Outlier detection for large scale manufacturing processes. - Abhinav Jauhri; Bradley McDanel; Chris Connor (IEEE BigData, 2015)

Sparse Coding Trees with application to emotion classification. - Hsieh-Chung Chen; Marcus Z. Comiter; H. T. Kung 001; Bradley McDanel (CVPR Workshops, 2015)

PNNU: Parallel Nearest-Neighbor Units for Learned Dictionaries. - H. T. Kung 001; Bradley McDanel; Surat Teerapittayanon (LCPC, 2015)

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 001 (MobiHoc, 2015)

BranchyNet: Fast inference via early exiting from deep neural networks. - Surat Teerapittayanon; Bradley McDanel; H. T. Kung 001 (ICPR, 2016)

Embedded Binarized Neural Networks. - Bradley McDanel; Surat Teerapittayanon; H. T. Kung 001 (EWSN, 2017)

Distributed Deep Neural Networks Over the Cloud, the Edge and End Devices. - Surat Teerapittayanon; Bradley McDanel; H. T. Kung 001 (ICDCS, 2017)

Incomplete Dot Products for Dynamic Computation Scaling in Neural Network Inference. - Bradley McDanel; Surat Teerapittayanon; H. T. Kung 001 (ICMLA, 2017)

Adaptive Tiling: Applying Fixed-size Systolic Arrays To Sparse Convolutional Neural Networks. - H. T. Kung 001; Bradley McDanel; Sai Qian Zhang (ICPR, 2018)

Mapping Systolic Arrays onto 3D Circuit Structures: Accelerating Convolutional Neural Network Inference. - H. T. Kung 001; Bradley McDanel; Sai Qian Zhang (SiPS, 2018)

Maestro: A Memory-on-Logic Architecture for Coordinated Parallel Use of Many Systolic Arrays. - H. T. Kung 001; Bradley McDanel; Sai Qian Zhang; Xin Dong 009; Chih-Chiang Chen (ASAP, 2019)

Packing Sparse Convolutional Neural Networks for Efficient Systolic Array Implementations: Column Combining Under Joint Optimization. - H. T. Kung 001; Bradley McDanel; Sai Qian Zhang (ASPLOS, 2019)

Full-stack optimization for accelerating CNNs using powers-of-two weights with FPGA validation. - Bradley McDanel; Sai Qian Zhang; H. T. Kung 001; Xin Dong 009 (ICS, 2019)

Systolic Building Block for Logic-on-Logic 3D-IC Implementations of Convolutional Neural Networks. - H. T. Kung 001; 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 (ISCAS, 2019)

Full-stack Optimization for Accelerating CNNs with FPGA Validation. - Bradley McDanel; Sai Qian Zhang; H. T. Kung 001; Xin Dong 009 (CoRR, 2019)

Term quantization: furthering quantization at run time. - Hsiang-Tsung Kung 001; Bradley McDanel; Sai Qian Zhang (SC, 2020)

Term Revealing: Furthering Quantization at Run Time on Quantized DNNs. - H. T. Kung 001; Bradley McDanel; Sai Qian Zhang (CoRR, 2020)

Training for multi-resolution inference using reusable quantization terms. - Sai Qian Zhang; Bradley McDanel; H. T. Kung 001; Xin Dong 009 (ASPLOS, 2021)

Saturation RRAM Leveraging Bit-Level Sparsity Resulting from Term Quantization. - Bradley McDanel; Sai Qian Zhang; H. T. Kung 001 (ISCAS, 2021)

FAST: DNN Training Under Variable Precision Block Floating Point with Stochastic Rounding. - Sai Qian Zhang; Bradley McDanel; H. T. Kung 001 (HPCA, 2022)

Accelerating DNN Training with Structured Data Gradient Pruning. - Bradley McDanel; Helia Dinh; John Magallanes (ICPR, 2022)

Accelerating Vision Transformer Training via a Patch Sampling Schedule. - Bradley McDanel; Chi Phuong Huynh (CoRR, 2022)

Dynamic Patch Sampling for Efficient Training and Dynamic Inference in Vision Transformers. - Bradley McDanel; Chi Phuong Ngoc Huynh (ICMLA, 2023)

StitchNet: Composing Neural Networks from Pre-Trained Fragments. - Surat Teerapittayanon; Marcus Z. Comiter; Bradley McDanel; H. T. Kung 001 (ICMLA, 2023)

PipeSpec: Breaking Stage Dependencies in Hierarchical LLM Decoding. - Bradley McDanel; Sai Qian Zhang; Yunhai Hu; Zining Liu (ACL (Findings), 2025)

AMUSD: Asynchronous Multi-Device Speculative Decoding for LLM Acceleration. - Bradley McDanel (ISCAS, 2025)

Designing LLM-Resistant Programming Assignments: Insights and Strategies for CS Educators. - Bradley McDanel; Ed Novak (SIGCSE (1), 2025)

Beyond Trusting Trust: Multi-Model Validation for Robust Code Generation. - Bradley McDanel (CoRR, 2025)

Speculative Decoding and Beyond: An In-Depth Survey of Techniques. - Yunhai Hu; Zining Liu; Zhenyuan Dong; Tianfan Peng; Bradley McDanel; Sai Qian Zhang (CoRR, 2025)