DDRO: A novel performance monitoring methodology based on design-dependent ring oscillators. - Tuck-Boon Chan; Puneet Gupta 001; Andrew B. Kahng; Liangzhen Lai (ISQED, 2012)

VarEMU: An emulation testbed for variability-aware software. - Lucas Francisco Wanner; Salma Elmalaki 001; Liangzhen Lai; Puneet Gupta 001; Mani B. Srivastava (CODES+ISSS, 2013)

SlackProbe: a low overhead in situ on-line timing slack monitoring methodology. - Liangzhen Lai; Vikas Chandra; Robert C. Aitken; Puneet Gupta 001 (DATE, 2013)

Accurate and inexpensive performance monitoring for variability-aware systems. - Liangzhen Lai; Puneet Gupta 001 (ASP-DAC, 2014)

BTI-Gater: An Aging-Resilient Clock Gating Methodology. - Liangzhen Lai; Vikas Chandra; Robert C. Aitken; Puneet Gupta 001 (IEEE J. Emerg. Sel. Topics Circuits Syst., 2014)

SlackProbe: A Flexible and Efficient In Situ Timing Slack Monitoring Methodology. - Liangzhen Lai; Vikas Chandra; Robert C. Aitken; Puneet Gupta 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2014)

Synthesis and Analysis of Design-Dependent Ring Oscillator (DDRO) Performance Monitors. - Tuck-Boon Chan; Puneet Gupta 001; Andrew B. Kahng; Liangzhen Lai (IEEE Trans. Very Large Scale Integr. Syst., 2014)

Evaluating and exploiting impacts of dynamic power management schemes on system reliability. - Liangzhen Lai; Vikas Chandra; Puneet Gupta 001 (CASES, 2015)

NSF expedition on variability-aware software: Recent results and contributions. - Lucas Francisco Wanner; Liangzhen Lai; Abbas Rahimi; Mark Gottscho; Pietro Mercati; Chu-Hsiang Huang; Frederic Sala; Yuvraj Agarwal; Lara Dolecek; Nikil D. Dutt; Puneet Gupta 001; Rajesh K. Gupta 001; et al. (it Inf. Technol., 2015)

Hardware Reliability margining for the dark silicon era. - Liangzhen Lai; Puneet Gupta 001 (ASP-DAC, 2016)

Multi-story power distribution networks for GPUs. - Qixiang Zhang; Liangzhen Lai; Mark Gottscho; Puneet Gupta 001 (DATE, 2016)

Resiliency in dynamically power managed designs. - Liangzhen Lai; Vikas Chandra; Rob Aitken (ICCAD, 2016)

Cross-level Monte Carlo Framework for System Vulnerability Evaluation against Fault Attack. - Meng Li 004; Liangzhen Lai; Vikas Chandra; David Z. Pan (DAC, 2017)

Exploiting data-dependence and Flip-Flop asymmetry for zero-overhead system soft error mitigation. - Vikas Chandra; Liangzhen Lai (DATE, 2017)

Deep Convolutional Neural Network Inference with Floating-point Weights and Fixed-point Activations. - Liangzhen Lai; Naveen Suda; Vikas Chandra (CoRR, 2017)

PrivyNet: A Flexible Framework for Privacy-Preserving Deep Neural Network Training with A Fine-Grained Privacy Control. - Meng Li 004; Liangzhen Lai; Naveen Suda; Vikas Chandra; David Z. Pan (CoRR, 2017)

Hello Edge: Keyword Spotting on Microcontrollers. - Yundong Zhang 001; Naveen Suda; Liangzhen Lai; Vikas Chandra (CoRR, 2017)

Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks. - Hardik Sharma; Jongse Park; Naveen Suda; Liangzhen Lai; Benson Chau; Joon Kyung Kim; Vikas Chandra; Hadi Esmaeilzadeh (CoRR, 2017)

System-Level Dynamic Variation Margining in Presence of Monitoring and Actuation. - Liangzhen Lai; Puneet Gupta 001 (IEEE Embed. Syst. Lett., 2017)

Enabling deep learning at the IoT edge. - Liangzhen Lai; Naveen Suda (ICCAD, 2018)

Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Network. - Hardik Sharma; Jongse Park; Naveen Suda; Liangzhen Lai; Benson Chau; Vikas Chandra; Hadi Esmaeilzadeh (ISCA, 2018)

Not All Ops Are Created Equal! - Liangzhen Lai; Naveen Suda; Vikas Chandra (CoRR, 2018)

CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUs. - Liangzhen Lai; Naveen Suda; Vikas Chandra (CoRR, 2018)

Federated Learning with Non-IID Data. - Yue Zhao; Meng Li 004; Liangzhen Lai; Naveen Suda; Damon Civin; Vikas Chandra (CoRR, 2018)

Rethinking Machine Learning Development and Deployment for Edge Devices. - Liangzhen Lai; Naveen Suda (CoRR, 2018)

SenseHAR: a robust virtual activity sensor for smartphones and wearables. - Jeya Vikranth Jeyakumar; Liangzhen Lai; Naveen Suda; Mani B. Srivastava (SenSys, 2019)

