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AI Engineer with less than a year in Web Development & Machine Learning
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Highly motivated and results-oriented B.Tech student in Computer Science and Engineering with 4 months of diverse experience in web development and AI/ML internships. Proficient in Python, Java, JavaScript, and cloud platforms like Microsoft Azure. Demonstrated ability to build responsive web applications and implement machine learning models for real-world problems such as water quality prediction and Alzheimer's disease classification. Eager to apply strong analytical and technical skills in a challenging AI or data-focused role.
Government Engineering College, Palamu
B.Tech · Computer Science and Engineering
August 1, 2022 – June 30, 2026
Edunet Foundation(Microsoft)
AI Azure Intern
May 1, 2025 – June 1, 2025
India
Prodigy Infotech
Web development Intern
June 1, 2023 – July 1, 2023
India
Water Quality Prediction Model
January 1, 2026 – Present
This project successfully demonstrated a machine learning-based approach to predict future water pollutant concentrations using historical data from water quality monitoring stations. By utilizing libraries such as pandas, numpy, and scikit-learn, we developed a MultiOutput Random Forest Regressor capable of predicting multiple pollutants based on the input features like Station ID and year. We trained and evaluated the model using Mean Squared Error (MSE) and R2 Score, which confirmed that the model provided accurate predictions across various pollutants.
Identification of Alzheimer's Disease Using a Hybrid Deep Learning Approach
January 1, 2026 – Present
Built an end-to-end Alzheimer's disease classification system using MRI brain scans and hybrid deep learning techniques. Engineered a Dual CNN model with attention mechanisms to automatically extract discriminative features from neuroimaging data. Combined SVM, KNN, and Random Forest classifiers through soft-voting ensemble learning to improve prediction robustness. Processed and augmented a dataset of 6,400 MRI images, applying normalization and SMOTE-based class balancing. Achieved 99.06% classification accuracy, outperforming individual baseline machine learning models. Implemented an interactive React-based frontend for real-time disease stage prediction and result visualization.
AI Badge
Microsoft
June 1, 2026 – Present
Certificate of Participation from ISRO in AI/ML for Geodata Analysis
ISRO
June 1, 2026 – Present
OCI AI Foundation Associate
Oracle
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and internships show a strong interest in AI/ML and web development, aligning with a tech-driven culture. The diversity of projects (environmental prediction, medical imaging, chatbot) indicates adaptability and a willingness to explore different problem domains. Participation in a coding club and sports club suggests a collaborative and well-rounded individual.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems and deliver functional solutions. Participation in clubs suggests teamwork and leadership potential. However, the experience is primarily academic and internship-based, which may require more operational guidance in a full-time senior role.