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Meng Li's Homepage
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Meng Li
Assistant Professor
Institute for Artificial Intelligence
School of Integrated Circuits
Peking University
Biography
I am currently a tenure-track assistant professor jointly affiliated with Institute for Artificial Intelligence and School of Integrated Circuits in Peking University. Before joining Peking University, I was a staff research scientist and tech lead in Meta On-Device AI team with a focus on researching and productizing efficient AI algorithms and hardwares for next generation AR/VR devices. I received my Ph.D. degree in the Department of Electrical and Computer Engineering, University of Texas at Austin under the supervision of Prof. David Z. Pan and my bachelor degree in Peking University under the supervision of Prof. Ru Huang and Prof. Runsheng Wang.
My research interests focus on efficient and secure multi-modality AI acceleration algorithms and hardwares.
I am always looking for creative and self-motivated students and post docs who are interested in co-designing the future AI acceleration algorithm and system for efficiency and privacy. Please contact me via email with the subject line “Prospective Student from [Your Institute]” and your CV. (I have finished the Ph.D. student recruiting for 2024. If you are interested in applying for 2025, contact me early.)
Download my resumé.
Interests
- Efficient and Secure Multi-Modality Artificial Intelligence
- Algorithm/Hardware Co-Design/Co-Optimization
Education
-
PhD in Computer Engineering, 2018
University of Texas at Austin, Austin, Tx, USA
-
MS in Computer Engineering, 2015
University of Texas at Austin, Austin, Tx, USA
-
BS in Microelectronics, 2013
Peking University, Beijing, China
Research Focus
Efficient AI Algorithm
Multi-Modal AI
AI/HW Co-Design
News
One paper on efficient embodied AI system is accepted by ASPLOS'2026 as a regular paper. The title of the paper is “CREATE: Cross-Layer Resilience Characterization and Optimization for Efficient yet Reliable Embodied AI Systems”.
Last updated on
Nov 4, 2025
One paper on efficient embodied AI is accepted by ASSCC'2025 as regular papers. In the paper, we designed and taped out a 28nm 534.6TOPS/W edge accelerator for embodied AI using stochastic computing, which supported mixed precision and sparsity.
Last updated on
Nov 6, 2025
Experience
Tenure-Track Assistant Professor
Jul 2022 –
Present
Beijing
Institute of Artificial Intelligence
Staff Research Scientist
Sep 2018 –
Jul 2022
California
Experience:
- 2018.09 - 2020.01 Research Scientist
- 2020.01 - 2021.06 Senior Research Scientist
- 2021.06 - 2022.07 Staff Research Scientist
Responsibilities include:
- Tech Lead, On-Device AI, Meta Reality Lab
- Efficient NN for AR Glasses
- Efficient NN/HW Co-Design/Co-Optimization
Research Intern
May 2017 –
Aug 2017
California
Privacy-preserving neural network training, including federated learning with non-IID data and PrivyNet with split network architectures
Research Intern
May 2016 –
Aug 2016
California
Cross-level monte carlo framework for system vulnerability evaluation against fault attack
Research & Design Intern
Cadence Design System
May 2014 –
Aug 2014
California
Static timing analysis acceleration
Recent Talks
Discuss the recent NeurIPs'2024 paper from our lab on joint network/protocol optimization to enable efficient private Transformer inference.
Oct 19, 2024 11:00 AM — 12:00 PM
Discuss the recent works from our lab on joint network/protocol optimization to enable more efficient privacy-preserving AI.
Jan 24, 2024 11:00 AM — 12:00 PM
Discuss the recent works from our lab on full stack optimization to enable accurate yet efficient AI acceleration for multi-modal applications.
Jan 20, 2024 11:00 AM — 12:00 PM
Discuss the recent works from our lab on full stack optimization to enable accurate yet efficient AI acceleration for multi-modal applications.
Jun 7, 2023 11:00 AM — 12:00 PM
Recent Publications
More detailed publication lists available through Google Scholar
Quickly discover relevant content by filtering publications.
Tong Xie,
Yijiahao Qi,
Jinqi Wen,
Zishen Wan,
Yanchi Dong,
Zihao Wang,
Shaofei Cai,
Yitao Liang,
Tianyu Jia,
Yuan Wang,
Runsheng Wang,
Meng Li
(2026).
