Meet Kiyoul Yang

Kiyoul's research is in the field of integrated photonics. Photonics is a fascinating field of physics and engineering that deals with the study and manipulation of light. The ability to control light is an integral part of many modern technologies. For example, computers separated by entire continents are able to communicate with one another through fast light pulses that travel through fiber optic cables spanning the world’s oceans. Beyond telecommunication, the applications of photonics are far-ranging, from self-driving cars to quantum computing to the humble barcode scanner.

To better understand integrated photonics, we can first think about something we interact with everyday: central processing units (CPUs). CPUs, which allow computers to function, are small silicon chips consisting of tiny electronic components that form a conventional integrated circuit (IC) for electrons to move through. Similarly, the systems studied in Kiyoul’s group are small chips consisting of photonic components that form a photonic integrated circuit (PIC) for light to move through. PICs are exciting because they allow researchers to manipulate light in very complex ways without the need for bulky optics equipment that can span several, meter-long optics tables.

In the following interview, Kiyoul takes us through his scientific journey, starting with where his love for science began and closing with what he hopes to accomplish at Harvard—all while offering advice to young students who may be interested in studying quantum science. Our conversation has been edited for ease of reading.

Were there any experiences you had as a child that sparked your interest in science? 

KY: I can think of many different experiences, but a funny and memorable one is when I would watch a Korean drama that had a plot similar to The Big Bang Theory. I was in elementary school at the time and became really interested in the science and technology discussed in the show to the point that it made me more serious about pursuing science and engineering. 

Around the same time, I also remember being fascinated by astronomy. There wasn't a formal educational program for me to learn more about astronomy or other scientific things, so I remember exploring them on my own. For example, I often tried to follow the paths of stars in the sky and estimate the size of the Sun.

How did you end up specializing in photonics?

KY: From my early explorations of astronomy, I realized that I liked light. Fortunately, at the end of high school, I had the opportunity to explore this interest further as an intern at the Bohyun Mountain Optical Astronomy Observatory, located at the top of a 3,600-ft tall mountain in South Korea. I lived there for over a month with scientists and wrote code to analyze massive observation data from Chile. With this data, I identified star light that abruptly became bright and dark due to the gravitational lens effect. This experience furthered my fascination with light and inspired me to study different physics topics when I went college. As I learned more physics and electrical engineering in university, I realized that I was fascinated by solid-state physics, since it was more predictable for me and easier for me to intuitively play with than other topics. Still, I liked light. If you put solid-state physics and light together, you get integrated photonics.

Diving into your graduate school years, how did you remain persistent through challenges in research?

KY: In my prior and on-going research efforts, there is a pretty low probability that my experiments will work as I want them to. There is usually something wrong or something to be improved in them. Sometimes, nothing works in my experiments, and I can’t figure out the reason why. This can be very frustrating since the work to fix things feels like it never ends! Therefore, as I plan my short-term experiments and long-term projects, I spend a good amount of time making a list of possible failures and ways to mitigate them. I do this by asking myself and my students: What would be our worst case? Would that worst case still be acceptable? If not, then let's try to make our worst case slightly better. Then, maybe even the worst case might turn out to be a successful and insightful experiment.

Do you have any mentors or role models that still influence you today? What do you value when it comes to mentorship?

KY: I try to find role models in my immediate environment. Not surprisingly, throughout my prior training, my role models were my PhD and postdoc advisors, Profs. Kerry Vahala and Jelena Vučković. My reasoning is simple: if I can interact with my role models frequently, then I can more effectively learn from them and stay motivated in my own work. With all of my role models, I pay attention to how they do science, interact with their colleagues, and teach their students. Overall, I aim to find someone I can admire for a long time. 

Are there any lessons you learned throughout your PhD that you’d like to share with new graduate students?

KY: The biggest lesson I learned through my PhD is to be persistent and reflective while doing research. For example, if I break down a year of research, I would say that for one month out of the entire year I'm very excited, happy, and getting promising results. But for the rest of the year, I'd probably say research has been difficult. I’m likely telling myself: “I don't know why this device doesn't work, and I don't know how I can improve it.” However, whenever I was faced with these challenges, I learned to reflect on my previous experiences to see if there are any clues that might lead me to a solution for my current problems. So, throughout my PhD experience, I learned how to persevere through research troubles by taking time to carefully reflect on what I’ve learned. 

To transition toward your current research activities, what inspires the work that you do?  

KY: If possible, I want to do my best to deliver photonic technologies that, even several decades from now, are relevant—or possibly integral—to daily life. To be more specific, I believe that photonic devices can be much more scalable than they are today, and I'd like to participate in the mini-revolution.

Diving deeper into your work, one technique that you use in your research is inverse design. As there are differing opinions on the utility of inverse design for designing photonic devices, how would you describe the merits of this approach?

[Editors' note: Inverse design is a new approach for developing novel photonic devices. Unlike forward design, where researchers have a set of device parameters that they want to tune to achieve a desired function in their device, inverse design lets researchers lead with these desired functions and, through computation, work backwards to find a device design that can do those things.]

KY: Currently, most photonic design efforts rely heavily on our physics intuition, which results in functional devices, but with rather simple and often limited capabilities. Additionally, manufacturability and scalability can sometimes be an issue with these intuitive designs. 

My team uses computational optimization to explore the full design space of photonic structures, resulting in scalable devices with advanced capabilities. We computationally optimize a variety of structures, including, but not limited to: frequency converters, vortex beam emitters, and signal multiplexers. We also experimentally research computational optimization for photonics and vice versa.

To wrap up our conversation, could you share your perspective on the future of photonics and quantum research?

KY: Something I think about a lot is: Can we build a photonic system that controls many lasers at once with high precision? While working towards this goal, we can also figure out how to create an effective connection between free-space optics and integrated photonic systems, which would allow for exciting quantum optics, quantum sensing, and quantum communication experiments. Lastly, I believe that we need to co-design photonic systems and electronics to realize scalable technologies that can revolutionize the way we process and share data.

Learn more about Prof. Yang’s research and team through his group website.