Featured Spotlight: Yuxuan Yin – PhD student in Computer Engineering

In Yuxuan’s own words – Interviewed during 2026 year

• Hometown: I was born in Beijing, China.
• Previous Degrees: Prior to UCSB, I acquired a B.Eng in Electronic Engineering and a B.Sci in Applied Mathematics (double major) from Tsinghua University.
• Degree Sought from UCSB: 5th-year PhD candidate
• Advisor / Lab or Group Name: Professor Peng Li
• ECE Research Area: Computer Engineering
• Hobbies and Interests: Piano, indie games

Yuxuan’s Research

• Main Area of Research: Artificial Intelligence, Electronic Design Automation
• Research Interests: Large Language Models, Agentic AI, Machine Learning, Uncertainty Quantification
• Important Conferences: International Conference on Machine Learning (ICML), Design Automation Conference (DAC), International Conference on Computer-Aided Design (ICCAD)
• Important Awards & Honors: ICML Spotlight Paper
• Yuxuan’s Personal Website
• Yuxuan’s Google Scholar
• Publications:
  • [ICCAD'24] *Yuxuan Yin, *Yu Wang, Boxun Xu, and Peng Li, “ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models,” in Proc. of IEEE/ACM International Conference on Computer-Aided Design
  • [ICML'24] Yuxuan Yin, Yu Wang, and Peng Li, “High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling,” International Conference on Machine Learning (ICML)

Favorite things about

• Department: What I love most about the ECE department is its faculty and research vibe. People are genuinely excited about what they're working on. It makes it easy to stay motivated even during the harder stretches of a PhD.
• UCSB: The beautiful campus is my favorite. It only takes 5 minutes to walk to Campus Point Beach from my office!
• Santa Barbara: I love the mild climate and the ocean views Santa Barbara has to offer. Downtown is also a great place to decompress after a long week, with good food and a relaxed atmosphere.

Yuxuan’s research

Tell us about your research: My research sits at the intersection of agentic AI and reliable machine learning: things like LLM-driven automation for analog circuit design, uncertainty quantification, and long-context modeling. The goal is to make machine learning systems that are not just accurate, but actually trustworthy enough to deploy in high-stakes hardware and engineering settings.

How and why did you get into your area of research?  My background in both electronic engineering and mathematics naturally pulled me toward ML problems that have real hardware implications. I am interested in the gap between how well models perform on benchmarks versus how reliably they behave on real-world tasks. That tension between capability and reliability is what keeps me going.

Why did you select UCSB and CE in regard to your research? Prof. Peng Li's group was a natural fit for my research interests, and his personality left a strong impression on me when we first connected. Beyond that, UCSB's Computer Engineering program has a great reputation and a research culture that spans both theory and application, which is exactly the kind of environment I was looking for.

What do you find rewarding about your research? The rewards come from a lot of different places: learning something new, coming up with a novel idea that actually works, hitting a performance milestone, getting that paper acceptance notification, and ultimately seeing the work deployed in a real industrial setting. Each of those moments hits differently, but they all remind you why the grind is worth it.

Thoughts on working in a group research environment: Working with Prof. Li has taught me how to think about research problems at multiple levels of abstraction: from the theoretical framing down to the implementation details. Discussion with labmates helps me to articulate ideas clearly, as well as to get invaluable feedback and insights.

UCSB Prides itself on its collaborative atmosphere, give some examples of how you collaborate: I've collaborated closely with researchers at NXP Semiconductors through two internships, translating academic ML methods into production-relevant tools for chip reliability prediction. 

Academics at UCSB

Strengths of the graduate program: The program does a great job of balancing strong theoretical foundations with research that has real-world relevance: you're never too far from either end. The faculty are also genuinely accessible, which makes a big difference when you're navigating the early stages of your PhD.

Favorite course: My favorite course was ECE 272, Machine Learning in Design and Test Automation, taught by Prof. Li-C Wang. What made it stand out was the combination of rigorous theoretical analysis and concrete real-world examples. It bridged the gap between ML fundamentals and actual engineering applications in a way that was immediately useful for my research. Prof. Wang and the TA were also really helpful and approachable throughout.

Describe your Graduate Student Researcher (GSR) and/or Teaching Assistant (TA) experiences:  As a GSR, most of my time is split between running experiments, reading literature, and writing manuscripts, the typical rhythm of pushing a research project forward. On the TA side, I've taught two courses: ECE 3, Introduction to Python Programming for Engineers, and ECE 274, Neurally Inspired Computing Systems, where I held office hours and labs to help students work through problems. Teaching has been a rewarding side of the PhD experience, because explaining concepts clearly to students actually sharpens your own understanding more than you'd expect.

Life as a graduate student

Quality of life as a graduate student and how you balance school, work, social, and family life: Life as a PhD student is busy, but I've found ways to keep it sustainable. I stay connected with family back home through regular video calls. For friends from college and UCSB, I make a point to find chances to meet in person whenever possible. Having that mix of online and in-person connection makes a real difference.

What is your social life like? Santa Barbara is honestly a great place to live: the weather, the beach, the mountains. I spent my first four years in Goleta, a lovely city near UCSB. I recently moved to Ventura, which has a slightly different pace but is still a beautiful place to be.

Tell us about your summer break: This summer, I plan to prepare for my defense. But once that's done, I'm definitely planning to travel in the US, visiting several famous national parks like Yellowstone and Glacier.

Advice to prospective graduate students: On the research side, don't be afraid to explore broadly in your first year before committing deeply. Finding a problem you're genuinely curious about makes the hard stretches much more bearable. In addition, protect your social life and don't isolate yourself, because the people you meet in grad school end up being one of the most valuable parts of the whole experience.

Future Plans...

Where will your research take you next and what are your future career goals: My goal is to join a research or applied science team in industry where I can contribute to building ML systems that are not just powerful, but actually dependable and scalable in production environments.