A loud controlled roar sounds as the engine revs up. The V-6 twin turbo engine was the source of the ruckus sound. It was audacious and powerful, with signature aesthetics. The carbon wheel arches are not only a stylistic choice, but helps strengthening the car body by making it more rigid. The iconic spoilers give the car a distinct look while also allowing the vehicle to become more aerodynamic. The Nissan GT-R is a truly an amazing feat in engineering. From a young age, I was obsessed with cars, their designs, and the way they were carefully conceived and constructed. Overtime, as I sped through my childhood and then adolescence, I discovered mechanical engineering as the driver behind the creation and design of almost all things. My interest in the subject came quickly and suddenly.
Analysis such as that in the form of an AHP matrix had to be done before we could proceed with design; various boxes needed to be checked, such as overall functionality and quality, efficient kinetic energy capture and storage, cost of production, amongst other factors. Efficient energy capture through the blade and rotor design was the most important factor, as it would influence other factors such as costs and overall functionality. Thus, we made it a major focus. Copious amount of work was done to find the optimal target after charting angular velocity versus torque. Later on, blade design had to filter through various sub-factors such as stability and manufacturability. The beta prototype would ultimately prevent crop destruction and preserve the elephant population in Kenya. The tremendous experience reinforced my passion for the subject that also enlightened me to the possibility of creating a more sustainable world through mechanical engineering.
During my junior year, I took part in the Discovery Park Undergraduate Research internship with Professor Austin Toombs in the field of human-computer interaction (HCI). The focus of the project was to analyze HCI in platforms in today’s shared economy, namely Uber and Lyft. The goal was to gain a deeper understanding of the social-technical systems behind these behemoths in today’s shared economy. The study was done from the driver’s perspective as we wanted to study and evaluate the impact of automation and technological innovation on an employee’s support and experience on the platforms as well as changes in employer responsibility. One point of interest in this research project was the work and analysis of autoethnographic data and different forms of metadata. These unconventional forms of information had to be compiled, grouped, and parsed in a fashion in order to derive quantitative metrics from them. We measured conventional statistics such as income, and overall money earned from Uber versus Lyft. In addition, we also logged overall driving summaries and tracking the frequency of request to feedback receipts, and even applied Linguistic Inquiry and Word Count analysis (LIWC) on various communications with the companies.
From a high level, the biggest takeaway from the study was the major role that different HCI qualities played in the perceptions of the underlying companies. There were stark contrasts between the two platforms’ styles and messaging that ultimately drove that difference in perception. Further studies are warranted so we can further analyze our autoethnographic notes and explore in greater depth the linguistic differences beyond the dimensions captured by LIWC. The study also confirmed my belief that effective HCI played a critical role in creating effective automation.
Although financial education has been a great interest of mine, I have also displayed a knack for quantitative classes as I earned the highest honors in courses such as Mathematical Analysis III and Probabilities and Statistics. Eventually, I expanded upon my classroom knowledge by working in CICC’s quantitative trading department where I honed my analytical and technical abilities. I built a number of trading tools with VBA macros that automated various trading and market data collection processes. I also worked on FX valuation models that helped the traders to pin-point the mid-price of FX forwards using academic concepts such as covered interest rate parity. During my internship, I realized the immense impact that applied analytics had for businesses. Quantitative methods and analytics could help optimize revenue generation and lower costs. During my internship, I worked with the team to code in VBA two types of checks that helped ensured data quality. First, running a regression to pinpoint outliers greatly narrowed the amount of data to be manually checked. In addition, in incidences when there were two sources of the same data, we built simple verifications between the two sources to spot potential discrepancies for further investigation.
I continued down this path further with my most recent internship with China’s Nation Bureau of Statistics. With this institution, I worked in various capacities ranging from high level analysis to meticulous maintenance of data. For example, I helped the team by using a variety of economic data to model the potential paths of Chinese unemployment rates by using multi-factor analysis and regression techniques based on industrial production, costs of living, seasonality fluctuations, labor force and population trends, amongst others. In total, over 40 factors were implemented in our model. In terms of the low level work I was also responsible for, I worked often with inflation data, gathering, normalizing, cleaning, and categorizing various inflation data from different municipalities, regarding different goods. The data sources were extensive and diverse as we drew information for the prices of countless goods from many regions. This was also an important task, as the bureau was a government entity and thus needed all its information to be correctly normalized, with high levels of integrity as these were all inputs used to create the national CPI index.
My grandma is an avid stock investor. When I lived with her when I was younger, I would always hear her complaint such as “I could have avoided the loss if I sold the stock a bit earlier” or “I could have made so much if I bought the stock a bit earlier”. I heard the same complaint for so many times throughout the summer that I started wondering what went wrong with people’s decision making process while trading stocks.I had a misconception that the stock market is controlled by computers. In fact, humans are the masterminds behind the stock market. There is a tendency for people to overanalyze the quantitative side of the stock market, and overlook the importance of human nature such as fear and greed, and the human decision making process. Psychology is so relevant to the topic of economics and finance; as a stock investor, I realize that I cannot maximize my return until I have a good understanding of the human thinking process. As a result, I’d like to study behavioral economics at the Wharton School.
Mathematics has been my passion since I was a child. The crux of mathematics is based in logic, something that I had a strong knack for even at a young age. Initially, it was my success in the subject that fueled my continued interest. As I learned more and more about the subjects of mathematics and statistics, I realized the tremendous depth and utility of the subject. The numbers and figures in any statistical study provide explanation and substance behind different stories. Thus, statistical analysis and studies can be used as a powerful tool to explain phenomena and other worldly occurrences. Furthermore, I am passionate about the subject as it acts as a light of truth that can shine even in the darkest of situations. The numbers will always display true relationships and detail an accurate account of past events. The illuminating power of math and statistics is self-evident. Understanding math and statistics is the key to ultimately understanding and using those numbers. This drove my passion to new heights.