Cunxi Yu
Assistant Professor
Develops machine-learning-driven design automation and compilers for hardware and AI systems.
Cunxi Yu's lab at UMD works on accelerators, chips & architecture and compilers & programming languages. 51 papers since 2023, 11 at top venues, mostly ICCAD and NeurIPS. 7 PhD students and 1 master's student. 6 alumni.
At a glance
- papers, 2023–2026
- 13/ year
- at T1 venues
- 22%
- PhD students
- 7
- MS students
- 1
- alumni listed
- 6
Papers by yearfrom the lab homepage, 2023–2026
- 16 papers2026 · T1 7 · collecting
- 14 papers2025 · T1 3
- 8 papers2024 · T1 0
- 13 papers2023 · T1 1
T1 venuesOtherVenues: ICCAD, NeurIPS, AISTATS, Nature Communications
Research focuspaper titles that use each topic's words
- Accelerators, chips & architecture2 papers
- Compilers & programming languages2 papers
- design automation1 paper
- hardware1 paper
- compilers0 papers
Paper list
From the lab homepage.
202616 papers
- AISTATS (T1)A Scalable Lift-and-Project Differentiable Approach For the Maximum Cut Problem (opens in a new tab)
- Design Automation Conference (DACAutonomous Evolution of EDA Tools: Multi-Agent Self-Evolved ABC (opens in a new tab)
- ICCAD (T1)AutoPD: Question-Driven MCTS from Paper Artifacts to PPA-Adaptive Physical-Design Algorithms (opens in a new tab)
- ICCAD (T1)Cedar: Learning to Optimize RTL via Accumulating Verified Rewrite Rules (opens in a new tab)
- International Symposium on Machine Learning for CADDifferentiable Initialization-Accelerated CPU-GPU Hybrid Combinatorial Scheduling (opens in a new tab)
- ICCAD (T1)E-Layout: Layout-Stage Restructuring via RL-Optimized Equality-Saturated Graph Retrieval-Augmented Generation (opens in a new tab)
- International Symposium on Machine Learning for CADEDAFLOWQA: Dual-Validated Q-Tree for a Multi-Stage EDA Log Reasoning Benchmark (opens in a new tab)
- VTSFVRuleLearner: Operator-Level Reasoning Tree (Op-Tree)-Based Rules Learning for Formal Verification (opens in a new tab)
- NeurIPS (T1)GauS: Differentiable Scheduling Optimization via Gaussian Reparameterization (opens in a new tab)
- ICCAD (T1)PWaT3D-Planner: Bridging Power and Timing Optimization with Thermal-Mechanical Awareness (opens in a new tab)
- —ReVEAL: GNN-Guided Reverse Engineering for Formal Verification of Optimized Multipliers (opens in a new tab)
- International Symposium on Machine Learning for CADRTLInsight: Self-Evolving Debugging Skills for Online RTL Bug Root-Cause Analysis and Repair (opens in a new tab)
202514 papers
- ACM/IEEE Workshop on Machine Learning for CADASPEN: LLM-Guided E-Graph Rewriting for RTL Datapath Optimization
- Design Automation Conference (DAC'25) (Best Paper Nomination, 5/1862) GitHubBoolE: Exact Symbolic Reasoning via Boolean Equality Saturation (opens in a new tab)
- International Conference on Machine Learning (ICML'25) GitHubDifferentiable Quadratic Optimization For the Maximum Independent Set Problem (opens in a new tab)
- Advanced Photonics ResearchDigitized Phase Change Material Heterostack for Diffractive Optical Neural Network (opens in a new tab)
- ACM/IEEE International Conference on Computer-Aided Design (ICCAD'25)e-boost: Boosted E-Graph Extraction with Adaptive Heuristics and Exact Solving (opens in a new tab)
- Design Automation Conference (DAC'25) GitHubE-morphic: Scalable Equality Saturation for Structural Exploration in Logic Synthesis (opens in a new tab)
- ICCAD (T1)GROOT: Graph Edge Re-growth and Partitioning for the Verification of Large Designs in Logic Synthesis
- USENIX Annual Technical ConferenceHEC: Equivalence Verification Checking for Code Transformation via Equliaty Saturation
- Cunxi Yu ACM/IEEE Workshop on Machine Learning for CADMapping Fusion: Improving FPGA Technology Mapping with ASIC Mapper
