MANOJ REDDY AVULA

Working to provide cutting-edge solutions in a variety of sectors and technology. Actively exploring ways to contribute to organizational progress via self-development and constant learning.

• Finding memory corruption bugs with KLEE and Comparing KLEE with SymCC: Detected and resolved memory corruption bugs in C and C++ programs using KLEE and SymCC symbolic execution tools, resulting in a 20% reduction in system crashes, Analyzed various bug types, execution paths, and memory addresses for precise issue identification and Demonstrated proficiency with symbolic execution tools, software testing, and debugging, leading to a improvement in overall software reliability.
• Leaf Disease Detection: Using a machine learning algorithm (CNN) and transfer learning, VGG16 is used to identify leaf disease. Any hardware device that is connected to the interface can also be used to directly input data (input format Images only). in which the Flask framework is used to create the interface.
• Cab service fare prediction system: using SVM, KNN, Logistic Regression, and Linear Regression to predict the fare based on conditions. after models are compared to determine which is best. where each analysis section is displayed on the main page for end users (admins) who wish to view it.