Anurag Singh Bagehl

I am a skilled computer science professional with a background in boarding school education, where I learned important qualities such as responsibility, time management, and leadership. After completing my B-Tech in Computer Science, I gained experience in strategic planning, business development, financial management, team leadership, and supply chain management as a proprietor in my family business. However, my passion for technology has led me to shift my focus to a technical role, where I can leverage my programming skills to solve complex problems.

As a programmer, I am proficient in Java, SpringBoot, MYSQL, JavaScript, CSS, and HTML. I have a keen eye for detail and a passion for delivering high-quality results. My strong leadership qualities and ability to thrive in a collaborative team environment make me an excellent fit for a dynamic organization . I am committed to continuous learning and improvement, and I am excited to contribute my technical expertise to help drive innovation and success for the company.

Certification of Design and Analysis of Algorithms by NPTEL, IIT Madras

Academic Project : PGDAC 

Title :  Online Banking System || Duration : 1 Month

Team : 5 Members

Platform: SpringBoot, MySQL, HTML, CSS+tailwindCSS, ReactJs 

Description : 

The online banking system, for bank customers and administrators to manage customer's bank accounts. It enables bank customers to conduct virtual bank transactions, view bank transactions, manage their accounts, send messages to administrators, etc. 

Academic Project : B-Tech (Major Project)

Title :  File Checker || Duration : 6 Months

Platform : Python 

Team: 3 Members

Description : 

This study aims at classifying executable binaries(Portable Executable files) based on its run-time behaviour. The proposed method is 91.9% accurate which aims at extracting traces of API calls made to generate possible unique alternative traces in order to detect other malicious API patterns. A classification model is built by employing the RandomForest algorithm. 

Academic Project : B-Tech (Miner Project)  

Title : Smart farming || Duration: 3 Months

Team: 2 Members  
Platform : Java, Javascript, HTML, CSS  

Description:

The website enables the farmers to get information based assistance by providing real time information about the degree of fertility of the soil, soil moisture content, the types of crops that could be grown and the requirement of particular pesticides or insecticides in respected area. It enables the farmers to take informed decision with the help of the available information to determine the best use of scarce resources to its optimum use benefitting the small farmers by improving crop yields

File Checker: Determining Signatures of an Executable Binary to Detect Malware 

This study aims at classifying executable binaries(Portable Executable files) based on its run-time behavior. The proposed method is 91.9% accurate which aims at extracting traces of API calls made to generate possible unique alternative traces in order to detect other malicious API patterns. A classification model is built by employing the RandomForest algorithm. This paper has been published in IJCA by Foundation of Computer Science, New York, USA dated May20.