CREATE: Cross-Layer Resilience Characterization and Optimization for Efficient yet Reliable Embodied AI Systems.
In International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) 2026.
Yifan Zhou,
Tianshi Xu,
Jue Hong,
Ye Wu,
Meng Li
(2025).
CryptoMoE: Privacy-Preserving and Scalable Mixture of Experts Inference via Balanced Expert Routing.
In Conference on Neural Information Processing Systems (NeurIPs) 2025.
Zebin Yang,
Sunjian Zheng,
Tong Xie,
Tianshi Xu,
Bo Yu,
Fan Wang,
Jie Tang,
Shaoshan Liu,
Meng Li
(2025).
EfficientNav: Towards On-Device Object-Goal Navigation with Navigation Map Caching and Retrieval.
In Conference on Neural Information Processing Systems (NeurIPs) 2025.
Wenxuan Zeng,
Ye Dong,
Jinjin Zhou,
Jin Tan,
Lei Wang,
Tao Wei,
Runsheng Wang,
Meng Li
(2025).
MPCache: MPC-Friendly KV Cache Eviction for Efficient Private LLM Inference.
In Conference on Neural Information Processing Systems (NeurIPs) 2025.
Tengyu Zhang,
Chenqi Lin,
Jiangrui Yu,
Shuwen Deng,
Meng Li
(2025).
FENIX: Flexible and Efficient Hybrid HE/MPC Acceleration with Near-Memory Processing.
In International Conference on Computer-Aided Design (ICCAD) 2025.
Zizhuo Fu,
Xiaotian Guo,
Wenxuan Zeng,
Shuzhang Zhong,
Yadong Zhang,
Peiyu Chen,
Runsheng Wang,
Le Ye,
Meng Li
(2025).
H2EAL: Hybrid-Bonding Architecture with Hybrid Sparse Attention for Efficient Long-Context LLM Inference.
In International Conference on Computer-Aided Design (ICCAD) 2025.
Haochen Huang,
Shuzhang Zhong,
Zhe Zhang,
Shuangchen Li,
Dimin Niu,
Hongzhong Zheng,
Runsheng Wang,
Meng Li
(2025).
HD-MoE: Hybrid and Dynamic Parallelism for Mixture-of-Expert LLMs with 3D Near-Memory Processing.
In International Conference on Computer-Aided Design (ICCAD) 2025.
Linye Wei,
Jiajun Tang,
Fan Fei,
Boxin Shi,
Runsheng Wang,
Meng Li
(2025).
No Redundancy, No Stall: Lightweight Streaming 3D Gaussian Splatting for Real-time Rendering.
In International Conference on Computer-Aided Design (ICCAD) 2025.
Linfeng Zhong,
Songqiang Xu,
Huifeng Wen,
Tong Xie,
Qingyu Guo,
Yuan Wang,
Meng Li
(2025).
SpecMamba: Accelerating Mamba Inference on FPGA with Speculative Decoding.
In International Conference on Computer-Aided Design (ICCAD) 2025.
Chenqi Lin,
Kang Yang,
Tianshi Xu,
Ling Liang,
Yufei Wang,
Zhaohui Chen,
Runsheng Wang,
Mingyu Gao,
Meng Li
(2025).
Ironman: Accelerating Oblivious Transfer Extension for Privacy-Preserving AI with Near-Memory Processing.
In MICRO 2025.
Tengyu Zhang,
Tong Xie,
Haoyang Luo,
Yixuan Hu,
Yaoyu Tao,
Xiyuan Tang,
Yuan Wang,
Runsheng Wang,
Meng Li
(2025).
A 28nm 534.6TOPS/W Mixed-Precision Edge Accelerator for Embodied AI Using Stochastic Computing.
In Asian Solid-State Circuits Conference (A-SSCC) 2025.
Tianshi Xu,
Wenjie Lu,
Jiangrui Yu,
Chenqi Lin,
Yi Chen,
Runsheng Wang,
Meng Li
(2025).
