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Albert Tai

I am the manager and primary Bioinformatican of the TUCF Genomics Core, overseeing the operation of three deep sequencing instruments (Illumina HiSeq 2500, MiSeq and Roche 454 Titanium FLX), and their associated services. As part of these services, I provide primary and secondary data analysis services, and or training associated with these analysis. Deep sequencing generates a large amount of data per run and data analysis requires a significant amount of computing resources, both processing and analytical storage. The high performance research cluster and its associated storage is an essential tool for myself and the users of core facility. The parallel computing capability allow us to analyze large data sets in a timely manner. It also expedites troubleshooting processes, which sometime require us to test multiple analytical parameters on a single data set. As the amount of data generated in biological research increases, high performance computing resources has become an essential resource. I would certainly hope to see the expansion of this crucial computing resource.

Marco Sammon

I recently finished my undergraduate degree in Quantitative Economics, and I am continuing work on my Senior Honors Thesis with Professor Marcelo Bianconi. Two parts of our research in mathematical finance require intense computing power: solving systems of Black-Scholes equations for implied volatility/implied risk-free rates, and fitting a SUR regression to explain factors that influence the difference between market prices and Black-Scholes prices. Before using the cluster, it took us weeks to process just a few days worth of options data. Now, we are able to work on many days of options data simultaneously, greatly expediting the process. This is important, as it allows us to aggregate a larger time series of data, which allows for much richer analysis.

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