in JUnit, integrating automated testing into the build process, improving platform reliability and reducing errors.

      4. Improved code quality by incorporating automated unit testing into the CI/CD pipeline, ensuring that test cases were run consistently during every build.

      5. Reduced manual testing efforts by 25% and improved bug detection by 18% through the continuous integration of automated tests into the SDLC.

    1. Systems Engineer

      December 2018 - January 2020

      1. Enhanced scalability and performance of an online travel portal using the MERN stack, decreasing system response time by 20% and increasing capacity for simultaneous users by 30%.

      2. Restructured web pages with React.js, resulting in a 12% increase in the stay time of users on the website compared to the previous year by implementing faster state management, users experience smoother navigation and shorter load times.

      3. Engineered a MongoDB database architecture, optimizing customer information storage and retrieval, boosting operational efficiency by 11%.

      4. Redesigned the payment portal with Bootstrap, improving accessibility and increasing transaction rates by 14%.

      5. Integrated jQuery and React to improve frontend responsiveness, resulting in a 25% enhancement in overall site performance.

    Education

    1. Arizona State University, Tempe

      Master of Science (MS) Software Engineering 2022 — 2024 GPA: 3.5/4

      Relevant Coursework - Advanced Data Structures and Algorithms, Machine Learning, Software Agility, Web based Applications


    2. Vellore Institute of Technology, Vellore

      Bachelor of Technology (B.Tech.) Electronics and Telecommunications Engineering 2014 — 2018 GPA: 8/10

      Relevant Coursework - Data Strcutures and Algorithms, Computer Architectures and organization.


    Projects

  • design icon

    Capstone Project Spring 2024: 5G Network Intrusion Detection Research Project

    - Intrusion Detection with XGBoost and CatBoost: Applied XGBoost and CatBoost machine learning algorithms for network intrusion detection, achieving a 30% increase in detection accuracy.
    - Feature Selection via Random Forest: Employed Random Forest for feature selection, reducing dimensionality and improving model interpretability and training efficiency by 20%.
    - OGAN-based Synthetic Data Generation: Utilized GANs (Generative Adversarial Networks) to generate synthetic data, augmenting the training set and boosting model accuracy to 99.97% for network security tasks.
    - Data Processing with Min-Max Scaling and Correlation Analysis: Implemented Min-Max scaling and Pearson/Spearman correlation analysis to optimize data preprocessing, leading to more efficient data modeling and improved feature relevance by 15%.
    - AI Integration with Federated Learning and Blockchain: Proposed integration of Federated Learning and Blockchain for decentralized and secure network management, enhancing security robustness in 5G/6G environments.

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  • design icon

    Taiga - API Integration using Java Spring Boot

    - Integrated Taiga APIs with Java Spring Boot to track performance metrics, architecting microservices, which led to a 20% improvement in project tracking and system monitoring.
    - Developed the frontend using Next.js, enabling real-time metric visualization, improving the accuracy and speed of decision-making by 20%.
    - Containerized microservices using Docker, ensuring consistent environments, reducing deployment time by 15%, and lowering error rates by 10%.
    - Deployed containerized applications to Microsoft Azure, improving scalability by 30%, reducing infrastructure costs by 18%, and enhancing operational efficiency by 25%.
    - Enhanced system maintenance and resilience by containerizing microservices, resulting in a 30% improvement in system scalability and a 15% reduction in downtime.

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    • Daniel lewis

    Daniel lewis

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