Lin (Robin) Sun

Lin (Robin) Sun
PhD Program
College of Engineering
Huai’an, Jiangsu Province, China

What inspired you to pursue graduate school?
One of my earliest memories from learning English was being asked, “What do you want to be when you grow up?” I wanted to say “engineer,” but I could not remember how to pronounce it, so I answered “doctor” instead. Much later, after years of engineering work, I realized that what I truly wanted was to become a doctor in another sense—someone who builds, questions, and pursues deeper understanding through critical thinking. Graduate school became the place where those two paths came together.

Why did you choose your current program or area of study?
I was drawn to computers from a young age, especially during the rise of the internet. That early fascination gradually became a deeper interest in computer science and systems research. Today, as computing continues to evolve through cloud infrastructure and AI, this field offers a rare opportunity not only to build useful technology, but also to explore fundamental questions that will shape the future.

What motivates you on challenging days in graduate school?
What motivates me is the desire to get closer to the truth. Truth is worth time, effort, and persistence. It is often difficult to find and even harder to face, but even a small piece of it makes the struggle meaningful.

Please provide a brief description of your research or current project.
My research focuses on workload co-scheduling in multi-tenant cloud datacenters, where workloads are overcommitted and colocated to improve infrastructure utilization. I study how to coordinate shared resources more efficiently while preserving performance, especially for latency-sensitive services.

What impact do you hope your research or work will have?
I hope my work helps cloud systems deliver significantly more useful output with fewer resources. More broadly, I want to improve efficiency at the systems level so that computing infrastructure becomes both more powerful and more cost-effective.

What has been your favorite part of your graduate experience so far?
My favorite part has been the moment when a difficult idea suddenly becomes clear. One especially meaningful experience was finding a way to extend an existing systems model so that it could apply to more realistic settings. That kind of breakthrough is what makes research deeply rewarding to me.

What achievement during grad school are you most proud of?
I am proud that I received three internship offers in a row from the same team at Uber. To me, that reflected both technical growth and the trust I was able to build through my work.

What is the biggest lesson you’ve learned as a graduate student?
The biggest lesson I have learned is that in systems research, choosing the right problem is usually more valuable than years of hard work on the wrong one.

How has your perspective on your field changed since you started your program?
When I began my first project, I approached systems research from a builder’s perspective. Instead of using simple scripts and terminal-based testing, I spent weeks building a polished interface to orchestrate experiments. Over time, I learned that the real value of evaluation lies not in how sophisticated it looks, but in how carefully it measures performance, isolates variables, and tests the system under realistic, high-load conditions. That shift changed how I think about research quality and scientific rigor.

What career path are you hoping to pursue after graduation?
After graduation, I hope to pursue a research-oriented career where I can continue working on impactful systems problems. I am especially interested in opportunities in both academia and industry research environments, with a long-term goal of contributing meaningful ideas that influence the future of computing.