Publications since 2020 are listed below. The last update was on 15 Oct 2026. For a more complete list, please see his Google Scholar Profile.

  • DY Akyol, C Guo, W Luk, “LLM4HLS-Agent: Budgeted Autonomous Repair and Multi-Objective Optimization for HLS”, International Conference on Field-Programmable Technology (FPT), 2026, 🥇 Design Competition Track A, First Prize [pdf] [code]

  • Z Zhang, Q Deng, W Gao, H Chen, A Wetscherek, C Guo, Z Que, W Luk, “Accelerating Complex-valued Uncertainty Estimation via Sparsity Exploration and Exploitation”, International Conference on Field-Programmable Technology (FPT), 2026 [pdf]

  • J Li, C Guo, W Luk, “Conformal Trust Control for Learned Sequential Policies under Regime Shift”, ACM International Conference on AI in Finance (ICAIF), 2026 [pdf] [code]

  • Z Zhang, Q Deng, Z Ren, M Chen, G Li, X Hu, JGF Coutinho, C Guo, W Luk, Z Que, H Fan, “HeteroReason: Heterogeneous FPGA-GPU Acceleration for Disaggregated Speculative Reasoning”, IEEE/ACM International Symposium on Microarchitecture (MICRO), 2026 [pdf] [code]

  • G Yu, C Guo, W Luk, “VCDF: A Validated Consensus-Driven Framework for Time Series Causal Discovery”, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2026 [pdf] [code]

  • Z Liu, C Guo, Z Zhang, Q Liu, W Luk, “EDSSC: An Efficient FPGA-based Accelerator for Dynamic Sparse Spectral Clustering”, IEEE International Symposium On Field-Programmable Custom Computing Machines (FCCM), 2026

  • G Li, Y Cao, LHL Ng, A Charlton, Q Wang, W Punter, P Papaphilippou, C Guo, H Fan, W Luk, S Amarasinghe, A Brahmakshatriya, “SPAC: Automating FPGA-based Network Switches with Protocol Adaptive Customization”, IEEE International Symposium On Field-Programmable Custom Computing Machines (FCCM), 2026

  • Z Que, JGF Coutinho, C Guo, H Fan, W Luk, “MetaML-Pro: Cross-Stage Design Flow Automation for Efficient Deep Learning Acceleration”, ACM Transactions on Reconfigurable Technology and Systems (TRETS), 2026

  • BPY Kwan, C Guo, W Luk, “Optimizing FPGA-Based Neural Network Ensemble”, International Symposium on Applied Reconfigurable Computing (ARC), 2026

  • Z Liu, C Guo, Z Zhang, Q Liu, W Luk, “CODESCA: Co-Design for Spectral Clustering Acceleration”, ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA), 2026

  • S Liang, Y Lu, C Guo, P Kelly, W Luk, H Fan, “Advancing Full-stack Acceleration for Schrödinger-Style Quantum Simulation”, IEEE International Symposium on High Performance Computer Architecture (HPCA), 2026 [pdf]

  • H Ito, H Otsuka, R Yasudo, Z Que, JGF Coutinho, D Fujiki, M Motomura, C Guo, W Luk, “Memory-Efficient and Trustworthy Neural Networks via Random Seed-Based Design”, IEEE Access, 2026

  • J Huang, C Guo, W Luk, “ProtoPGTN: A Scalable Prototype-Based Gated Transformer Network for Interpretable Time Series Classification”, Information, 2025 [pdf] [code]

  • L Faloughi, C Guo, W Luk, “ProtoHedge: Interpretable Hedging with Market Prototypes”, ACM International Conference on AI in Finance (ICAIF), 2025, 🥇 Best Student Paper [pdf] [code]

  • QA Nguyen, C Guo, W Luk, “Repurposing Language Models for FX Volatility Forecasting: A Data-Efficient and Context-Aware Approach”, ACM International Conference on AI in Finance (ICAIF), 2025 [pdf] [code]

  • ATL Leung, C Guo, W Luk, “FABS: An Extensible and High-Performance Digital Twin Framework of AI-Driven Financial Systems”, ACM International Conference on AI in Finance (ICAIF), 2025 [pdf] [code]

  • JR De Freitas, JGF Coutinho, C Guo, S Demirsoy, W Luk, Z Que, “Optimizing LLM Inference for FPGAs”, International Conference on ASIC (ASICON), 2025

  • Z Jiao, C Guo, W Luk, “Scalable Time Series Causal Discovery with Approximate Causal Ordering”, Mathematics, 2025 [pdf] [code]

  • H Wu, C Guo, W Luk, R Mullins, “ASPO: Constraint-Aware Bayesian Optimization for FPGA-based Soft Processors”, International Conference on Field-Programmable Logic and Applications (FPL), 2025 [pdf]

  • Y Lu, S Liang, H Fan, C Guo, W Luk, PHJ Kelly, “Versatile Cross-platform Compilation Toolchain for Schrödinger-style Quantum Circuit Simulation”, ACM/IEEE Design Automation Conference (DAC), 2025 [pdf]

  • C Guo, T Zhao, “ResBench: A Resource-Aware Benchmark for LLM-Generated FPGA Designs”, International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies (HEART), 2025 [pdf]

  • Z Que, H Fan, G Figueiredo, C Guo, W Luk, R Yasudo, M Motomura, “Trustworthy Deep Learning Acceleration with Customizable Design Flow Automation”, International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies (HEART), 2025 [pdf]

