About Heesun Lee

I am a master’s student of Computer Science in Rochester Institute of Technology.

I do not limit my skills. I flexibly adopt new skills whenever I need them.

My academic objectives in a master’s program are to publish at least one thesis that is accepted by an international conference.

My research interests are in the areas of intelligent systems, and cloud computing.

I would like to develop a theory on effectively adopting artificial intelligence techniques in the course of designing, implementing, operating, and maintaining an actual web service. Also, I am eager to explore how massive, complicated computations affect the performance of running web systems in the long term and how to improve it, while fully leveraging the benefit of updated research. I am currently interested in applying machine learning techniques to security solutions.

I aspire to find answers to fundamental questions related to artificial intelligence. Specifically, I hope to establish a theory explaining the processes and results of training in deep learning. Based on this theory, I would like to clarify why and how human engineers achieved certain results, especially in real-time and safety-critical systems.

My motivation for pursuing the above research stemmed from learning about fundamental problems with current deep learning methodologies. First, the way people study deep learning is close to empiricism and lacks adaptability. Regarding data that a deep learning model has not yet experienced, the error rate rises significantly. Secondly, to train one deep learning model, we need enormous data and time. To overcome the above limitations, I will integrate deep learning (which excels at classification) with symbolic systems (which are good at inference and generalization).

While working for a company, I mainly developed firmware and network middleware. I experienced various tasks such as exterior API utilization, test code writing, technical document composition, and prototype development using Arduino. Although I do not define myself with a few computer languages, I mostly used C, C++, Python, Java in the company.

To pursue my intended fields of study and for fun, I have spent my time reading various theses, acquiring practical programming, math, and theory, and taking online courses. These courses have addressed web programming with various languages and frameworks, cloud server implementation, mobile application development, financial engineering, deep learning, and artificial intelligence. Through practical knowledge and concepts, I was able to broaden and deepen my background in computing for future research.

While volunteering for the “Artificial Intelligence for Non-Computer Science Majors” program, it was delightful to share my technical skills with students and see their improvement. Most students were adults and unfamiliar with programming. During the course, I helped them to combine their domain knowledge with concepts of machine learning. This experience showed me that bringing STEM education to a diverse population is eminently feasible as well. This was what made me certain that I would be a good educator.