The future of computing lies in the management of data. The term "data" refers not only to structured data, but in a broader sense to semi-structured and unstructured data. In the past three decades, research in information retrieval and data management has already transformed the world.
Extracting value out of semi-structured and unstructured data, however, is
still a problem at large and has huge potential in sculpturing a new computing landscape. There are two parts to this that I am equally passionate about: finding new ways to extract value out of data and building efficient systems that enable the former.
My interest in building systems started in high school, when I co-founded a business offering bulletin board solutions to large-scale websites. I was immersed in exploiting techniques to improve system performance and thrilled that our product outperformed competing solutions. Intrigued by learning more about the design and implementation of highly scalable systems, I joined a team at IBM building a new shared-data distributed database product dubbed DB2 pureScale. My work focuses on the efficient use of buffer pools and algorithms to optimize them in a multi-tiered, distributed context. This experience of building large systems for real clients makes me contemplate about differences between ideal academic settings and reality.
Interested in further pursuing the field of data management, I enrolled in a full year thesis under Professor XXXX's supervision working on a framework for data integration [1]. I implemented a new SQL-like language for specifying linkage between data silos. The framework translates user specified queries in LinQL into SQL, taking into account both syntactic and semantic meaning of data. This research experience has confirmed my understanding about status quo that a large amount of value is buried in all kinds of data and we have yet to find good ways to make use of overwhelming flow of data.
Take emails as an example. Studies show that over 45% of business-critical information resides in email messages . Collectively, emails reflect the behaviors and intrinsic social patterns of the people involved. Nonetheless,with the exception of spam filtering, information in emails is absorbed and consumed only by the human that actually reads them.
With this belief in mind, I spent a period of time researching emails after my graduation. I prototyped ideas to facilitate email searching and the exploration of email social networks. What I had realized is that no single field alone can fulfill the goal. This area is incredibly interdisciplinary.
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（编辑：chole）
