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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Some useful PhD resources : Peer review
Published:
Peer review can be some of the toughest parts of a PhD. These people have written about receiving and giving reviews, even managing to inject some humor into an otherwise stress inducing process.
Some useful PhD resources : Writing and speaking
Published:
Below are some resources I found useful for academic writing and speaking. They range from articles, books and an online course.
Some useful PhD resources
Published:
I found other academics’ writing useful in navigating PhD life and academia in general. So I thought of putting together a list of them.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Modeling task uncertainty for neural processes to meta-learn with fewer tasks
Published in Neurocomputing, 2026
talks
Science Quest data science module
Published:
An introduction to concepts in data science and machine learning for middle and high school students.
Petrichor machine learning workshop
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A hands-on session on machine learning for undergraduates from non-CS backgrounds.
Research Scholar’s Day
Published:
A research talk for a general audience representing my department.
Latex workshop
Published:
An introduction to LaTeX for PhD students.
teaching
Teaching experience
Undergraduate courses, Rajagiri School of Engineering and Technology, Department of Mathematics, 2019
Multivariable calculus, vector calculus, differential equations, complex analysis, linear algebra, discrete mathematics, probability and numerical methods
Teaching assistance
Undergraduate and Postgraduate courses, IIT Palakkad, Department of Data Science, 2023
- Generative Artificial Intelligence (Aug - Nov 2026)
- Introduction to Deep Learning (Jan - May 2026)
- Data Engineering (Aug - Nov 2025)
- Introduction to Programming (Jan - May 2025)
- Data Analytics (Aug - Nov 2024)
- Foundations of Data Science and Machine Learning (Jan - May 2024)
- Data Engineering (Aug - Nov 2023)
- Deep Learning (Jan - May 2023)