I am a B.Tech CSE (AI & ML) student at Ellenki College of Engineering with a passion for data-driven solutions. With a cumulative GPA of 9.3/10, I focus on bridging the gap between theoretical algorithms and real-world application.
My expertise lies in Machine Learning, Deep Learning, and building intelligent systems using Python. I am always exploring new technologies to solve complex problems.
Ellenki College (2023 - Present)
GPA: 9.3/10Sri Chaitanya Jr College (2021 - 2023)
GPA: 9.5/10Python, Java, C, C++, R, SQL, HTML/CSS
Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Scikit-Learn, TensorFlow, PyTorch
Visual Studio Code, Jupyter Lab & Notebook, GitHub, Docker, Streamlit, MySQL, Netlify, Vercel,R Studio
An acoustic fault detection system for industrial machinery. Uses Short-Time Fourier Transforms (STFT) and CNNs to identify bearing faults.
Predicts employee salaries using Linear Regression and Random Forest. Involved extensive feature engineering and data preprocessing.
Predicts likelihood of diabetes using Logistic Regression and SVM on the PIMA Indian Diabetes dataset.
A collection of interactive applications including Flappy Bird, Snake Game, and a BFS Algorithm Visualizer.
Neuro mimesis is a app which uses the advance security protocols rather than just facial and biometric authentication.
P4-based in-network aggregation system for Federated Learning using BMv2, Mininet, Scapy, and Docker to reduce network congestion and server overhead through SwitchML-based gradient aggregation.
A containerized In-Network DDoS Mitigation system using P4 and BMv2 to detect and drop volumetric SYN floods at line-rate without CPU overhead.