HERALD: Optimizing Heterogeneous DNN Accelerators for Edge Devices. - Hyoukjun Kwon; Liangzhen Lai; Tushar Krishna; Vikas Chandra (CoRR, 2019)

Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks. - Lei Yang 018; Zheyu Yan; Meng Li 004; Hyoukjun Kwon; Liangzhen Lai; Tushar Krishna; Vikas Chandra; Weiwen Jiang; Yiyu Shi 001 (DAC, 2020)

Improving Efficiency in Neural Network Accelerator Using Operands Hamming Distance optimization. - Meng Li 004; Yilei Li; Pierce Chuang; Liangzhen Lai; Vikas Chandra (CoRR, 2020)

Heterogeneous Dataflow Accelerators for Multi-DNN Workloads. - Hyoukjun Kwon; Liangzhen Lai; Michael Pellauer; Tushar Krishna; Yu-Hsin Chen; Vikas Chandra (HPCA, 2021)

Low-Rank+Sparse Tensor Compression for Neural Networks. - Cole Hawkins; Haichuan Yang; Meng Li 004; Liangzhen Lai; Vikas Chandra (CoRR, 2021)

Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation. - Jiaqi Gu 002; Hyoukjun Kwon; Dilin Wang; Wei Ye 008; Meng Li 004; Yu-Hsin Chen; Liangzhen Lai; Vikas Chandra; David Z. Pan (CVPR, 2022)

SDRM3: A Dynamic Scheduler for Dynamic Real-time Multi-model ML Workloads. - Seah Kim; Hyoukjun Kwon; Jinook Song; Jihyuck Jo; Yu-Hsin Chen; Liangzhen Lai; Vikas Chandra (CoRR, 2022)

DREAM: A Dynamic Scheduler for Dynamic Real-time Multi-model ML Workloads. - Seah Kim; Hyoukjun Kwon; Jinook Song; Jihyuck Jo; Yu-Hsin Chen; Liangzhen Lai; Vikas Chandra (ASPLOS (4), 2023)

Efficient Non-Linear Adder for Stochastic Computing with Approximate Spatial-Temporal Sorting Network. - Yixuan Hu; Tengyu Zhang; Meng Li 004; Renjie Wei; Liangzhen Lai; Yuan Wang 001; Runsheng Wang; Ru Huang 001 (DAC, 2023)

XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse. - Hyoukjun Kwon; Krishnakumar Nair; Jamin Seo; Jason Yik; Debabrata Mohapatra; Dongyuan Zhan; Jinook Song; Peter Capak; Peizhao Zhang; Peter Vajda; Colby R. Banbury; Mark Mazumder; et al. (MLSys, 2023)

Folding Attention: Memory and Power Optimization for On-Device Transformer-based Streaming Speech Recognition. - Yang Li 183; Liangzhen Lai; Yuan Shangguan; Forrest N. Iandola; Ernie Chang; Yangyang Shi; Vikas Chandra (CoRR, 2023)

LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding. - Mostafa Elhoushi; Akshat Shrivastava; Diana Liskovich; Basil Hosmer; Bram Wasti; Liangzhen Lai; Anas Mahmoud 002; Bilge Acun; Saurabh Agarwal; Ahmed Roman; Ahmed A Aly; Beidi Chen; et al. (ACL (1), 2024)

GPU-based Private Information Retrieval for On-Device Machine Learning Inference. - Maximilian Lam; Jeff Johnson 004; Wenjie Xiong 001; Kiwan Maeng; Udit Gupta; Yang Li 183; Liangzhen Lai; Ilias Leontiadis; Minsoo Rhu; Hsien-Hsin S. Lee; Vijay Janapa Reddi; Gu-Yeon Wei; et al. (ASPLOS (1), 2024)

Folding Attention: Memory and Power Optimization for On-Device Transformer-Based Streaming Speech Recognition. - Yang Li 183; Liangzhen Lai; Yuan Shangguan; Forrest N. Iandola; Zhaoheng Ni; Ernie Chang; Yangyang Shi; Vikas Chandra (ICASSP, 2024)

MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases. - Zechun Liu; Changsheng Zhao 002; Forrest N. Iandola; Chen Lai; Yuandong Tian; Igor Fedorov; Yunyang Xiong; Ernie Chang; Yangyang Shi; Raghuraman Krishnamoorthi; Liangzhen Lai; Vikas Chandra (ICML, 2024)

Not All Weights Are Created Equal: Enhancing Energy Efficiency in On-Device Streaming Speech Recognition. - Yang Li 183; Yuan Shangguan; Yuhao Wang; Liangzhen Lai; Ernie Chang; Changsheng Zhao 002; Yangyang Shi; Vikas Chandra (CoRR, 2024)

PipeOrgan: Efficient Inter-operation Pipelining with Flexible Spatial Organization and Interconnects. - Raveesh Garg; Hyoukjun Kwon; Eric Qin 001; Yu-Hsin Chen; Tushar Krishna; Liangzhen Lai (CoRR, 2024)

Breaking Down Power Barriers in On-Device Streaming ASR: Insights and Solutions. - Yang Li 183; Yuan Shangguan; Yuhao Wang; Liangzhen Lai; Ernie Chang; Changsheng Zhao 002; Yangyang Shi; Vikas Chandra (NAACL (Industry Track), 2025)