Kavya Tatikonda

Hi, I am Kavya Tatikonda. I am currently pursuing under graduation in Computer Science & Engineering. I feel responsible towards my work. I focus on key results, build amazing teams and quickly adapt to new insights. I love to win, but helping the team win gives me greater joy. I tell great narratives that motivate. I educate, refine and drive myself to be a better person, I am constantly learning because i never settle. I focus on making high-quality decisions. I enjoy meeting new people and hearing new perspectives. Solution-focused Web Developer Intern with experience in web-based applications. Participated in development and implementation of web-based solutions. Supported company business objectives and strategies while gaining real-world experience. Mentored Senior Java Web Developers, learning multiple systems and efficient development techniques.

• Data Analyst Intern, Phoenix Global
• Web Development Training & Internship, Bolt IoT
• Salesforce Administrator Virtual Internship, Salesforce

• Lead Volunteer, National Service Scheme (NSS), 07/2021, Present, COVID Vaccination Awareness Activity (Rural) -2021 NSS Special Camp - Teaching & Career Guidance in Government School - 2022
• NCC (National Cadet Corps), Passed 'A' Certificate exam

• Introduction to Big Data with Spark and Hadoop - IBM
• Introduction to Web Development - University of California, Davis
• Cloud Computing Foundations - Duke University
• Data Analysis with R Programming - Google
• Database Management Essentials - University of Colorado System

Data Mining for Software Repositories with Data Analytics for Feature Extraction and Classification Using Deep Learning Model

Project 1: Toxic comment Classification model

Understanding the harmful effects of tainted comments on individuals, such as hurtful insults and bullying. Developed a robust classification model to identify toxic words accurately to create safe, online environment. We built the UI by deploying the model to make it flexible for the users. 

Project 2: Detection of phishing websites using Machine Learning

We developed a system to protect users from phishing websites that aim to steal their personal information. Our advanced model analyzes website URLs to distinguish between legitimate and fake sites. What sets our system apart is its long-term effectiveness, remaining accurate for at least 50 years without relying on specific data. We created a user-friendly interface where users can input a URL and receive instant information about its safety, along with our model's accuracy rating.

A Two - Day International Workshop on Machine Learning Applications for a Better Society, Department of Computer Science and Engineering, GITAM Institute of Technology, GITAM DEEMED TO BE UNIVERSITY, VISAKHAPATNAM, INDIA,