Statement of Purpose (Master of Computer and Information Technology)
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As a business school student surrounded by suit-up colleagues, my dream, however, has always been to become a university professor. I want to devote myself to pushing the academic frontier then contributing the research back to the students or daily business operations. After three years of exploration and one accidental discovery of the importance of computer science in business, I’d like to share a story about how I want to further that dream by steering my academic interests towards computer science, specifically in data-related fields by joining University of Pennsylvania as a Master of Computer and Information Technology (MCIT) candidate.
One night in my sophomore year, I was burning the midnight oil preparing a business project presentation about cost evaluation of product design processes. While searching for references, I found a thesis on such evaluation through a machine learning approach based on computer science knowledge. Upon diving in, I came across something named “VAE model” which was able to significantly reduce the costs by incorporating computational skills. Immediately fascinated by this potential applicability into the business world, I was simultaneously confused about how computer scientists managed to harness algorithms for processing the complex business data. My confusion turned into a sleepless night sipping coffee and researching more –with limited resources, I came up with many exciting questions to solve but did not know how.
Early next morning, I went to my professors for answers. To my surprise, all professors shrugged, claiming they knew little on business data with in-depth computer knowledge, and perhaps the business school is not the best place for such consultancies.
Coming out of the office, I felt a pity that even the most avant-garde business school in China has yet to realize the significance of incorporating interdisciplinary computer science knowledge into the education system. It could have benefited the scholars, especially for preparing us about a future where big data processing is paramount to business understanding. Frustrated but still captivated by such knowledge, I therefore spent nights and days looking for coding and data mining lessons online.
Even with limited entry-level knowledge, I knew diving directly into real research application will help me learn faster. Therefore, I took the opportunity to conduct an independent research supervised by Dr. Wang Xiaoning who is a PhD candidate at Wharton. With his guidance, I initiated a project themed on “Does Data Analytics Contribute in Startups Valuation?”. From capturing to processing massive data from the global venture capital market, I learned how computer science can be applied to business analysis through techniques like natural language processing, text matching and web crawling. Furthermore, I am proud to see myself currently preparing a manuscript for future publication which can be applied by start-ups that are interested in expanding their data analysis departments.
Till this point, I felt like I had reached the ceilings of what I could learn: I constantly found my code inefficient and my algorithm methodologies problematic. After a comprehensive research on the universities that provide CS departments, I found UPenn’s MCIT degree perfectly designed for a student like me with little prior institutional education.
Without any systematic training in the field, I believe courses like Introduction to Computer Systems taught by Dr. Thomas Farmer and course Algorithms & Computation taught by Dr. Arvind Bhusnurmath will introduce me a wide range of computational solutions. After laying out some theoretical foundation, I’d like to take higher level classes like Machine Learning taught by Dr. Lyle Ungar and Artificial Intelligence taught by Dr. Chris Callison-Burch. Here, I believe I can better understand these courses’ focus on prediction and clustering in higher dimensional data with my mathematical knowledge on areas like probability theory or linear algebra. To further build my interdisciplinary involvement, I plan to stay connected to business as a specialty by participating classes or activities in the school of Wharton. Moreover, Warren Center for Network & Data Sciences is an ideal research place for me, where it fosters research and innovation in interconnected social, economic and technological sectors.
If I am admitted to the program, I would love to share my personal experiences back to the SEAS community. For one, I am ready to apply for more TA positions: my experiences as assistants to my previous professors not just made me realize my passion for teaching, but also the importance of communication between the faculty and students. Simultaneously, I believe our physical well-being is just as important. With my experience as the captain of Tsinghua University’s swimming team, I always find organizing swimming workouts, water polos, or the outdoor barbeque sessions afterwards fun and healthy for my colleagues who are used to sitting in front of computers all day long.
Upon graduating from University of Pennsylvania as a MCIT candidate, I aspire to become a female educator with experiences in both computer science and business. I wish to continue researching on the interdisciplinary domains, so that my academic input will not only inspire different industries, but those students like I once was – the late-night coffee sippers, willing to climb mountains to go beyond their majors, but didn’t quite know how.
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