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Supervisor

Dr. Roberto Solis-Oba

About

I am a full-time PhD student in the Department of Computer Science at The University of Western Ontario. I like the Toronto Blue Jays (though it still stings a bit to see Roy Halladay in a Phillies uniform), my dog, programming in Ruby, hacking in Linux, and teaching Computer Science, but not necessarily in that order.

I have about 6 years of industry experience in various technical roles, so I'd like to think I can practice what I preach. My time in industry includes a 16-month internship with IBM Canada as a software developer for a technical marketing team. For those undergrads in second and third year, I strongly recommend you check out the industry internship program. Yes, it delays your degree by a year, but you will learn a lot from the experience, and will be more appealing to employers after you graduate. A number of people have come by to talk to me about it — I encourage you to do the same if you think you might be interested in doing an internship.

I submit to you that no self-respecting programmer should ever sit down to code with his/her toes constrained by socks and/or shoes in a world in which Birkenstocks exist, lest his/her creativity be impeded. While I recognize it as a fashion faux-pas, I am not above the donning of socks and sandals, should the weather be inappropriate for sandals alone. Let me be clear, however — I am not a hippie. My desire to produce wonderfully inspired, toes-liberated code simply exceeds my desire to be stylish.

I also have a penchant for berating students for submitting poorly formatted assignments, and suggest they use my Computer Science Assignment Wizard to format their assignments. :)

You can learn more about me on my LinkedIn profile.

Research

I am currently studying graph algorithms to identify similar nodes in citation graphs produced from citations in scientific literature. You might say I'm doing research on research itself. The goal of the research is to produce a set of algorithms that can identify publications highly relevant to a given publication, reducing the amount of time researchers need to spend on a literature search.

This work also has applications on the World Wide Web and social networks. For instance, a keyword-based search on a search engine like Google will yield us results that Google deems to be related to the terms we have entered. However, what if we are on a particular page, and we want to find pages relevant to the material contained within the page? We could extract certain keywords from the page, and then use a search engine to find other pages with those terms. However, because many authors use different terms to explain the same concepts, this may lead us to exclude many highly relevant results. Instead, a reasonable technique would be to examine the links between web pages, and attempt to discern collections of relevant pages based on the link structure of the Web graph. This is the basic idea behind many link analysis algorithms, such as Jon Kleinberg's HITS.

By the way, for you undergrads out there, graph theory is cool. I didn't realize how cool it was until I took Roberto's Analysis of Algorithms II course. Not only is the material extremely fascinating, but Roberto has a knack for explaining difficult concepts in a way you just understand. I highly recommend it! Sites like Facebook, LinkedIn, Twitter, and many others all heavily rely on graph algorithms to help us connect. So, don't make the mistake of thinking this is simply an area of theoretical interest.

Publications

Teaching

Lecturer

Teaching Assistant

Talks / Presentations

Projects

Things I've Made

Selected Awards

Selected xkcd Favourites

Other Things I Find Amusing