💻 Final Year Computer Science & Engineering Student @ Manipal Institute of Technology
🤖 Pursuing Minor Specialization in Computational Intelligence
🚀 Passionate about Artificial Intelligence & Machine Learning

✨ I love building intelligent systems that combine AI + Machine Learning to solve real-world problems.
🔍 Currently exploring LLMs, Computer Vision, and Blockchain Security, while contributing to open-source projects.
🌱 On a mission to learn, build, and innovate every day.

Amazon Jan 2026- Present

• Worked with large-scale internal Amazon systems and operational tools to validate, audit, and process high-volume transactional data, ensuring accuracy, compliance, and system integrity across workflows.
• Performed root-cause analysis on data mismatches and system-generated exceptions by analyzing logs, reports, and rule-based outputs, contributing to process optimization and defect reduction.
• Utilized automation-driven workflows, dashboards, and rule engines to monitor operational KPIs, detect anomalies, and support data-backed decision making for business stakeholders.

Xcitium-NuFintech Nov 2025 – Jan 2026

• Built data-driven trading intelligence models leveraging market microstructure gamma-exposure analytics.
• Improved trade-outcome prediction accuracy by 30% through optimized ML pipelines and semantically rich composite features.
• Automated an oscillator-based signal-detection framework, achieving 5× faster feature extraction.
• Collaborated with research leads to integrate structural and statistical indicators into production-grade models.

JPMorgan Chase Jun 2024 – Jul 2024

• 🌐 HTTP Request Tracking: Tracked and logged HTTP requests and responses (URLs, headers, payloads) into a secure MySQL database using Java & Spring Boot.
• 📊 Data Visualization Dashboard: Created a web dashboard with Chart.js, displaying metrics such as number of requests per domain and total data size transferred.
• 🔐 Security & Authentication: Implemented user authentication and data encryption with Spring Security to ensure privacy and controlled dashboard access.

A Machine Learning Model forecasting air quality

• 🏗️ Designed and deployed a machine learning-powered web application for real-time air quality forecasting, addressing rising concerns over public health and climate change..
• 📊 Leveraged historical AQI, PM2.5, and PM10 datasets with advanced feature engineering to train deep learning models, enabling accurate future pollution predictions.
• ⚡ Integrated TensorFlow.js for seamless browser-based real-time inference, ensuring fast, accessible, and scalable deployment.

Tech Stack: TensorFlow.js Python JupyterNotebook Keras Pandas Deep Neural Networks

TensorFlow-Powered Machine Learning Model for Classifying Pedigree Charts into Autosomal Dominant, Autosomal Recessive, X-Linked Dominant, X-Linked Recessive Y-Linked Dominant, & Y-Linked Recessive Inheritance Pattern.

• 🛠️ Built a custom pedigree chart dataset modeling autosomal dominant/recessive, X-linked dominant/recessive, and Ylinked dominant/recessive inheritance patterns.
• 📈 Trained and optimized a TensorFlow classification model with preprocessing, normalization, and one-hot encoding ,using the Adam optimizer for faster convergence.
• 🎯 Applied hyperparameter tuning and cross-validation, achieving 94% accuracy in predicting inheritance patterns on unseen data.

Tech Stack: TensorFlow.js Python JupyterNotebook Keras Pandas Convolutional Neural Networks

A Flutter app for IoT based Arduino nano non-invasive device for comprehensive blood glucose monitoring.

• 📱 Developed an end-to-end industrial IoT health monitoring app using Flutter/Dart with Firebase for real-time sync.
• </> Applied Concepts of Software Engineering Like SDLC Prototype Model in development, achieving 95% alignment with objectives and improving development efficiency by 40% through iterative prototype refinement.
• ⚡ Conducted performance optimization tests, improving system efficiency by 30%.

Tech Stack: Flutter Dart Software Engineering Google Firebase Firestone RestAPI

Flutter app for table reservation database management

• 📱 Developed a cross-platform mobile application using Flutter and Dart, integrating Firebase for real time data synchronization and authentication, which enhanced user engagement by 30%.
• 🎨 Designed intuitive UI/UX for Table reservation based mobile app, resulting in 25 % increase in user satisfaction and a 20 % reduction in user churn.
• 🔗 Implemented REST APIs for seamless communication between mobile app and Backend services, reducing data retrieval time by 50 %.

Tech Stack: Flutter Dart JSON Google Firebase Firestone RestAPI

• Bachelor of Technology, Computer Science and Engineering
• Minor Specialization in Computational Intelligence

Manipal Institute of Technology • Sep 2022 – July 2026

• Relevant Coursework:
  • Data Structures & Algorithms
  • Object Oriented Programming
  • Operating Systems
  • Computer Networks
  • Soft Computing Paradigms
  • Artificial Intelligence
  • Machine Learning
  • Computer Vision
  • Parallel Computing
  • Blockchain Technology

• Pollution Predictor : A machine Learning Model For Forecasting Air Quality (Minor Project Publication )
• Medisure Type 2 Diabetes Predictor (Undergoing)

• IN23/2404 Application No. 202441091887 Device and method for monitoring blood parameters of a user (Early Publication available)