  • A Gausen, C Guo, W Luk, “An approach to sociotechnical transparency of social media algorithms using agent-based modelling”, AI and Ethics, vol 5, iss 2, 1827–1845, 2025, Springer [pdf]

  • Z Que, A Zhao, JGF Coutinho, C Guo, W Luk, “Optimizing DNN Accelerator Compression Using Tolerable Accuracy Loss”, International Conference on Field-Programmable Technology (FPT), 2024

  • A Gausen, C Guo, W Luk, “Hardware Acceleration of Agent-Based Simulations of Social Media”, Annual European Simulation and Modelling Conference, 2024 [pdf]

  • C Guo, H Wu, W Luk, “Resource-Constraint Bayesian Optimization for Soft Processors on FPGAs”, International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies (HEART), 2024 [pdf]

  • S Liang, Y Lu, C Guo, W Luk, P Kelly, “PCQ: Parallel Compact Quantum Circuit Simulation”, IEEE International Symposium On Field-Programmable Custom Computing Machines (FCCM), 2024, 🥈 Best Short Paper Runner-Up [pdf]

  • Z Que, M Zhang, H Fan, H Li, C Guo, W Luk, “Low latency variational autoencoder on FPGAs”, IEEE Journal of Emerging and Selected Topics in Circuits and Systems, 2024 [pdf]

  • K Gao, P Vytelingum, S Weston, W Luk, C Guo, “High-frequency Financial Market Simulation and Flash Crash Scenarios Analysis: An Agent-based Modelling Approach”, Journal of Artificial Societies and Social Simulation (JASSS), 2024 [pdf]

  • C Stanford, W Luk, S Weston, C Guo, J Babaie-Harmon, K Vytelingum, “Agent-Based Modelling for Scenario Analysis in Management Consulting”, Wilmott, vol 2024, iss 130, 2024 [pdf]

  • C Guo, W Luk, “FPGA-Accelerated Sim-to-Real Control Policy Learning for Robotic Arms”, IEEE Transactions on Circuits and Systems II: Express Briefs (TCAS-II), 2024 [pdf]

  • K Gao, S Weston, P Vytelingum, N Stillman, W Luk, C Guo, “Deeper hedging: A new agent-based model for effective deep hedging”, International Conference on AI in Finance (ICAIF), 2023 [pdf]

  • JGF Coutinho, C Guo, T Todman, W Luk, “Exploring machine learning adoption in customisable processor design”, International Conference on ASIC (ASICON), 2023 [link]

  • C Guo, D Cupello, W Luk, J Levine, A Warren, P Brookes, “FPGA-accelerated causal discovery with conditional independence test prioritization”, International Conference on Field-Programmable Logic and Applications (FPL), 2023 [pdf]

  • Z Que, S Liu, M Rognlien, C Guo, JGF Coutinho, W Luk, “MetaML: Automating Customizable Cross-Stage Design-Flow for Deep Learning Acceleration”, International Conference on Field-Programmable Logic and Applications (FPL), 2023

  • C Guo, W Luk, A Warren, J Levine, P Brookes, “Co-Design of Algorithm and FPGA Accelerator for Conditional Independence Test”, International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2023 [pdf]

  • W Luk, C Guo, “Hardware-Aware Execution”, Machine Learning under Resource Constraints - Fundamentals, 249-304, 2023 [pdf]

  • A Gausen, W Luk, C Guo, “Using Agent-Based Modelling to Evaluate the Impact of Algorithmic Curation on Social Media”, ACM Journal of Data and Information Quality (JDIQ), 2022

  • BPY Kwan, C Guo, W Luk, P Jiang, “Light-Weight Permutation Generator for Efficient Convolutional Neural Network Data Augmentation”, International Symposium on Applied Reconfigurable Computing (ARC), 2022

  • H Fan, C Guo, W Luk, “Optimizing quantum circuit placement via machine learning”, ACM/IEEE Design Automation Conference (DAC), 2022 [pdf]

  • C Guo, W Luk, “Accelerating Constraint-Based Causal Discovery by Shifting Speed Bottleneck”, ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA), 2022

  • R Yasudo, JGF Coutinho, AL Varbanescu, W Luk, H Amano, T Becker, C Guo, “Analytical Performance Estimation for Large-Scale Reconfigurable Dataflow Platforms”, ACM Transactions on Reconfigurable Technology and Systems (TRETS), 2021

  • A Gausen, W Luk, C Guo, “Can We Stop Fake News? Using Agent-Based Modelling to Evaluate Countermeasures for Misinformation on Social Media”, International AAAI Conference on Web and Social Media (ICWSM) Workshops, 2021

  • L Fu, C Guo, W Luk, “FPGA-Accelerated Agent-Based Simulation for COVID-19”, IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2021

  • C Guo, W Luk, “Quantisation-Aware Dimensionality Reduction”, International Conference on Field-Programmable Technology (FPT), 2020

  • C Guo, W Luk, S Weston, “Accelerating Simulation for Agent-Based Epidemic Models using FPGAs”, IEEE/ACS International Conference on Computer Systems and Applications (AICCSA), 2020

  • J Meng, C Guo, N Gebara, W Luk, “Fast and Accurate Training of Ensemble Models with FPGA-based Switch”, International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2020

  • C Luo, MK Sit, H Fan, S Liu, W Luk, C Guo, “Towards Efficient Deep Neural Network Training by FPGA-Based Batch-Level Parallelism”, Journal of Semiconductors, 2020