Process variation aware data management for magnetic skyrmions racetrack memory. - Fan Chen 001; Zheng Li; Wang Kang 001; Weisheng Zhao; Hai Li 001; Yiran Chen 001 (ASP-DAC, 2018)

ReGAN: A pipelined ReRAM-based accelerator for generative adversarial networks. - Fan Chen 001; Linghao Song; Yiran Chen 001 (ASP-DAC, 2018)

ReRAM-based accelerator for deep learning. - Bing Li 017; Linghao Song; Fan Chen 001; Xuehai Qian; Yiran Chen 001; Hai Helen Li (DATE, 2018)

Exploring the opportunity of implementing neuromorphic computing systems with spintronic devices. - Bonan Yan; Fan Chen 001; Yaojun Zhang; Chang Song 001; Hai Li 001; Yiran Chen 001 (DATE, 2018)

EMAT: an efficient multi-task architecture for transfer learning using ReRAM. - Fan Chen 001; Hai Li 001 (ICCAD, 2018)

Design and Data Management for Magnetic Racetrack Memory. - Bing Li 017; Fan Chen 001; Wang Kang 001; Weisheng Zhao; Yiran Chen 001; Hai Li 001 (ISCAS, 2018)

Taming extreme heterogeneity via machine learning based design of autonomous manycore systems. - Paul Bogdan; Fan Chen 001; Aryan Deshwal; Janardhan Rao Doppa; Biresh Kumar Joardar; Hai (Helen) Li; Shahin Nazarian; Linghao Song; Yao Xiao (CODES+ISSS, 2019)

ZARA: A Novel Zero-free Dataflow Accelerator for Generative Adversarial Networks in 3D ReRAM. - Fan Chen 001; Linghao Song; Hai Helen Li; Yiran Chen 001 (DAC, 2019)

Efficient Process-in-Memory Architecture Design for Unsupervised GAN-based Deep Learning using ReRAM. - Fan Chen 001; Linghao Song; Hai (Helen) Li (ACM Great Lakes Symposium on VLSI, 2019)

Deep Learning for Vertex Reconstruction of Neutrino-nucleus Interaction Events with Combined Energy and Time Data. - Linghao Song; Fan Chen 001; Steven R. Young; Catherine D. Schuman; Gabriel N. Perdue; Thomas E. Potok (ICASSP, 2019)

How to Obtain and Run Light and Efficient Deep Learning Networks. - Fan Chen 001; Wei Wen; Linghao Song; Jingchi Zhang; Hai Helen Li; Yiran Chen 001 (ICCAD, 2019)

Exploring Bit-Slice Sparsity in Deep Neural Networks for Efficient ReRAM-Based Deployment. - Jingyang Zhang; Huanrui Yang; Fan Chen 001; Yitu Wang; Hai Li 001 (EMC2@NeurIPS, 2019)

PARC: A Processing-in-CAM Architecture for Genomic Long Read Pairwise Alignment using ReRAM. - Fan Chen 001; Linghao Song; Hai Helen Li; Yiran Chen 001 (ASP-DAC, 2020)

Parallelism in Deep Learning Accelerators. - Linghao Song; Fan Chen 001; Yiran Chen 001; Hai Helen Li (ASP-DAC, 2020)

ReBoc: Accelerating Block-Circulant Neural Networks in ReRAM. - Yitu Wang; Fan Chen 001; Linghao Song; Chuanjin Richard Shi; Hai Helen Li; Yiran Chen 001 (DATE, 2020)

AccPar: Tensor Partitioning for Heterogeneous Deep Learning Accelerators. - Linghao Song; Fan Chen 001; Youwei Zhuo; Xuehai Qian; Hai Li 001; Yiran Chen 001 (HPCA, 2020)

Low-Cost Floating-Point Processing in ReRAM for Scientific Computing. - Linghao Song; Fan Chen 001; Xuehai Qian; Hai Li 001; Yiran Chen 001 (CoRR, 2020)

In-Memory Computing Architecture for Deep Learning Acceleration. - Fan Chen 001 (2020)

RAISE: A Resistive Accelerator for Subject-Independent EEG Signal Classification. - Fan Chen 001; Linghao Song; Hai Helen Li; Yiran Chen 001 (DATE, 2021)

Marvel: A Vertical Resistive Accelerator for Low-Power Deep Learning Inference in Monolithic 3D. - Fan Chen 001; Linghao Song; Hai Li 001; Yiran Chen 001 (DATE, 2021)

RECOIN: A Low-Power Processing-in-ReRAM Architecture for Deformable Convolution. - Cheng Chu; Fan Chen 001; Dawen Xu 002; Ying Wang 001 (ACM Great Lakes Symposium on VLSI, 2021)

Rerec: In-ReRAM Acceleration with Access-Aware Mapping for Personalized Recommendation. - Yitu Wang; Zhenhua Zhu; Fan Chen 001; Mingyuan Ma; Guohao Dai; Yu Wang 002; Hai Li 001; Yiran Chen 001 (ICCAD, 2021)

PUFFIN: An Efficient DNN Training Accelerator for Direct Feedback Alignment in FeFET. - Fan Chen 001 (ISLPED, 2021)

FeFET-based Process-in-Memory Architecture for Low-Power DNN Training. - Farzaneh Zokaee; Bing Li 017; Fan Chen 001 (NANOARCH, 2021)

MOCCA: A Process Variation Tolerant Systolic DNN Accelerator using CNFETs in Monolithic 3D. - Samuel J. Engers; Cheng Chu; Dawen Xu 002; Ying Wang 001; Fan Chen 001 (ACM Great Lakes Symposium on VLSI, 2022)

