Links to various course resources.

This is a list of some resources I used for courses or sessions over the years.

  1. Pytorch for machine learning and computational graph building.

    I taught a week-long course for doctoral students at TU Eindhoven for Pytorch from the ground up. Here’s a link to the repository containing the Jupyter notebooks I used for teaching.

  2. Generating post-hoc explanations for neural networks through concept mapping.

    Here’s a link to the slides I used for my presentation at the Benelux AI conference (BNAIC), 2018. The topic was on concept-mapping, a technique I created that constructs mappings between feature layers of neural networks and interpretable knowledge comprised on input features.

  3. Struc2vec - Learning Node Representations from Structural Identity

    Here’s a link to slides I used for a presentation I gave at a machine learning meetup in the Netherlands, on the topic of struc2vec, a node embedding technique that takes into account the structural identity of nodes.

  4. Computational intelligence

    I also was the teaching assistant for a year for `TI2736A Computational intelligence’, a course at TU Delft. I helped in designing and grading assignments, and helped students with their lab work.


I also volunteered as a English and mathematics teacher for underprivileged high school students at schools in Mumbai for the 2014-15 academic year, through the Make a Difference foundation.