Portfolio item number 1
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portfolio
Portfolio item number 2
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projects
Predicting ATP binding sites for protein sequences
Creating a model for protein-ATP binding sites prediction based on sequence information.
Comparative study of learning approaches
Compared supervised, semi-supervised and self-supervised approaches on image classification task on STL 10 dataset. Used a ResNet-18 model for supervised, vanilla CNN for semi-supervised and SimCLR for unsupervised learning.
Meta learning library using JAX
This project aims to implement various Meta Learning methods and benchmark them on few-shot learning tasks. The goal is to build a modular extensible and well documented library of these methods in JAX.
Probing language inference models
Trained a classifier model on SNLI Dataset to determine the inference relationship between the sentence pairs and performed probing on thee model’s layers for POS tags.
Source code synthesis
Developing a model to perform code search, syntax error detection and code repair on different programming languages.
publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
CTE Instructor-Introduction and Applications of Machine Learning
Introductory course, BITS Pilani, 2021
The course intends to help students with no experience in machine learning take their first steps in the field. We will start off with the basic Machine learning theory and look into essential tools needed for ML; libraries like numpy and pandas. Then we will proceed to teach the students about various machine learning algorithms, the maths behind it. With the help of scikit learn, the students will learn how to implement various models as well.