Pre-RTCL: Why Real-Time Systems?#

Motivation#

My major is Applied Statistics, and I had been primarily studying data analysis. After taking an Operating Systems course and learning about data engineering, I became interested in systems in general, which led me to start a double major in Computer Science in the second semester (25-2).

I had explored various areas including cloud systems and AI systems, but I was left wanting deeper, more focused study. This semester (25-2), while taking a Real-Time Systems course, I found it fascinating to design and optimize systems under clear constraints — limited resources and strict deadlines. I was drawn to the process of synthesizing various system-level knowledge to derive solutions in well-defined problem spaces. I also believed that these design principles from real-time systems could extend to areas I care about, such as AI systems and cloud environments.

Why I Got Into Computer Science#

Taking the Operating Systems course sparked my interest in how programs run at the process level. I found it fascinating to learn how multiple tasks are defined at the OS level and how they are managed based on different criteria.

Why Real-Time Systems Interest Me#

After developing an interest in operating systems, I began exploring how things work at the system level. While studying these topics, I took a Real-Time Systems course and found it exciting to run tasks under more specific and constrained conditions. The idea of handling computation under limited resources and hard deadlines was inherently interesting to me.

Areas That Excited Me#

The real-time systems research I looked into revolved around the question of how to schedule multiple tasks while guaranteeing real-time constraints. I understood that research is being conducted from various perspectives — how to schedule parallel tasks efficiently on edge devices, embedded devices, and with resource efficiency in mind. Additionally, I learned that for tasks like AI inference, research explores the tradeoff between accuracy and deadline satisfaction.

I was also intrigued by research on guaranteeing real-time behavior at the OS level, particularly in the context of ROS.

Thoughts on Career Direction#

Through my experience in development, I realized that while building better programs is certainly a goal, what I really want is to create programs that are more precise and system-efficient. To achieve this, rather than pursuing a career as a developer, I want to conduct research that can also be applied to practical domains. At this point, I am committed to pursuing a master’s degree, and I want to decide about a PhD after gaining actual research experience.

What I Have Been Doing#

Through taking courses across systems topics, I have been studying how programs actually run. In this process, I became curious not just about implementing things, but about how to build programs that are efficient at the computer systems level. There are still many courses I want to take, and I feel excited about what’s ahead.

My projects have been mostly implementation-focused:

  • AI services using RAG (dinner recommendations, legal risk assessment, form filling)
  • Home LLM inference server setup
  • Hazard detection robot system using ROS2 and YOLO

Through these projects, I realized that my interest lies not only in implementation but more in the systems-level approach.