Sharan Babu is a B.Tech student in Computer Science with skills in Python, Keras, TensorFlow, and Flutter. He has internship experience writing Python articles and personal projects including gaze estimation desktop navigation using OpenCV and deep learning, predicting PUBG player win percentage from game data using regression algorithms, and an income classification model served as an API using Random Forest and Logistic Regression. His certifications include Python for Data Science from NPTEL and Deep Learning with TensorFlow from Coursera. He was a top 16 participant in the IBM Nasscom Crack the Covid Hackathon and won Best Undergraduate Hack at Bit Hacks for a gaze-based AI desktop navigation system.

1. SHARAN BABU
Portfolio: https://sharan-babu.github.io/ LinkedIn: sharan-babu-39a757197/
Email: sharanbabu2001@gmail.com Mobile: 9052337437
EDUCATION
B.V. Raju Institute of Technology Narsapur, (2019–Present)
- Bachelor of Technology (Computer Science)
- CGPA: 8.85/10
The Secunderabad Public School Secunderabad, (2017–2019)
- Higher Secondary
- CGPA: 8.92/10
SKILLS
Programming: C, Dart, Python – Keras, TensorFlow 2.0, scikit-learn, opencv, numpy, pandas, seaborn
Database: MySql
Others: Flutter, Git, Firebase
INTERNSHIP
Python Intern at CodeSpeedy Technology (5 February 2020 –25 March 2020)
Work from Home
- Article writing on Python based libraries and applications after thorough study of topic.
- Topics ranging from calculating domain age of a webpage to implementing progress bars in Python.
- Submitted a total of 20 articles within the stipulated time period.
PERSONAL PROJECTS
Gaze Estimation for Desktop Navigation (June 2020)
- A Deep Learning Python application that enables users to control the desktop using their eyes.
- Used OpenVino Pre-trained Gaze Estimation models and libraries like opencv, dlib for blink detection.
- User friendly GUI implemented using PyQt5 library.
- Efficient and Comfortable than the existing Head Pose estimation solutions.
PUBG Win Percentage Prediction (May 2020)
- Derived meaningful insights through exploratory data analysis on 4 million record dataset using matplotlib
and seaborn libraries.
- Predicted ‘win percentage’ and rank of a PUBG player based on player’s previous game play data.
- Used Feature Engineering Techniques to improve accuracy by 7%.
- Regression problem solved using algorithms like Linear Regression and Random Forest Regression.
Income Classification
Link: https://income-classification-model.herokuapp.com/ (April 2020)
- Determined Income of a Person provided various features using various classification algorithms.
- Model served as API using Flask and Heroku.
- Used Random Forest Classification and Logistic Regression to predict outcome.
CERTIFICATIONS
- Python for Data Science, NPTEL, IIT-Madras
- AI for Everyone , Coursera
- Deep Learning with TensorFlow Specialization ,Coursera
AWARDS
IBM Nasscom Crack the Covid National Hackathon
- Top 16 among 26,000 nationwide participants.
- Built a Flutter cross-platform application that aimed to cater to psychological needs of people due to the pandemic.
Bit Hacks International Hackathon – Best Undergraduate Hack
Link: https://github.com/Sharan-Babu/Gaze-Estimation--BitHacks-Hackathon
- Used TensorFlow and OpenVino model to build an AI Desktop Navigation system that helps people use their
electronic devices with only their eyes.