| 2026 | SIGCSE | Individualized Quizzes From Student Code with LLMs. | Ed Novak, Bradley McDanel |
| 2025 | ACL | PipeSpec: Breaking Stage Dependencies in Hierarchical LLM Decoding. | Bradley McDanel, Sai Qian Zhang, Yunhai Hu, Zining Liu |
| 2025 | EMNLP | Mitigating Sequential Dependencies: A Survey of Algorithms and Systems for Generation-Refinement Frameworks in Autoregressive Models. | Yunhai Hu, Zining Liu, Zhenyuan Dong, Tianfan Peng, Bradley McDanel, Sai Qian Zhang |
| 2025 | ISCAS | AMUSD: Asynchronous Multi-Device Speculative Decoding for LLM Acceleration. | Bradley McDanel |
| 2025 | SIGCSE | Designing LLM-Resistant Programming Assignments: Insights and Strategies for CS Educators. | Bradley McDanel, Ed Novak |
| 2023 | ICMLA | Dynamic Patch Sampling for Efficient Training and Dynamic Inference in Vision Transformers. | Bradley McDanel, Chi Phuong Ngoc Huynh |
| 2023 | ICMLA | StitchNet: Composing Neural Networks from Pre-Trained Fragments. | Surat Teerapittayanon, Marcus Z. Comiter, Bradley McDanel, H. T. Kung |
| 2022 | HPCA | FAST: DNN Training Under Variable Precision Block Floating Point with Stochastic Rounding. | Sai Qian Zhang, Bradley McDanel, H. T. Kung |
| 2022 | ICPR | Accelerating DNN Training with Structured Data Gradient Pruning. | Bradley McDanel, Helia Dinh, John Magallanes |
| 2021 | ASPLOS | Training for multi-resolution inference using reusable quantization terms. | Sai Qian Zhang, Bradley McDanel, H. T. Kung, Xin Dong |
| 2021 | ISCAS | Saturation RRAM Leveraging Bit-Level Sparsity Resulting from Term Quantization. | Bradley McDanel, Sai Qian Zhang, H. T. Kung |
| 2020 | SC | Term quantization: furthering quantization at run time. | Hsiang-Tsung Kung, Bradley McDanel, Sai Qian Zhang |
| 2019 | ASPLOS | Packing Sparse Convolutional Neural Networks for Efficient Systolic Array Implementations: Column Combining Under Joint Optimization. | H. T. Kung, Bradley McDanel, Sai Qian Zhang |
| 2019 | ISCAS | Systolic Building Block for Logic-on-Logic 3D-IC Implementations of Convolutional Neural Networks. | H. T. Kung, Bradley McDanel, Sai Qian Zhang, C. T. Wang, Jin Cai, C. Y. Chen, Victor C. Y. Chang, M. F. Chen, Jack Yuan-Chen Sun, Douglas Yu |
| 2019 | ICS | Full-stack optimization for accelerating CNNs using powers-of-two weights with FPGA validation. | Bradley McDanel, Sai Qian Zhang, H. T. Kung, Xin Dong |
| 2018 | ICPR | Adaptive Tiling: Applying Fixed-size Systolic Arrays To Sparse Convolutional Neural Networks. | H. T. Kung, Bradley McDanel, Sai Qian Zhang |
| 2017 | EWSN | Embedded Binarized Neural Networks. | Bradley McDanel, Surat Teerapittayanon, H. T. Kung |
| 2017 | ICDCS | Distributed Deep Neural Networks Over the Cloud, the Edge and End Devices. | Surat Teerapittayanon, Bradley McDanel, H. T. Kung |
| 2017 | ICMLA | Incomplete Dot Products for Dynamic Computation Scaling in Neural Network Inference. | Bradley McDanel, Surat Teerapittayanon, H. T. Kung |
| 2016 | ICPR | BranchyNet: Fast inference via early exiting from deep neural networks. | Surat Teerapittayanon, Bradley McDanel, H. T. Kung |
| 2015 | CVPR | Sparse Coding Trees with application to emotion classification. | Hsieh-Chung Chen, Marcus Z. Comiter, H. T. Kung, Bradley McDanel |
| 2015 | MOBIHOC | Taming Wireless Fluctuations by Predictive Queuing Using a Sparse-Coding Link-State Model. | Stephen J. Tarsa, Marcus Z. Comiter, Michael B. Crouse, Bradley McDanel, H. T. Kung |