Curriculum Vitae
Yichao Yuan
Ph.D. Student in Computer Science · University of Illinois Urbana-Champaign
Education
University of Illinois Urbana-Champaign
Ph.D. Student in Computer Science
Focus: GPU-accelerated system design, systems and architecture for AI applications, and systems/architecture–algorithm co-design
University of Michigan
Ph.D. Student in Computer Science and Engineering · GPA 4.0/4.0
Transferred to UIUC with advisor in August 2025
University of Michigan
M.S.E. in Electrical and Computer Engineering · GPA 4.0/4.0
Shanghai Jiao Tong University
B.S.E. in Electrical and Computer Engineering · GPA 3.8/4.0
University of Michigan–Shanghai Jiao Tong University Joint Institute
Publications
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Y. Yuan, M. Chowdhury, and N. Talati. “KAIROS: Stateful, Context-Aware Power-Efficient Agentic Inference Serving.” ASPLOS 2027.
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Y. Yuan, A. Nayak, S. Kundu, and N. Talati. “Agentic AI Workload Characteristics.” IISWC 2026.
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Y. Yuan, L. Ma, and N. Talati. “MoE-Lens: Towards the Hardware Limit of High-Throughput MoE LLM Serving Under Resource Constraints.” HPDC 2026.
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Y. Xia, D. Sharma, Y. Yuan, S. Kundu, and N. Talati. “MoDM: Efficient Serving for Image Generation via Mixture-of-Diffusion Models.” ASPLOS 2026.
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Y. Yuan, A. Iyer, L. Ma, and N. Talati. “Vortex: Overcoming Memory Capacity Limitations in GPU-Accelerated Large-Scale Data Analytics.” VLDB 2025.
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H. Ye, Y. Xia, Y. Chen, K.-Y. Chen, Y. Yuan, S. Deng, B. Kasikci, T. Mudge, and N. Talati. “Palermo: Improving the Performance of Oblivious Memory using Protocol-Hardware Co-Design.” HPCA 2025.
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J. Pavon, I. Valdivieso, C. Morales, C. Hernandez, M. Aslan, J. Lindegger, Y. Yuan, R. Bagué, M. Alser, O. Mutlu, S. Marco-Sola, O. Ergin, N. Talati, M. Valero, O. Unsal, and A. Cristal. “QUETZAL: Vector Acceleration Framework for Modern Genome Sequence Analysis Algorithms.” ISCA 2024.
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Y. Yuan, H. Ye, S. Vedula, W. Kaza, and N. Talati. “Everest: GPU-Accelerated System for Mining Temporal Motifs.” VLDB 2024.
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N. Talati, H. Ye, S. Vedula, K.-Y. Chen, Y. Chen, D. Liu, Y. Yuan, D. Blaauw, A. Bronstein, T. Mudge, and R. Dreslinski. “Mint: An Accelerator for Mining Temporal Motifs.” MICRO 2022.
Professional Experience
Google · Software Engineering Intern
Investigated GPU-accelerated query processing; evaluated how kernel interface design affects operator performance; developed and tested techniques for query-level acceleration.
Arm · System Architecture Intern
Researched memory-access performance in chiplet architectures and architectural support and kernel performance for KV-cache management and attention in CPU-based LLM inference.
Professional Service
Review Board MemberVLDB 2027
Program Committee MemberVLDB 2026 Demonstration Track
Shadow Program Committee MemberVLDB 2026
Artifact Evaluation Committee MemberASPLOS 2025 · ISCA 2025
Technical Skills
LanguagesC++, C, Python, CUDA, HIP, SystemVerilog
Tools & frameworksNVIDIA Nsight Systems/Compute, ROCm profiler, PyTorch, OpenMP, x86/ARM vector intrinsics