Breaking the Layer Barrier: Remodeling Private Transformer Inference with Hybrid CKKS and MPC.
In Usenix Security Symposium 2025.
Yu Fu,
Yu Tong,
Yijing Ning,
Tianshi Xu,
Meng Li,
Jingqiang Lin,
Dengguo Feng
(2025).
Swift: Fast Secure Neural Network Inference with Fully Homomorphic Encryption.
In IEEE Transactions on Information Forensics and Security (TIFS) (2025).
Shuzhang Zhong,
Yanfan Sun,
Ling Liang,
Runsheng Wang,
Ru Huang,
Meng Li
(2025).
HybriMoE: Hybrid CPU-GPU Scheduling and Cache Management for Efficient MoE Inference.
In Design Automation Conference (DAC) 2025.
Tong Xie,
Jiawang Zhao,
Zishen Wan,
Zuodong Zhang,
Yuan Wang,
Runsheng Wang,
Ru Huang,
Meng Li
(2025).
ReaLM: Reliable and Efficient Large Language Model Inference with Statistical Algorithm-Based Fault Tolerance.
In Design Automation Conference (DAC) 2025.
Linye Wei,
Shuzhang Zhong,
Songqiang Xu,
Runsheng Wang,
Ru Huang,
Meng Li
(2025).
SpecASR: Accelerating LLM-based Automatic Speech Recognition via Speculative Decoding.
In Design Automation Conference (DAC) 2025.
Weikai Xu,
Wenxuan Zeng,
Qianqian Huang,
Meng Li,
Ru Huang
(2025).
UniCAIM: A Unified CAM/CIM Architecture with Static-Dynamic KV Cache Pruning for Efficient Long-Context LLM Inference.
In Design Automation Conference (DAC) 2025.
Renjie Wei,
Zechun Liu,
Yuchen Fan,
Runsheng Wang,
Ru Huang,
Meng Li
(2025).
SCALES: Boost Binary Neural Network for Image Super-Resolution with Efficient Scalings.
In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2025.
Weikai Xu,
Meng Li,
Qianqian Huang,
Ru Huang
(2025).
Compact Non-Volatile Lookup Table Architecture based on Ferroelectric FET Array through In-Situ Combinatorial One-Hot Encoding for Reconfigurable Computing.
In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2025.
Renjie Wei,
Songqiang Xu,
Linfeng Zhong,
Zebin Yang,
Qingyu Guo,
Yuan Wang,
Runsheng Wang,
Meng Li
(2025).
LightMamba: Efficient Mamba Acceleration on FPGA with Quantization and Hardware Co-design.
In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2025.
Tengyu Zhang,
Yufei Xue,
Ling Liang,
Zhen Gu,
Yuan Wang,
Runsheng Wang,
Ru Huang,
Meng Li
(2025).
FLASH: An Efficient Hardware Accelerator Leveraging Approximate and Sparse FFT for Homomorphic Encryption.
In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2025.
Xincheng Feng,
Guodong Shen,
Jianhao Hu,
Meng Li,
Ngai Wong
(2025).
Stochastic Multivariate Universal-Radix Finite-State Machine: a Theoretically and Practically Elegant Nonlinear Function Approximator.
In Asia and South Pacific Design Automation Conference (ASP-DAC) 2025.
Renze Chen,
Zhuofeng Wang,
Beiquan Cao,
Tong Wu,
Size Zheng,
Xiuhong Li,
Xuechao Wei,
Shengen Yan,
Meng Li,
Yun Liang
(2024).
ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction.
In Conference on Neural Information Processing Systems (NeurIPs) 2024.
Tianshi Xu,
Lemeng Wu,
Runsheng Wang,
Meng Li
(2024).
PrivCirNet: Efficient Private Inference via Block Circulant Transformation.
In Conference on Neural Information Processing Systems (NeurIPs) 2024.
Shuzhang Zhong,
Zebin Yang,
Ruihao Gong,
Runsheng Wang,
Ru Huang,
Meng Li
(2024).
ProPD: Dynamic Token Tree Pruning and Generation for LLM Parallel Decoding.
In International Conference on Computer-Aided Design (ICCAD) 2024.