Canopy: A CNFET-based Process Variation Aware Systolic DNN Accelerator. - Cheng Chu; Dawen Xu 002; Ying Wang 001; Fan Chen 001 (ISLPED, 2022)

QMLP: An Error-Tolerant Nonlinear Quantum MLP Architecture using Parameterized Two-Qubit Gates. - Cheng Chu; Nai-Hui Chia; Lei Jiang 001; Fan Chen 001 (ISLPED, 2022)

CryptoLight: An Electro-Optical Accelerator for Fully Homomorphic Encryption. - Mengxin Zheng; Qian Lou; Fan Chen 001; Lei Jiang 001; Yongxin Zhu 001 (NANOARCH, 2022)

QTROJAN: A Circuit Backdoor Against Quantum Neural Networks. - Cheng Chu; Lei Jiang 001; Martin Swany; Fan Chen 001 (ICASSP, 2023)

IQGAN: Robust Quantum Generative Adversarial Network for Image Synthesis On NISQ Devices. - Cheng Chu; Grant Skipper; Martin Swany; Fan Chen 001 (ICASSP, 2023)

PriML: An Electro-Optical Accelerator for Private Machine Learning on Encrypted Data. - Mengxin Zheng; Fan Chen 001; Lei Jiang 001; Qian Lou (ISQED, 2023)

QDoor: Exploiting Approximate Synthesis for Backdoor Attacks in Quantum Neural Networks. - Cheng Chu; Fan Chen 001; Philip Richerme; Lei Jiang 001 (QCE, 2023)

CryptoQFL: Quantum Federated Learning on Encrypted Data. - Cheng Chu; Lei Jiang 001; Fan Chen 001 (QCE, 2023)

ReFloat: Low-Cost Floating-Point Processing in ReRAM for Accelerating Iterative Linear Solvers. - Linghao Song; Fan Chen 001; Hai Li 001; Yiran Chen 001 (SC, 2023)

LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models. - Ahmad Faiz; Sotaro Kaneda; Ruhan Wang; Rita Chukwunyere Osi; Parteek Sharma; Fan Chen 001; Lei Jiang 001 (CoRR, 2023)

Sky-Sorter: A Processing-in-Memory Architecture for Large-Scale Sorting. - Farzaneh Zokaee; Fan Chen 001; Guangyu Sun 003; Lei Jiang 001 (IEEE Trans. Computers, 2023)

JustQ: Automated Deployment of Fair and Accurate Quantum Neural Networks. - Ruhan Wang; Fahiz Baba-Yara; Fan Chen 001 (ASPDAC, 2024)

Special Session: End-To-End Carbon Footprint Assessment and Modeling of Deep Learning. - Ahmad Faiz; Lei Jiang 001; Fan Chen 001 (CODES+ISSS, 2024)

TITAN: A Fast and Distributed Large-Scale Trapped-Ion NISQ Computer. - Cheng Chu; Zhenxiao Fu; Yilun Xu; Gang Huang; Hausi A. Müller; Fan Chen 001; Lei Jiang 001 (DAC, 2024)

Late Breaking Results: Extracting QNNs from NISQ Computers via Ensemble Learning. - Zhenxiao Fu; Fan Chen 001 (DAC, 2024)

LLMCarbon: Modeling the End-to-End Carbon Footprint of Large Language Models. - Ahmad Faiz; Sotaro Kaneda; Ruhan Wang; Rita Chukwunyere Osi; Prateek Sharma; Fan Chen 001; Lei Jiang 001 (ICLR, 2024)

QuantumLeak: Stealing Quantum Neural Networks from Cloud-based NISQ Machines. - Zhenxiao Fu; Min Yang; Cheng Chu; Yilun Xu; Gang Huang; Fan Chen 001 (IJCNN, 2024)

System Support for Environmentally Sustainable Computing in Data Centers. - Fan Chen 001 (ISVLSI, 2024)

Posters Program: 2024 IEEE International Conference on Quantum Computing and Engineering. - Fan Chen 001; Huiyang Zhou (QCE, 2024)

TITAN: A Distributed Large-Scale Trapped-Ion NISQ Computer. - Cheng Chu; Zhenxiao Fu; Yilun Xu; Gang Huang; Hausi A. Müller; Fan Chen 001; Lei Jiang 001 (CoRR, 2024)

IoTCO2: Assessing the End-To-End Carbon Footprint of Internet-of-Things-Enabled Deep Learning. - Ahmad Faiz; Shahzeen Attari; Gayle Buck; Fan Chen 001; Lei Jiang 001 (CoRR, 2024)

LLMCO2: Advancing Accurate Carbon Footprint Prediction for LLM Inferences. - Zhenxiao Fu; Fan Chen 001; Shan Zhou; Haitong Li; Lei Jiang 001 (CoRR, 2024)

LSTM-QGAN: Scalable NISQ Generative Adversarial Network. - Cheng Chu; Aishwarya Hastak; Fan Chen 001 (ICASSP, 2025)

Quantum Neural Network Extraction Attack via Split Co-Teaching. - Zhenxiao Fu; Fan Chen 001 (ICASSP Workshops, 2025)

CopyQNN: Quantum Neural Network Extraction Attack under Varying Quantum Noise. - Zhenxiao Fu; Leyi Zhao; Xuhong Zhang 001; Yilun Xu; Gang Huang; Fan Chen 001 (CoRR, 2025)