About Me
My Background
I am a Computer Science and Mathematics student at Schreyer Honors College, Penn State University, specializing in artificial intelligence and machine learning. With a 3.98/4.00 GPA, I have consistently been recognized on the Dean's List for academic excellence.
My academic journey includes a summer at Stanford University, where I explored advanced AI and machine learning concepts, gaining hands-on experience in algorithm development and real-world applications.
Through research positions and internships, I have contributed to AI-driven projects ranging from adaptive learning algorithms to real-time image processing systems using YOLOv5 and OpenCV. My experience bridges theoretical research with practical implementation, driving innovation in AI applications.
Achievements
- Developed an adaptive learning algorithm that improved WisdomNet's reliability by 90% for safety-critical applications, tested on breast cancer and synthetic datasets.
- Built an AI-powered real-time detection system using YOLOv5 and OpenCV to identify fire, smoke, and face masks, enhancing safety monitoring.
- Created a voice-activated Android application for display panel printing, integrating Bluetooth communication and Arduino-based controls.
- Processed T1-weighted MRI data for 887 patients from the PPMI database, applying segmentation and atlas-based alignment to extract clinically relevant features.
- Designed a deep learning pipeline combining 3D CNNs, SVM, and Random Forest, achieving 76.4% binary accuracy in Parkinson’s disease classification.
- Holder of multiple patents, including the In-Pipe Inspection Robot (Indian Design Patent: 360985-001).