About Me

  • Over 2 years of experience in developing and designing Web Based Internet/Intranet, Multi-tier distributed applications using latest Core Java and J2EE technologies and various open source frameworks
  • Used Spring Core Annotations for Dependency Injection Spring DI and Spring MVC for REST API.
  • Strong hands-on experience with Spring IOC, Spring Boot with Micro services.
  • Experience in Jenkins, Docker and Kubernetes
  • Experience developing Front End User Interface in web applications using HTML5, CSS3, Java Script, Angular 11, React JS and Bootstrap.
  • Experienced in using build tools such as Maven.
  • Experienced in different software development methodologies like Waterfall Model and Agile Methodology.
  • Experience with Amazon Web Services like EC2, S3.
  • Hands-on experience in relational databases like MySql, MongoDB.
  • Expertise in using version control systems such as GIT.
  • Expertise in client scripting language and server scripting languages like JavaScript, and JSON.
  • Configured and developed web applications using SpringMVC Architecture, IOC and other Spring modules
  • Developed web applications based on different Design Patterns including Model-View-Controller (MVC), Data Access Object (DAO), Front Controller etc.
  • Experienced in databases such as MySQL to manage tables.

Work Experience

Full Stack Developer
- Sprigrer Technologies
  • Designing and developing Web Application adhering to MVC architecture that provides users ability of creating new web-based claims and viewing claims status online.
  • Used Spring Core for Inversion of Control (IOC) to inject dependencies (DI) for loose coupling.
  • Wrote Spring Controllers, DAOs & their Implementations, Service and Model classes and auto-wired them.
  • Worked under Test Driven Development (TDD) along with Agile/Scrum methodology.
  • Created numerous mocks from test database using Mockito for unit testing of the code using the JUnit testing framework to implement TDD.
  • Created and maintain web pages using HTML5, CSS3, JavaScript and Angular responsible for designing of Web pages.
  • Developed Web API using Node JS and hosted on multiple load balanced API instances.
  • Implemented Software Design patterns like Singleton and Factory.
  • Used to developing software using SDLC and Agile/Scrum methodologies using TDD/BDD.
  • Developed User Interface using TypeScript and Angular involving interactive features such as text boxes, navigation buttons, directives and services.
  • Handled security concerns by implementing Spring Security using JWT for Authentication and Authorization to control patient, receptionist and administrator access.
  • Constructing reusable front-end structure that consumes RESTful endpoints to render and display claims files to the customers.
  • Interacting with the clients to understand their requirements and provide smooth implementation and ongoing support.
  • Developed and executed unit test plans using JUnit and Mockito ensuring that results are documented and reviewed with quality assurance teams responsible for integration testing.
  • Involved in the Agile sprints to streamline the development and design process.
June 2020 - July 2021
Backend Developer
- Verzeo Technologies
  • Worked in collaborative team environment with developers, business analysts, data analysts and product managers to develop the requirement and design specifications.
  • Involved in various phases of Software Development Life Cycle (SDLC) of the application like requirements gathering, analysis, design, development, testing and deployment.
  • Involved in Agile Methodology process, which included bi-weekly sprint and daily Scrum to discuss the design and work progress.
  • Implemented and enhanced CRUD operations for the applications using the Spring-Rest Framework.
  • Developed RESTful Web Services using Spring REST Controller to expose existing application functionalities for end clients.
  • Worked on preparing design documents and user instructions.
  • Created the User Interface for user to perform various operations on claims posted in the system.
  • Created service clients to consume web services from other application modules.
  • Adapted to all stages of software life cycle like design, development, testing and deployment.
  • Developed code based on Spring REST framework and used Dependency Injection (DI) to decouple the dependencies between objects.
  • Developed persistence Layer using Hibernate to persist and manage the data.
  • Used Spring Security to implement security features for the web application.
  • Involved in creation of RESTful WebServices and web methods using Annotation.
  • Implemented and enhanced CRUD operations for the application using the MVC architecture.
  • Deployed the application using Tomcat server.
  • Testing of individual components using JUnit and fix issues to achieve better delivery quality as per customer quality guidelines.
  • Implement several core design pattern like MVC, singleton, Data Access Object (DAO), Adapter pattern and Factory pattern.
  • Used complex SQL queries to implement procedures for MySQL database.
Jan 2019 - May 2020

Education

Masters in Computer Science
Aug 2021 - Dec 2023
Rochester Institute of Technology, New York, USA
B-Tech in Computer Science
Aug 2017 - July 2021
Vellore Institute of Technology, Madhya Pradesh, India

Projects

SPEECH TO FACE: Generating Faces using Audio
  • The Aim of this project was to use the power of Generative AI to create a CNN model capable of using Audio clips of 6 seconds and create an accurate image of the speaker.
  • This project uses pre-existing Facial recognition and Voice recognition software to Pre-Process the data.
  • A Python script was created to download 10,000 videos using YouTube DLL Dataset and send to the Facial and Voice Recognition software for Pre-Processing.
  • During Pre-Processing Audio and the Image are separated and stored in an AWS cloud for further use.
  • During the training phase of SpeechToFace CNN model, Audio and Image files are taken from AWS cloud and the model is trained on them.
  • During the Testing Phase of the CNN model just the Audio clips are supplied to the model and 4096D Facial Vectors are generated.
  • These 4096D Facial Vectors are passed through the Face-Decoder Model and an image resembling the original speaker is generated.
  • My SpeechToFace CNN model is around 92% accurate while generating upto 95% likeness of the original speaker.
Aug 2023 - Dec 2023
Analysis of Loss using Different risk factors
  • The aim of this project was to study and reduce overall loss in Machine learning models using different risk factors like Bias and Variance.
  • We used ResNet18 as the CNN model for this project with CIFAR10 and CIFAR100 datasets.
  • Our Hypothesis was if we reduce the Bias while keeping the variance same then the overall loss would decrease.
  • To test this hypothesis, we first used CIFAR10 Dataset and conducted the experiment with 4 different Biases.
  • Since we were getting positive results, we moved on to a significantly larger Dataset i.e. CIFAR100.
  • Our Experiments showed that keeping Variance same while changing the Bias has a significant result on the overall loss of the CNN.
  • Hence, we Concluded that Loss can be reduced with Appropriate Bias and Risk factor.
Feb 2023 - May 2023
MySQL to MongoDB
  • The Aim of this project was to create a Java Program to create a ETL pipeline capable of taking a MySQL database and transfer its data to a MongoDB database while maintaining data integrity.
  • The first step was to use JDBC to Capture the data from MySQL.
  • This was done in batches since IMDB dataset with 1Billion Rows was used.
  • Next step was to use Java to connect to MongoDB and Transform the data as required and pass it to MongoDB server.
  • Time taken and Internal memory used was the biggest challenge in this project since the whole IMDB dataset has over 1 billion records and over 5 tables.
  • My Solution to reduce the time taken was to use multiple threads and run them in parallel to Transfer the data.
  • This opens up the possibility of data redundancy. To avoid that I used Transactions to make sure that data is not redundant.
  • Total time taken for the whole process was 1.5hr with multi-Threading and 3.5hr without multi-Threading.
Feb 2022 - March 2022