OBJECTIVE:

To work in a real professional atmosphere that offers a challenging and simulating work with a scope for software development that helps me in widening spectrum of my knowledge and along with attractive prospects.

PROFESSIONAL EXPERIENCE:

Working for Present Employer as Software Engineer from Feb 2017 to till date.

EDUCATIONAL QUALIFICATION

Completed MCA in Hi-Tech Engineering College with 77% Aggregate in the year 2011.
Completed BSC (MPCS) from SSR Degree College with 70% aggregate in the year 2008.
Completed Intermediate (MPC) from VidhyaVikas Jr College with 62% aggregate in the year 2005.
Completed SSC from Pragna High School with 70% aggregate in the year 2003.

TECHNICAL SKILLS:

Languages : Java, Node
Java Framewoks : Spring, SpringBoot, SpringJpa, SpringMvc
Scripting Language : React Js, Node Js, Angular ,TypeScript, Java Script
Web Server : Apache Tomcat
Markup Languages : HTML5, CSS, JSON
Databases : Oracle, MySql, Node
Development Tools : Eclipse, STS, Vs Code
Operating Systems : Windows, Linux
Source Control Tool : GitHub

PROJECTS:

Fake reviews :

Platform : Web application.

Role : Developed a Dashboard, Rest APIs(web services), Database Team : 6

Technologies : React Js, Node Js, Angular, TypeScript, HTML,CSS, JavaScript, Json,. Source Control Tool: GitHub

Development Tool : Vs Code Description :

Product reviews are vital sources of customers opinions and have a significant impact on purchasing decisions and product rankings on online shopping sites. Unfortunately, fraudsters (spammers) may write deceptive reviews (Spam reviews) appreciating or deprecating a product, which can mislead potential customers and negatively affect revenues of many genuine organizations. Therefore, there is a great need for an effective approach to detect fake reviews and spammers. The proposed model consists of two components: detection of duplicate reviews, detection of anomaly in review count and rating distribution.

Various companies are hiring people to write fake positive reviews about their services or products or unfair negative reviews about their competitors services or products. This process gives wrong input to the new customers who wish to buy such items and hence we need a system to detect such fake reviews and remove them.

Sneakerware :

Platform : Web application.

Role : Developed Dashboard(website), database.

Team : 8

Technologies : Java, Spring, Angular, HTML,CSS, JavaScript, Json, SpringJpa, MySql. Development Tool : Spring STS, Vs code

Source Control Tool: GitHub

Description :

Think of SneakerWare as a Facebook designed specifically with sneakers and their ardent collectors in mind – SneakerWare allows each sneakerhead to create his or her own mobile profile where they can connect with their friends, make new ones, and stalk their kicks. Users will be able to interact with their friends and other members Let's take you on a walkthrough of SneakerWare: after carefully creating an impressive profile of personal information, it is time to build your mobile warehouse. Create an inventory of your sneakers and organize them digitally via your iPhone library or take new ones on the spot. Then, you can share your prized possessions in a comprehensive manner with other users and friends, and they can rate your kicks, comment on them or make offers

or trade requests, using a built-in trading function.

Sneaker Collections - Users can take their own pictures to add to their "collection" that they can access.
Sneaker Network: Users can add friends and be able to see other’s collections
Shop Guide: Users can see a list of shops in our shop guide database and also be able to submit shops to be added to the DB
News: The is a news reader that will display news articles from various sneaker news sources leveraging RSS