Proactive and analytical Computer Science Engineering student with strong logical reasoning and problem-solving skills, interested in applying analytical thinking to real-world challenges.
Defence Laboratory, Jodhpur (DRDO)
06/2025 – 07/2025 · Jodhpur, India
Built an image analysis program to automatically extract and interpret dominant visual features from varied image inputs; implemented analytical modules to study and visualize patterns in extracted data.
B.Tech, Computer Science Engineering
2026
8.3 CGPA; Member of GeeksforGeeks (ADGIPS Chapter).
12th, PCM
2021
Scored 91.2%.
10th
2019
Scored 85.2%.
Designed and implemented a custom CNN to classify synthetic facial images using Python, TensorFlow, OpenCV, Scikit-learn, and MySQL. Applied preprocessing and augmentation to improve generalization and reduce overfitting. Achieved 94% training accuracy, 91% validation accuracy, and 91.85% test accuracy, with precision of 0.98 for synthetic images and recall of 0.99 for genuine faces.
Developed a hybrid recommendation engine using content-based filtering and Multinomial Naive Bayes with Python, Flask, Scikit-learn, and the TMDB API. Combined the TMDB 5000 dataset with scraped Wikipedia records and achieved validated sentiment accuracy of 98.77%.