Get to know: Gokul Ravi

Gokul Ravi is an assistant professor who joined the CSE faculty in Fall 2023. His research interests lie primarily in the area of quantum computing, including quantum computing systems and architectures, as well as the intersection between classical and quantum computing.

Before coming to the University of Michigan, Gokul was an NSF Computing Innovation Fellow at the University of Chicago. He completed his PhD in computer architecture at the University of Wisconsin-Madison in 2020.

Gokul has been recognized widely for his research, including winning best paper awards at leading conferences such as HPCA and IEEE Quantum Week. Most recently, he was recognized with the Innovation Award in the Quantum Computing for Drug Discovery Challenge at ICCAD 2023.

We recently spoke with Gokul to learn a bit more about his research interests and goals.

What are the key research problems that motivate your work?

Over the past decade, quantum computing has begun to transition from lab curiosity to practical (and nearly useful) reality. However, as we advance into this era of practical utility, it is critical to bridge the wide gap between the theoretical requirements of numerous quantum applications and the inherent limitations of quantum computers. Only then can we unlock the full potential of quantum computing to achieve meaningful benefits in real-world applications with imperfect quantum technology. My research is motivated by this theory-to-experiment gap. As a quantum computing architect, I am helping to build a computing ecosystem that actively enhances the capabilities of quantum systems, in a manner well acquainted with application requirements.

What’s unique about your approach to tackling these problems?

Building practically useful large-scale quantum systems critically requires contributions from the classical computing world. Classical computing researchers are adept at bridging the information gap between different layers of the computing stack and have progressively accumulated expertise in designing tightly constrained, highly optimized classical systems. Unlike most researchers in this space, I am a computer architect trained thoroughly in both classical (during my PhD) and quantum (during my postdoc) computing. Therefore, I bring a unique perspective to designing quantum computing systems: I leverage classical computing principles, both explicitly and implicitly, to build toward a hybrid computing ecosystem for practical quantum advantage.

How do you see your work impacting society at large?

I aim to do meaningful research that will hopefully have a lasting positive impact on technology and society. I believe that the potential for such impact is especially high in nascent/emerging areas of computing. Among many promising emerging areas, I was drawn toward quantum computing because it is a disruptive technological paradigm with the potential to revolutionize computing and, therefore, the world. It lays a powerful foundation for tackling today’s urgent problems, as well as tomorrow’s emerging challenges. For example, the Covid-19 pandemic highlighted the need to vastly improve our ability to rapidly develop drugs to combat diseases. If quantum computing is able to live up to its incredible potential, it can considerably accelerate the drug development process. Similarly, it can impact other domains of critical interest, such as carbon fixation, forecasting, supply chain, cybersecurity, and machine learning. However, there is still a long and challenging journey ahead, and I hope I can make impactful contributions along the way.

What are your future goals with regard to research?

The opportunities for classical architects in quantum computing are vast: technology-aware circuit compilation, application-tailored quantum error mitigation, classical processing to bootstrap quantum execution, latency/bandwidth/power constrained classical hardware design to support quantum (for example, for quantum error correction), scalable classical simulation of quantum systems, multi-chip strategies, cloud resource management, feedback-based (potentially ML-aided) optimization, benchmarking, automated design space exploration, and much more. My research broadly encompasses these areas, but I am particularly excited about ideas that enable the seamless migration from today’s Noisy Intermediate Scale Quantum (NISQ) systems to futuristic systems for Fault Tolerant Quantum Computing (FTQC).

What’s most important to you as a mentor to graduate students?

It is important to me that my students enjoy what they do and their day-to-day academic life is something they look forward to and not an arduous, overbearing task. After all, students are investing a significant portion of their young adult life in graduate school, and they deserve it to be fulfilling, both academically and otherwise. From a mentoring perspective, I strive to understand each student’s unique set of skills, strengths, and weaknesses, and adapt according to their needs. Some students prefer to be more independent in how they pursue their research and I try to provide them with as much freedom as possible, as long as they are progressing well with their research and coursework, and contributing toward my broader research goals. On the other hand, some students like more hands-on mentorship and I am happy to oblige, at least until they reach a senior level in the PhD program. I do expect and encourage independence in the latter stages of the PhD as this is vital in the “real” world, irrespective of the career the student wishes to pursue. I try to maintain honest and direct communication with my students so that we can understand and respect each other’s expectations and goals at all times.

What do you expect from the students you work with?

The high-level expectation is that students diligently pursue impactful research. Since I broadly work in quantum computing and related topics, I expect my students to be excited by this domain and want to actively contribute to it. The research focus area itself can be fairly diverse and students can get a sense of my broad interests by browsing through my publications and/or by talking to me. Students are expected to make active progress in their research and I expect weekly updates (with reasonable flexibility). It is often challenging to measure progress objectively, but it would ideally involve reading literature, proposing new ideas, implementing proposed ideas, evaluating implemented ideas, writing papers, presenting work, etc. Progress, of course, will not always be ideal and that is understandable. Therefore, it is important to me that I maintain regular communication with my students so that I can understand and support them to the best of my ability.

When you’re not thinking about computer science, what else do you do?

I am an avid sports fan, so I am closely following football every week (Go Pack Go!) or waking up at odd times to watch cricket, my first love. I am passionate about fostering cats and dogs; I’ve fostered ~10 of them in the past three years. In warmer weather, I enjoy exploring nature while listening to podcasts or rock music.