When working with sequencing datasets of ecological interest, an interesting problem is how to tease out the genetic diversity present in the population being sequenced. Usually, assembly software simply aligns the short read sequences, and determines the consensus sequence based on the majority vote of each position. However, we may wish to seperately assemble each haplotype (version) of each gene. We formulate this as a graph problem, where short reads that overlap are considered nodes in a graph that share an edge if they should go in different haplotypes.

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Some extended family got married in Jamaica, I did some photography for them.

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A few fun things I don’t want to lose.

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I did this project with Mike Olson, a Notre Dame graduate student. (He’s narrating the video.) We studied the proper design of user interfaces in this class. Although we mostly focused on graphical interfaces, we also learned how to interface with motion-based systems such as the Nintendo Wii remote and Balance Board. For our final project, we wanted to design an interactive browser for the Microsoft Surface, a multitouch based coffeetable like device.

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This class was very interesting; we studied some of the basics of online algorithms as well as some applications to computational finance. Perhaps the most intriguing parts (for someone already familiar with online algorithms) were what we learned about classic computational finance, such as Black-Scholes-Merton. This “project” is a review of the main result of an interesting paper, entitled “Making Decisions in the Face of Uncertainty: How to Pick a Winner Almost Every Time,” by Awerbuch et al.

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Much of the research I performed during my Master’s was on the newsvendor problem, which deals with attempting to guess the demand for short-lived products so as to maximize profits. Unfortunately, data about newspaper sales is tough to come by. So, why not use an online equivalent? This project aims at predicting the number of comments a Slashdot story will generate given text which appears in the summary. However, since we are interested in looking at the number of comments as a demand for a product to be sold, we don’t stop there.

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Machine learning methods and inventory management were a focus in my Master’s work. In the newsvendor problem, an amount of product to order must be decided upon periodically for reselling. Ordering too much results in losses due to overstock which must be discarded; too little results in losses due to lost sales. Traditional approaches experience a tradeoff in that some methods perform better in some situations, while our machine learning approach performs well consistently, particularly in situations where the demand suddenly increases or decreases.

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This was a project I did for Cryptography, which implemented a digital cash scheme as a web service. The idea behind digital cash is that, well, it’s digital cash. Which means, it’s a digital object which has value and can be traded/spent, but is also anonymous. This is accomplished via digital signatures. Alice, who has money in the bank, sends the bank an string of random letters and an amount to withdraw.

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