Shuzhang Zhong,
Ling Liang,
Yuan Wang,
Runsheng Wang,
Ru Huang,
Meng Li
(2024).
AdapMoE: Adaptive Sensitivity-based Expert Gating and Management for Efficient MoE Inference.
In International Conference on Computer-Aided Design (ICCAD) 2024.
Jiangrui Yu,
Wenxuan Zeng,
Tianshi Xu,
Renze Chen,
Yun (Eric) Liang,
Runsheng Wang,
Ru Huang,
Meng Li
(2024).
FlexHE: A flexible Kernel Generation Framework for Homomorphic Encryption-Based Private Inference.
In International Conference on Computer-Aided Design (ICCAD) 2024.
Qingyu Guo,
Jiayong Wan,
Songqiang Xu,
Meng Li,
Yuan Wang
(2024).
HG-PIPE: Vision Transformer Acceleration with Hybrid-Grained Pipeline.
In International Conference on Computer-Aided Design (ICCAD) 2024.
Zebin Yang,
Renze Chen,
Taiqiang Wu,
Ngai Wong,
Yun (Eric) Liang,
Runsheng Wang,
Ru Huang,
Meng Li
(2024).
MCUBERT: Memory-Efficient BERT Inference on Commodity Microcontrollers.
In International Conference on Computer-Aided Design (ICCAD) 2024.
Yixuan Hu,
Yikang Jia,
Meng Li,
Yuan Wang,
Runsheng Wang,
Ru Huang
(2024).
OSCA: End-to-end Serial Stochastic Computing Neural Acceleration with Fine-grained Scaling and Piecewise Activation.
In International Conference on Computer-Aided Design (ICCAD) 2024.
Tianshi Xu,
Shuzhang Zhong,
Wenxuan Zeng,
Runsheng Wang,
Meng Li
(2024).
PrivQuant: Communication-Efficient Private Inference with Quantized Network/Protocol Co-Optimization.
In International Conference on Computer-Aided Design (ICCAD) 2024.
Qingyu Guo,
Haoyang Luo,
Meng Li,
Xiyuan Tang,
Yuan Wang
(2024).
CASCADE: A Framework for CNN Accelerator Synthesis with Concatenation and Refreshing Dataflow.
In IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I) (2024).
Jianan Mu,
Husheng Han,
Shangyi Shi,
Jing Ye,
Zizhen Liu,
Shengwen Liang,
Meng Li,
Mingzhe Zhang,
Song Bian,
Xing Hu,
Huaiwei Li,
Xiaowei Li
(2024).
Alchemist: A Unified Accelerator Architecture for Cross-Scheme Fully Homomorphic Encryption.
In Design Automation Conference (DAC) 2024.
Chenqi Lin,
Tianshi Xu,
Zebin Yang,
Meng Li,
Runsheng Wang,
Ru Huang
(2024).
FastQuery: Communication-efficient Embedding Table Query for Private LLMs inference.
In Design Automation Conference (DAC) 2024.
Renze Chen,
Zijian Ding,
Size Zheng,
Meng Li,
Yun (Eric) Liang
(2024).
MoteNN: Memory Optimization via Fine-grained Scheduling for Deep Neural Networks on Tiny Devices.
In Design Automation Conference (DAC) 2024.
Tong Xie,
Yixuan Hu,
Renjie Wei,
Meng Li,
Runsheng Wang,
Yuan Wang,
Ru Huang
(2024).
ASCEND: Accurate yet Efficient End-to-End Stochastic Computing Acceleration of Vision Transformer.
In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2024.
Lemeng Wu,
Dilin Wang,
Meng Li,
Yunyang Xiong,
Raghuraman Krishnamoorthi,
Qiang Liu,
Vikas Chandra
(2024).
Enhancing 3D Detection Through Feature Aligned Deep Fusion.
In International Conference on 3D Vision (3DV) 2024.
Xin Qiao,
Qingyu Guo,
Xiyuan Tang,
Jiahao Song,
Renjie Wei,
Meng Li,
Runsheng Wang,
Yuan Wang
(2024).
A 16.38TOPS and 4.55POPS/W SRAM Computing-in-Memory Macro for Signed Operands Computation and Batch Normalization Implementation.
In IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I) (2024).
Xin Qiao,
Jiahao Song,
Youming Yang,
Renjie Wei,
Xiyuan Tang,
Meng Li,
Runsheng Wang,
Yuan Wang
(2024).
MixCIM: A Hybrid-Cell-Based Computing-in-Memory Macro with Less-Data-Movement and Activation-Memory-Reuse for Depthwise Separable Neural Networks.
In IEEE Custom Integrated Circuits Conference (CICC) 2024.
Wenxuan Zeng,
Meng Li,
Haichuan Yang,
Wen-jie Lu,
Runsheng Wang,
Ru Huang
(2023).
CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference.
In Conference on Neural Information Processing Systems (NeurIPs) 2023.
Zuodong Zhang,
Meng Li,
Yibo Lin,
Runsheng Wang,
Ru Huang
(2023).
READ: Reliability-Enhanced Accelerator Dataflow Optimization using Critical Input Pattern Reduction.
In ACM/IEEE International Conference on Computer Aided Design (ICCAD) 2023.
Tianshi Xu,
Meng Li,
Runsheng Wang,
Ru Huang
(2023).
Falcon: Accelerating Homomorphically Encrypted Convolutions for Efficient Private Mobile Network Inference.
In ACM/IEEE International Conference on Computer Aided Design (ICCAD) 2023.
Wenxuan Zeng,
Meng Li,
Wenjie Xiong,
Tong Tong,
Wen-jie Lu,
Jin Tan,
Runsheng Wang,
Ru Huang
(2023).
MPCViT: Searching for Accurate and Efficient MPC-Friendly Vision Transformer with Heterogeneous Attention.
In International Conference on Computer Vision (ICCV) 2023.
Meng Li,
Yixuan Hu,
Tengyu Zhang,
Renjie Wei,
Yawen Zhang,
Ru Huang,
Runsheng Wang
(2023).
Not your father’s stochastic computing (SC)! Efficient yet Accurate End-to-End SC Accelerator Design.
In International Conference on ASIC (ASICON) 2023.
Shuzhang Zhong,
Meng Li,
Yun (Eric) Liang,
Runsheng Wang,
Ru Huang
(2023).
Memory-aware Scheduling for Complex Wired Networks with Iterative Graph Optimization.
In ACM/IEEE International Conference on Computer Aided Design (ICCAD) 2023.
Zuodong Zhang,
Zizheng Guo,
Yibo Lin,
Meng Li,
Runsheng Wang,
Ru Huang
(2023).
AVATAR: An Aging- and Variation-Aware Dynamic Timing Analyzer for Error-Efficient Computing.
In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2023).
Yixuan Hu,
Tengyu Zhang,
Meng Li,
Renjie Wei,
Liangzhen Lai,
Yuan Wang,
Runsheng Wang,
Ru Huang
(2023).
Efficient Non-Linear Adder for Stochastic Computing with Approximate Spatial-Temporal Sorting Network.
In Design Automation Conference (DAC) 2023.
Zuodong Zhang,
Meng Li,
Yibo Lin,
Runsheng Wang,
Ru Huang
(2023).
READ: Reliability-Enhanced Accelerator Dataflow Optimization using Critical Input Pattern Reduction.
In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2023 (extended abstract).
Yixuan Hu,
Tengyu Zhang,
Renjie Wei,
Meng Li,
Runsheng Wang,
Yuan Wang,
Ru Huang
(2023).
Accurate yet Efficient Stochastic Computing Neural Acceleration with High Precision Residual Fusion.
In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2023.
Zechun Liu,
Barlas Oguz,
Aasish Pappu,
Lin Xiao,
Scott Yih,
Meng Li,
Raghuraman Krishnamoorthi,
Yashar Mehdad
(2022).
BiT: Robustly Binarized Multi-distilled Transformer.
In Conference on Neural Information Processing Systems (NeurIPs) 2022.
Yonggan Fu,
Haichuan Yang,
Jiayi Yuan,
Meng Li,
Raghuraman Krishnamoorthi,
Vikas Chandra,
Yingyan Lin
(2022).
Depth Shrink: Empowering Hardware-Friendly Shallow Neural Networks.