- Nature Communications (T1)Optical Neural Engine for Solving Scientific Partial Differential Equations (opens in a new tab)
- ACM/IEEE Workshop on Machine Learning for CADOptimizing CUDA Graph Scheduling with Reinforcement Learning: A Case Study in SSTA Propagation
- ICCAD (T1)Revisit Choice Network for Synthesis and Technology Mapping (opens in a new tab)
20248 papers
- IEEE Design, Automation and Test in Europe ConferenceBoolGebra: Attributed Graph-learning for Boolean Algebraic Manipulation (opens in a new tab)
- IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) orchestrate@ABCDAG-aware Synthesis Orchestration (opens in a new tab)
- International Conference on Machine Learning (ICML'24) GitHubDifferentiable Combinatorial Scheduling at Scale (opens in a new tab)
- Design Automation Conference (DAC'24) GitHubE-Syn: E-Graph Rewriting with Technology-Aware Cost Functions for Logic Synthesis (opens in a new tab)
- Design Automation Conference (DAC'24) GitHubLess is More: Hop-wise Graph Attention for Scalable and Generalizable Learning on Circuits (opens in a new tab)
- VLSI-SoCLinear Algebra Approach to Verification of Modular (2^n−1) Multipliers (opens in a new tab)
- IEEE/ACM International Conference On Computer Aided Design (ICCAD'24) GitHubMapTune: Advancing ASIC Technology Mapping via Reinforcement Learning Guided Library Tuning (opens in a new tab)
- —Springer (Book), 2024
202313 papers
- ICCAD (T1)Accelerating Exact Combinatorial Optimization via RL-based Initialization -- A Case Study in Scheduling (opens in a new tab)
- ACM/IEEE International Conference on Computer-Aided Design (ICCAD'23) GitHubAIM: Accelerating Arbitrary-precision Integer Multiplication on Heterogeneous Reconfigurable Computing Platform Versal ACAP (opens in a new tab)
- SpringerBook chapter: Machine Learning for Agile FPGA Design (opens in a new tab)
- —Design Automation Conference (DAC'23)
- JanEffects of Interlayer Reflection and Interpixel Interaction in Diffractive Optical Neural Networks (opens in a new tab)
- Design Automation Conference (DAC'23) (23%) (Best Paper Award, 2/1157) GitHub SlidesGamora: Graph Learning based Symbolic Reasoning for Large-Scale Boolean Networks (opens in a new tab)
- Design Automation Conference (DAC'23)Invited: Equality Saturation for Datapath Synthesis: A Pathway to Pareto Optimality
- ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'24) LightRidgeLightRidge: An End-to-end Agile Design Framework for Diffractive Optical Neural Networks (opens in a new tab)
- Design Automation Conference (DAC'23) (23%) Github: will be released with LightRidgePhysics-aware Roughness Optimization for Diffractive Optical Neural Networks (opens in a new tab)
- Design Automation Conference (DAC'23) (23%) GitHubRESPECT: Reinforcement Learning based Edge Scheduling on Pipelined Coral Edge TPUs (opens in a new tab)
- LightRidgeRubikONNs: Multi-task Learning with Rubik's Diffractive Optical Neural Networks (opens in a new tab)
- Design Automation Conference (DAC'23) SlidesTutorial: A Journey to Optical Computing: From Physics Fundamentals to Hardware-Software Co-Design, Automation, and Application (opens in a new tab)
Where alumni went6 listed, 0% to industry
Industry 0Academia 4
Also to
- Simon Fraser University
- University of Maryland
Apply to UMDFall 2027
Not announced yet
UMD Computer Science PhD
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- GRE
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- English
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Not yet confirmed for this intake.
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26 T1
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