Senior Technologist at Philips | Full Stack Java Engineer | Microservices | Spring

Vinay GopalKrishna • Peerlist

Involved in product security update using java EE security features.
Used OWASP Application Security Standards.

Javelina Application Security Update

Project aims to give a hassle free process for polling.

Online National Polling(IBM's TGMC Project)

The SaaS Control Plane - SaaS CP for short - is architectural thinking that translates the SaaS Factory needs into smaller solution patterns. The onboarding framework defines both customer onboarding and tenant onboarding, user access management functions, and set of user interfaces. 

Technologies and AWS Services Used:
AWS Lambda, Amazon API Gateway, Amazon RDS, AWS S3, AWS CloudFormation, python, Spring, Step functions.

Saas Control Plane

Javelina™ is a payer platform for health benefits and reimbursement administration.

Designing and developing the web applications using XTTM, HTML5, JavaScript, jQuery and ajax.
Converting user requirements for the project into technical requirements.
Implemented Model View Controller (MVC) architecture and used custom components available in the framework.
Building the application and deploying it to the Tomcat Web Server.
Code review based on java coding standards.

Javelina

Hobby Project:
A simple financial Bot using Oracle Intelligent Bots platform, 
configured its artifacts, tested it and deployed it to a sample web application.
1. Created intents
2. Added utterances (sample phrases to help your bot reference intents when it
parses the user input)
3. Added entities (extra content to enable your bot to complete a user
request)
4. Configured system components (built-in components that allow you to perform
typical interactions with the users, control the flow, perform language detection and
manipulate variables) and custom components (REST services that allow the Bot to
interface with external APIs)
5. Configured messaging channels where you enable a messaging platform to use your bot.

Developed and deployed AI powered intelligent Bot using Orac

Problem Statement: Customers need to find the right insurance plan by identifying the optimal prices to quote based on the coverage, health records.  

Data Selection: Claim’s data & patient generated health data are selected to determine the patient disease, medical & claim history. All internal & external data is considered which will helps us to determine the right plan for the patient.  

Data Preparation: It includes sorting, structuring, preprocessing & filling the missing data points (if any). Training Data Set & Testing Data Set will be prepared. 

Development 

Development & modelling: A machine learning technique is chosen. Right algorithms are selected. 

Technology stack: Machine Learning, Pandas, TensorFlow & Torch/PyTorch , python

Collaboration: Rapid iteration & validation of Trained models are done so that the business goal is achieved.  

Testing: Here the model is tested to check how well the model works on the data it has never seen. 
 
Validation 
In this final stage initial insights are presented & results will be evaluated. Recommendations will be issued for deployment strategy. All possible recommendations will be evaluated & validated.

Insurance Pricing Prediction

Google Hackathon Project
Idea description
Chatbot which will help/guide the user for using the product or getting information etc  
Possible Use Case: 
View Products
View/Update Employee Information
View Commissions & Pay
Update Payment Information

TECHNOLOGY STACK
Java, Google App Engine, Google Cloud, Google DialogFlow



AI Powered ChatBot For Health Insurance Product

Profit Enhancement Center is a cloud solution offering integrated cost management, revenue assurance, profit analytic solutions and network optimization in a single platform for communication service providers.

Responsibilities:
Involved in Analysis of the requirements to define business process and workflow for each of the Use cases.
Participated in Architectural discussions on UML Specifications, defining Structural and Behavioral Elements, forming relationships and applying relevant design patterns wherever applicable.
Developed UML Use-Case diagrams, Sequence and Collaboration diagrams, class diagrams.
Prepared Test Cases to perform Unit Testing. Tested the developed components using Junit.
Used Log4j for logging and debugging and used Junit extensively for testing.