M.Tech Data Science · GITAM University
Data Scientist & ML Engineer with a passion for computer vision, deep learning, and building intelligent systems. Currently pursuing M.Tech in Data Science (2025–2027) with a focus on research-grade ML projects.
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Research, deep learning, and full-stack ML work
Convolutional Autoencoder (U-Net architecture) trained on CIFAR-10 using LAB color space. Uses MSE + VGG perceptual loss, 64×64 resolution, 8K training samples. EarlyStopping callbacks for Colab CPU compatibility.
Deep autoencoder-based anomaly detection system for identifying unusual student learning patterns. Comparative analysis of 5 experimental ML papers with practical implementation design.
Proposed IDSGOF framework — IoT + LSTM-Transformer hybrid with Multi-Agent Reinforcement Learning for dynamic load prediction. Addresses the Ramp Rate Problem in renewable energy integration.
Deep Neural Network with Dropout Regularization and Feature Importance Analysis for clinical heart disease risk prediction. Interpretability-focused design for clinical deployment.
Real-time facial recognition system using OpenCV in cybersecurity applications. Published as a research paper in IEEE (Dec 2024) highlighting effectiveness and adaptability for employee security systems.
Machine learning recommendation engine using cosine similarity on genre vectors with 60% genre match, 30% rating weight, and 10% popularity factor. Fully client-side, deployed on Vercel.
Immersive interactive solar system explorer built with TypeScript, HTML, CSS. 3D-like planetary visualization with smooth animations and educational content about each planet.
Neural network classifier on MNIST using TensorFlow/Keras with BatchNorm, Dropout, L2 regularization, EarlyStopping, and ReduceLROnPlateau. Classification and regression models with full pipeline.
// Research
ResearchGate · December 2024
Research on real-time facial recognition highlighting the effectiveness and adaptability of OpenCV in cybersecurity applications. Published on ResearchGate, Dec 2024.
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Machine Learning & AI
Programming & Data
Cloud & Visualization
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2025 – 2027 · Current
GITAM University, Hyderabad
Specializing in machine learning, deep learning, big data analytics, and AI research. Active on image colorization, anomaly detection, and energy optimization projects.
2024 · Certification
IIT Roorkee
Advanced certification covering data science methodologies, AI fundamentals, and applied machine learning techniques.
2021 – 2025
Parul University (PIET), Vadodara · CGPA: 7.13/10
Core foundation in algorithms, OOP, AI, ML, and software engineering. Published IEEE paper during final year on real-time face detection.
2021 · 12th Grade
Sri Chaitanya Junior College, Vijayawada · 86.40%
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Feb – Mar 2025
Forage (Virtual)
Strengthened Power BI skills for client data visualization needs. Created executive dashboards communicating KPIs clearly. Responded to client requests with well-designed analytical solutions.
Mar 2025
Forage (Virtual)
Designed scalable hosting architecture using Elastic Beanstalk for a high-growth client. Communicated architecture and cost models in plain language.
May – Jun 2024
Bytexl
Completed training modules in JavaScript, HTML, CSS, Python, and MS Office. Enhanced practical skills through assessments and project work.
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NPTEL / Coursera
Introduction to Machine Learning
✓ Aggregate: 100/100
Cisco
Python Essentials 2
✓ Aggregate: 100/100
Cisco
Python Essentials 1
✓ Aggregate: 100/100
IIT Roorkee
Data Science & AI Program
✓ Completed
Forage / PwC
Power BI Job Simulation
✓ Completed 2025
Forage / AWS
APAC Solutions Architecture
✓ Completed 2025
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Open to research internships, data science roles, and collaboration on ML/AI projects. Available for remote, hybrid, or onsite opportunities.
Data Science / ML / AI Research internships & full-time roles. Open to Data Analyst, Computer Vision, and ML Engineer positions. Remote, hybrid, or onsite.