Hi, I’m Yuxuan Yin, a Ph.D. candidate in Electrical and Computer Engineering at UC Santa Barbara, advised by Prof. Peng Li. I received my B.E. in Electronic Engineering and B.S. in Mathematics from Tsinghua University.

My research spans agentic AI and reliable deep learning for real-world applications, with hands-on experience in LLM post-training, long-context modeling, and uncertainty quantification. I am the lead author of ADO-LLM, the first LLM-driven agent for automated analog circuit sizing. My work has appeared at ICML, AAAI, ICCAD, DAC, and ISCA.

📢 I am on the job market and actively seeking full-time opportunities. I am looking for roles where I can leverage my expertise in reliable agentic AI and ML systems. Feel free to reach out at y_yin [at] ucsb [dot] edu.

Internship Experience

Preprints

LASER: Language Model Regression for Semi-Structured Workflow Resource and Runtime Estimation
Yuxuan Yin, Shengke Zhou, Yunjie Zhang, Ajay Mohindra, Boxun Xu, Peng Li. (2025). arXiv. [paper]

Towards the Mitigation of Confirmation Bias in Semi-supervised Learning: a Debiased Training Perspective
Yuxuan Yin*, Yu Wang*, Peng Li. (2024). arXiv. [paper]

Publications

GAUSS: Graph-Assisted Uncertainty Quantification using Structure and Semantics for Long-Form Generation in LLMs
Karthik Somayaji NS, Yuxuan Yin, Peng Li. (2026). ICML. [paper]

Data-Efficient Prediction of Minimum Operating Voltage via Inter- and Intra-Wafer Variation Alignment
Yuxuan Yin, Rebecca Chen, Chen He, Peng Li. (2025). VTS. [paper]

Reliable Board-Level Degradation Prediction with Monotonic Segmented Regression under Noisy Measurement
Yuxuan Yin, Rebecca Chen, Chen He, Peng Li. (2025). VTS. [paper]

Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing
Yuxuan Yin, Rebecca Chen, Boxun Xu, Chen He, Peng Li. (2025). ITC. [paper]

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning
Boxun Xu, Yuxuan Yin, Vikram Iyer, Peng Li. (2025). ISCA. [paper]

High-dimensional Bayesian Optimization via Semi-supervised Learning with Optimized Unlabeled Data Sampling (Spotlight)
Yuxuan Yin, Yu Wang, Peng Li. (2024). ICML. [paper]

ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models
Yuxuan Yin*, Yu Wang*, Boxun Xu, Peng Li. (2024). ICCAD. [paper]

Reliable Interval Prediction of Minimum Operating Voltage Based on On-chip Monitors via Conformalized Quantile Regression
Yuxuan Yin, Xiaoxiao Wang, Rebecca Chen, Chen He, Peng Li. (2024). DATE. [paper]

Data-Efficient Conformalized Interval Prediction of Minimum Operating Voltage Capturing Process Variations
Yuxuan Yin, Rebecca Chen, Chen He, Peng Li. (2024). DAC. [paper]

Semi-Supervised Learning of Dynamical Systems with Neural Ordinary Differential Equations: A Teacher-Student Model Approach
Yu Wang, Yuxuan Yin, Karthik Suryanarayana, Jan Drgona, Malachi Schram, Mahantesh Halappanavar, Frank Liu, Peng Li. (2024). AAAI. [paper]

Domain-Specific Machine Learning based Minimum Operating Voltage Prediction using On-Chip Monitor Data
Yuxuan Yin, Rebecca Chen, Chen He, Peng Li. (2023). ITC. [paper]

S3: Side-Channel Attack on Stylus Pencil through Sensors
Habiba Farrukh, Tinghan Yang, Hanwen Xu, Yuxuan Yin, He Wang, Z Berkay Celik. (2021). IMWUT. [paper]