SRINIDHI VADDEMPUDI 320-***-****
Regent Dr, Dekalb, 60115 https://github.com/srinidhi13-hub
I am a dedicated individual with professional experience as Full Stack Developer for two years having worked on programming languages and technologies of Java, Python, HTML/CSS, JS, React.JS, RESTful Web Services also an experienced SQL developer.
Programming Languages: C, C++, Java, Spring MVC, Spring Boot.
Visualization Tools: Tableau, Kibana, Elastic Search, Logstash.
Web Technologies: HTML5, CSS, JS, JSON, jQuery, Node.js, React.js, D3.js, RESTful web services.
Database: Oracle SQL Developer, Microsoft SQL Server, Relational Databases, MySQL, MongoDB.
Other Tools: GIT, Jenkins, AWS, Linux.
Master of Science: Computer Science, Northern Illinois University Jan 2019 - May 2020(GPA:3.7)
Coursework: Design & Analysis of Algorithms, Java, C++, ASP.NET, Python, Web Technologies (HTML/CSS, JS, React.js, Node.js), DBMS, Big Data, Visualization Technologies (R, Tableau).
Bachelor of Technology: Computer Science and Engineering, KL University Aug 2013 - May 2017
PROFESSIONAL EXPERIENCE May 2017 – December 2018
Full-Stack-Developer, Capgemini, Bangalore, India.
Ecommerce Website Order History: May 2017 – June 2018
It is an e-commerce website present from more than 8 years having billions of data. In order to make user to search the past years data in Order History integrated Java with Elastic Search. It’s is developed on the micro-service Architecture.
Worked in the API Services integrating with project standard libraries, Java8 streams and lambda expressions.
Worked in the Data Design for the Elastic Search. Worked on Junits, Mockito’s.
Planning Website for Promoting Products to Customers: July 2018 – Dec 2018
An intranet Application used to help the customers to promote the products to customers by planning the promotions for the promoting products. The project is developed on MVC Architecture.
Implemented several API services integrating with the elastic search. Designed the search functionality from the requirements phase to deployment phase and integrated the API's to the application.
Portfolio: I have developed my portfolio using REACT.JS and deployed using GitHub which gives brief information about my projects and work experience(https://srinidhivaddempudi.herokuapp.com/).
A Comparative Study on Study on Coterie Identification in Facebook Network:
The coterie identification can be done by the structure of Facebook public pages. There are a lot of activities people perform which are diverse from each other. For this, we use the Label Propagation Algorithm, Fast Unfolding and Spectral Clustering methods for identification and compare the results of each method to get a fair understanding of which method calculates the user’s nodes effectively. The technologies used are Python and Java.
Air Quality Prediction and Analysis using ANN and ANFIS:
This project is centered around predicting the contents of atmospheric pollutants over an interval of time and generating alerts to the people via a mobile application if the toxicity is beyond the permissible level.
This is designed using Artificial Neural Networks and Fuzzy Systems using “Python programming”.
Big Data Compression in IOT
Developed a method for efficient compression of IOT sensor data, which involves organizing the data from multiple sensors in the form of matrices and then compressing it by using video compression algorithm.
By this method, the tons of data generated by IOT sensors can easily be compressed, stored and transmitted over network.
Blind Image Blur via Deep Learning
Pre-trained deep neural network is used for the purpose of blur analysis in the stream of image processing.
The blur type is estimated and classified by training the deep neural network with input samples and then general
regression neural network is used for parameter estimation, which greatly helps in de-blurring of a blurred image.
Certified in Amazon Web Services (AWS) as Developer Associate.