Hi,
I'm Varad Kelkar.
Engineer

I'm Varad Kelkar, and I recently graduated with a Bachelor of Engineering in Computers. My academic journey culminated in a research-intensive final year project titled Anomaly Detection Using AI Methods where I explored various algorithms to find the best solutions for detecting anomalies in data.

I'm fascinated by how machine learning and deep learning models can be used to solve existing human problems, and I enjoy working on such challenges.

My skillset includes:
  • Programming Languages: C/C++, Python
  • Web Development: HTML, CSS, JavaScript, ReactJS, NextJS, Flask
  • Machine Learning libraries: Tensorflow, Keras, Scikit-learn
  • Data Visualisation: NumPy, Pandas, Matplotlib, Seaborn
  • Database Management: MySQL
  • Version Control & Management: Git, Jira
  • Quality Assurance: Cucumber, Gherkin
Check out my Projects
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Anomaly Detection using Artificial Intelligence Methods

Research

This research project involved a comprehensive benchmark study of various anomaly detection algorithms on a diverse set of univariate and multivariate datasets. The study compared various types of machine learning and deep learning algorithms. Along with the reserach a web application was developed to visualize and understand the results and compare these algorithms.

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Chest X-Ray image generation using Generative Adversarial Networks (GANs)

Generative Model

The objective is to implement and compare architectures of GANs. The exploration involves 4 GAN architectures: GAN, DCGAN(Deep Convolutional GAN), CGAN(Conditional GAN), and BiGAN(Bidirectional GAN). The primary focus is on conducting a comparative study to assess their efficacy in generating chest X-ray images illustrating both normal and pneumonia affected conditions.

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Disaster Tweet Classification using NLP

Natural Language Processing

Twitter has emerged as a vital communication channel during emergencies, enabling real-time reporting of incidents by individuals. Consequently, various agencies, including disaster relief organizations and news agencies, are keen on programmatically monitoring Twitter to identify and respond to emergencies promptly.However, discerning whether a tweet genuinely pertains to a disaster is not always straightforward.

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Experience

Research Intern | BITS, Goa

Internship, Aug 23 - Feb 24

During my internship and final year project under the guidance of a professor from BITS, Goa, I focused on benchmarking anomaly detection algorithms on univariate and multivariate datasets. I utilized Python and machine learning libraries such as TensorFlow, Keras, and scikit-learn to conduct this research.

SDE Intern | OneShield India

Internship, Aug 23 - Oct 23

During my internship at OneShield India Pvt Ltd, I was part of the Quality Assurance team where I focused on automating test cases for their internal software. I worked with Gherkin, Cucumber, and the BDD approach to ensure comprehensive test coverage. Additionally, I used Selenium IDE for writing test scripts and Git for version control.