About
Hello! I'm Nishanth, a talented, ambitious, and hardworking individual, with broad skills and prior knowledge in the analytical area to suit up with Business Analytics and Data Science. By nature a confident leader and enthusiastic participant and communicator with a handful of knowledge in interpreting and analyzing data reinforced by excellent statistics, mathematics, and analytics tool knowledge. Currently, I am working as a Java Full Stack Developer at Cognizant.
Internships
Cognizant
MARCH 2021 – AUGUST 221
( Full Stack Developer )
Responsible for API design and development of RESTful Services using Java Spring framework. Worked on building new Angular components for the customer-facing web app. Used Git for version control and have worked with GitFlow. Contributed to the development of a web application – Audit Management System
CodeBind Technologies, Chennai
MAY 2019 – JUNE 2019
( Front-end and Back-end )
Learned about the fundamental scripting skills to look for in a web developer training program which includes HTML, CSS, and Javascript. Also, I got an idea for hot programming skills for back-end web development positions including PHP, XML, and SQL.
National Small Industries Corporation Ltd, Chennai
NOVEMBER 2018
( IoT )
Learned how to control all the electronic devices to function automatically through the internet. The main purpose of Internet-connected devices has been to enable communication with each other and to access online data and processes.
Research Paper
Automatic Personality Recognition System using Time Distributed CNN
SEPTEMBER 2020 – FEBRUARY 2021
With the occasion of Artificial Intelligence (AI), the automated assessment of digital interviews to well-known individual personality traits has ended up being a lively place of research and has programs in character computing. Advances in computer vision have caused the foundation of convolutional neural organization models that accurately comprehend their character improvements. In this way, a start to finish Machine Learning (ML) fueled meeting machine was progressed with the utilization of Asynchronous Video Interview (AVI) handling. A TensorFlow AI engine seeming automated personality recognition (APR) upheld by the capacities separated from the AVIs. The exploratory results show that our ML-based meeting specialist effectively recognizes an interviewee's "OCEAN" advancement. Along these lines, the ML-based automated talk with the specialist can enhance or supplant current selfexpressed character stock methods that cycle applicants may misshape to acknowledge socially suitable impacts.
