IBM University Relations team has a number of programs and I’ve been quite happy to contribute. In 2019, I contributed to IBM Hackathons and Global Remote Mentoring, and was pleasantly surprised when they even invited me to an year end event and recognized my contribution.

So recently, when I learned about other initiatives like Academic Ambassadors and *Keep On Learning*, I wanted to explore them too. And pretty much immediately, they approached me to see if I can give guest lectures on Design and Analysis of Algorithms.

Given that I work on Graphs these days, I suggested a lecture on the *Design and Analysis of Graph Algorithms* instead. That was fine with them and in quick time, they had reached out to partner colleges.

We were delighted when RVCE, Bengaluru and NIE, Mysuru faculty invited me to give guest lectures to students, most of whom are learning from home, because of the ongoing COVID19 pandemic. This was quite in line with the spirit of *Keep On Learning*, even during these stressful times.

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I was first introduced to Algorithms in the first year of my undergraduate program at the University of Madras, using How to Solve It by Computer by R G Dromey. Then we formally learned Design and Analysis of Algorithms from the legendary CLRS text.

When I went to grad school, at The University of Arizona, I excitedly took CS545 Design and Analysis of Algorithms course which was then offered by Prof. Stephen Koborou. And it was one of my biggest mistakes in grad school!!

I’m kidding. But the course was brutal and Prof. Koborou wanted us to learn more advanced graph algorithms. He made the first 6 chapters of CLRS, class reading and went to later chapters!!

Later on, even after I graduated, I’ve kept returning to Algorithm courses taught by Prof. Steven Skiena, Prof. Robert Sedgewick and Prof. Tom Roughgarden. More recently, for my work on Knowledge Graphs, I’ve been closely following the work of Prof. Jure Leskovec.

For my lectures I borrowed heavily from the slides of Prof. Roughgarden and Prof. Leskovec.

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At IBM Research, I have been working on Knowledge Graphs for almost 4 years now. Though I’ve spent more time on Information Extraction in Automatic Knowledge Base Construction. In particular, I work on constructing person knowledge graphs that contain PI/SPI (personal data) of people. You can find our work at [1], [2], [3], [4], [5], [6].

So for the lectures, I decided to present on the topic of “Link Prediction in the Real World”, drawing few examples from our most recent work. Much of the lecture materials were from Algorithms Illuminated by Prof. Roughgarden and these slides on Graph Neural Networks by Prof. Leskovec.

Delivering these lectures was a really good experience! The last time I gave a lecture was in January 2018. Preparing for the lectures, reminded me of grad school! And I hope my lectures were useful to the students who want to *Keep On Learning.* You can find the slides from the lectures at the below location.