In Conference on Machine Learning (ICML) 2022.
Haichuan Yang,
Yuan Shangguan,
Dilin Wang,
Meng Li,
Pierce Chuang,
Xiaohui Zhang,
Ganesh Venkatesh,
Ozlem Kalinli,
Vikas Chandra
(2022).
Omni-sparsity DNN: Fast Sparsity Optimization for On-Device Streaming E2E ASR via Supernet.
In International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2022.
Jiaqi Gu,
Hyoukjun Kwon,
Dilin Wang,
Wei Ye,
Meng Li,
Yu-Hsin Chen,
Liangzhen Lai,
Vikas Chandra,
David Pan
(2022).
Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation.
In Conference on Computer Vision and Pattern Recognition (CVPR) 2022.
Xin Dong,
Ziyun Li,
Meng Li,
Zhongnan Qu,
Barbara De Salvo,
Chiao Liu,
Hsiang-Tsung Kung
(2022).
SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems.
In Conference on Computer Vision and Pattern Recognition (CVPR) 2022.
Chengyue Gong,
Dilin Wang,
Meng Li,
Xinlei Chen,
Zhicheng Yan,
Yuandong Tian,
Qiang Liu,
Vikas Chandra
(2022).
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training.
In Conference on Learning Representations (ICLR) 2022.
Yongan Zhang,
Yonggan Fu,
Weiwen Jiang,
Chaojian Li,
Haoran You,
Meng Li,
Vikas Chandra,
Yingyan Lin
(2021).
DNA: Differentiable Network-Accelerator Co-Search.
In International Symposium on Low Power Electronics and Design (ISLPED) 2021.
Dilin Wang,
Chengyue Gong,
Meng Li,
Qiang Liu,
Vikas Chandra
(2021).
AlphaNet: Improved Training of Supernets with Alpha-Divergence.
In Conference on Machine Learning (ICML) 2021 (Long Oral).
Dilin Wang,
Meng Li,
Chengyue Gong,
Vikas Chandra
(2021).
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling.
In Conference on Computer Vision and Pattern Recognition (CVPR) 2021.
Meng Li,
Yilei Li,
Vikas Chandra
(2021).
Improving efficiency in neural network accelerator using operands hamming distance optimization.
In Asia and South Pacific Design Automation Conference (ASP-DAC) 2021.
Chengyue Gong,
Dilin Wang,
Meng Li,
Vikas Chandra,
Qiang Liu
(2020).
KeepAugment: A Simple Information-Preserving Data Augmentation Approach.
In Conference on Computer Vision and Pattern Recognition (CVPR) 2021.
Lei Yang,
Zheyu Yan,
Meng Li,
Hyoukjun Kwon,
Liangzhen Lai,
Tushar Krishna,
Vikas Chandra,
Weiwen Jiang,
Yiyu Shi
(2020).
Co-exploration of neural architectures and heterogeneous asic accelerator designs targeting multiple tasks.
In ACM/IEEE Design Automation Conference (DAC) 2020.
Meng Li,
Kaveh Shamsi,
Yier Jin,
David Z Pan
(2018).
TimingSAT: Decamouflaging timing-based logic obfuscation.
In IEEE International Test Conference (ITC) 2018.
Meng Li,
David Z. Pan
(2018).
A Synergistic Framework for Hardware IP Privacy and Integrity Protection.
In Springer (2018).
Meng Li,
Bei Yu,
Yibo Lin,
Xiaoqing Xu,
Wuxi Li,
David Z. Pan
(2018).
A Practical Split Manufacturing Framework for Trojan Prevention via Simultaneous Wire Lifting and Cell Insertion.
In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2018).
Yue Zhao,
Meng Li,
Liangzhen Lai,
Naveen Suda,
Damon Civin,
Vikas Chandra
(2018).
Federated Learning with Non-IID Data.
In arXiv:1806.00582 (2018).
Meng Li,
Bei Yu,
Yibo Lin,
Xiaoqing Xu,
Wuxi Li,
David Z. Pan
(2018).
A Practical Split Manufacturing Framework for Trojan Prevention via Simultaneous Wire Lifting and Cell Insertion.
In Asia and South Pacific Design Automation Conference (ASP-DAC) 2018.
Meng Li,
Liangzhen Lai,
Naveen Suda,
Vikas Chandra,
David Z. Pan
(2018).
PrivyNet: A Flexible Framework for Privacy-Preserving Deep Neural Network Training.
In arXiv:1709:06161 (2018).
Meng Li,
Kaveh Shamsi,
Travis Meade,
Zheng Zhao,
Bei Yu,
Yier Jin,
David Z Pan
(2017).
Provably secure camouflaging strategy for IC protection.
In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2018).
Meng Li,
Kaveh Shamsi,
Travis Meade,
Zheng Zhao,
Bei Yu,
Yier Jin,
David Z Pan
(2017).
Provably secure camouflaging strategy for IC protection.
In ACM/IEEE International Conference on Computer Aided Design (ICCAD) 2017.
Meng Li,
Liangzhen Lai,
Vikas Chandra,
David Z. Pan
(2017).
Cross-level monte carlo framework for system vulnerability evaluation against fault attack.
In ACM/IEEE Design Automation Conference (DAC) 2017.
Kaveh Shamsi,
Meng Li,
Travis Meade,
Zheng Zhao,
David Z Pan,
Yier Jin
(2017).
AppSAT: Approximately Deobfuscating Integrated Circuits.
In IEEE International Symposium on Hardware Oriented Security and Trust (HOST) 2017 (Best Paper Award).
Meng Li,
Ye Wang,
Michael Orshansky
(2016).
A monte carlo simulation flow for seu analysis of sequential circuits.
In ACM/IEEE Design Automation Conference (DAC) 2016.
Meng Li,
Jin Miao,
Kai Zhong,
David Z Pan
(2016).
Practical public PUF enabled by solving max-flow problem on chip.
In ACM/IEEE Design Automation Conference (DAC) 2016.
Meng Li,
Runsheng Wang,
Jibin Zou,
Ru Huang
(2013).
Characterization of Random Telegraph Noise in Scaled High-κ/Metal-Gate MOSFETs with SiO2/HfO2 Gate Dielectrics.
In ECS Transactions, 52 (1) 941-946 (2013).
Projects
*
Accomplishments
AICAS Grand Challenge on LLM Hardware System Design 1st Place
IEEE Circuit & System Society
Apr 2025
Young Teachers’ Teaching Skills Competition 1st Place Prize
Peking University
Dec 2024
CCF-Ant Group Research Award on Hardware/Software Co-Design
China Computer Federation (CCF)
Aug 2024
CCF Integrated Circuits Early Career Award
China Computer Federation (CCF)
Jul 2024
Secretflow Outstanding Industry-Academic Cooperation Contribution Award
Ant Group
May 2024
CCF-Ant Group Research Award on Privacy Computing
China Computer Federation (CCF)
Aug 2023
Margarida Jacome Outstanding Dissertation Prize
University of Texas at Austin
May 2019
Outstanding Dissertations Award
European Design and Automation Association (EDAA)
May 2019
Nominee of ACM Doctoral Dissertation Award
University of Texas at Austin
Mar 2019
First Place, Student Research Competition Grand Final (Graduate Category)
Aossication of Computing Machinery (ACM)
Jun 2018
Best Paper Award
ACM Great Lake Symposium on VLSI (GLSVLSI)
Mar 2018
Best Poster (Presentation) Award
ASPDAC Student Research Forum, Aossication of Computing Machinery (ACM) SIGDA
Feb 2018
Gold Medal
ICCAD Student Research Competition, Aossication of Computing Machinery (ACM) SIGDA
Nov 2017
Best Paper Award
IEEE International Symposium on Hardware Oriented Security and Trust (HOST)
Jul 2017
Cockrell School Graduate Student Fellowship
University of Texas at Austin
Sep 2013
Yang Fuqing and Wang Yangyuan Academician Scholarship
Peking University
Sep 2011
Li Yanhong Baidu Scholarship
Peking University
Sep 2010
Contact
- meng[dot]li[at]pku[dot]edu[dot]cn
- No.5, Yiheyuan Road, Haidian District, Beijing 100871