Publications



For a complete list of my publications, please visit my Google Scholar Profile.

* indicates equal contributions.

    Book


  • 创新工场讲AI课：从知识到实践 (Chinese)
    李开复, 王咏刚, 张潼, 宋彦, 屠可伟, 张发恩, 唐剑, 张弥, 吴佳洪, 刘宁.
    电子工业出版社, 2021.
    [Purchase Link]

    • Survey and Vision Papers


  • Artificial Intelligence of Things: A Survey
    Shakhrul Iman Siam, Hyunho Ahn, Li Liu, Samiul Alam, Hui Shen, Zhichao Cao, Ness Shroff, Bhaskar Krishnamachari, Mani Srivastava, Mi Zhang.
    ACM Transactions on Sensor Networks (ACM TOSN), August 2024.
    [Paper | BibTex | Paper List]

  • The Internet of Things in the Era of Generative AI: Vision and Challenges
    Xin Wang, Zhongwei Wan, Arvin Hekmati, Mingyu Zong, Samiul Alam, Mi Zhang, Bhaskar Krishnamachari.
    IEEE Internet Computing Magazine (IEEE IC), August 2024.
    Feature Article
    [Paper | BibTex]

  • Efficient Large Language Models: A Survey
    Zhongwei Wan, Xin Wang, Che Liu, Samiul Alam, Yu Zheng, Jiachen Liu, Zhongnan Qu, Shen Yan, Yi Zhu, Quanlu Zhang, Mosharaf Chowdhury, Mi Zhang.
    Transactions on Machine Learning Research (TMLR), May 2024.
    [Paper | BibTex | Paper List]

  • Federated Learning for Internet of Things: Applications, Challenges, and Opportunities
    Tuo Zhang, Lei Gao, Chaoyang He, Mi Zhang, Bhaskar Krishnamachari, and Salman Avestimehr.
    IEEE Internet of Things Magazine (IEEE IoTM), March 2022.
    [Paper | BibTex]

  • Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning
    David C. Mohr, Mi Zhang, and Stephen M. Schueller.
    Annual Review of Clinical Psychology (ARCP), March 2017.
    Impact Factor: 17.8
    Invited Article
    [Link | Paper | BibTex]

    • Preprint


  • SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression
    Xin Wang, Yu Zheng, Zhongwei Wan, Mi Zhang.
    [Paper | Code]

  • D2O: Dynamic Discriminative Operations for Efficient Generative Inference of Large Language Models
    Zhongwei Wan, Xinjian Wu, Yu Zhang, Yi Xin, Chaofan Tao, Zhihong Zhu, Xin Wang, Siqi Luo, Jing Xiong, Mi Zhang.
    [Paper]

  • MEIT: Multi-Modal Electrocardiogram Instruction Tuning on Large Language Models for Report Generation
    Zhongwei Wan, Che Liu, Xin Wang, Chaofan Tao, Hui Shen, Zhenwu Peng, Jie Fu, Rossella Arcucci, Huaxiu Yao, Mi Zhang.
    [Paper]

  • GPT-FL: Generative Pre-trained Model-Assisted Federated Learning
    Tuo Zhang, Tiantian Feng, Samiul Alam, Mi Zhang, Shrikanth S Narayanan, Salman Avestimehr.
    [Paper]

    • 2024


  • ChirpTransformer: Versatile LoRa Encoding for Low-Power Wide-Area IoT
    Chenning Li, Yidong Ren, Shuai Tong, Shakhrul Iman Siam, Mi Zhang, Jiliang Wang, Yunhao Liu, Zhichao Cao.
    ACM International Conference on Mobile Systems, Applications, and Services (MobiSys'24).
    Acceptance Rate: 43/263 = 16.3%
    [Paper | BibTex]

  • Demeter: Reliable Cross-Soil LPWAN with Low-Cost Signal Polarization Alignment
    Yidong Ren, Wei Sun, Jialuo Du, Huaili Zeng, Younsuk Dong, Mi Zhang, Shigang Chen, Yunhao Liu, Tianxing Li, Zhichao Cao.
    ACM International Conference on Mobile Computing and Networking (MobiCom'24).
    Acceptance Rate: 103/494 = 20.9%
    [Paper | BibTex]

  • FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of Things
    Samiul Alam, Tuo Zhang, Tiantian Feng, Hui Shen, Zhichao Cao, Dong Zhao, JeongGil Ko, Kiran Somasundaram, Shrikanth S. Narayanan, Salman Avestimehr, Mi Zhang.
    Journal of Data-centric Machine Learning Research (DMLR), 2024.
    [Paper | BibTex | Code]

  • ETP: Learning Transferable ECG Representations via ECG-Text Pre-Training
    Che Liu, Zhongwei Wan, Sibo Cheng, Mi Zhang, Rossella Arcucci.
    IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'24).
    [Paper | BibTex]

  • Famba-V: Fast Vision Mamba with Cross-Layer Token Fusion
    Hui Shen, Zhongwei Wan, Xin Wang, and Mi Zhang.
    European Conference on Computer Vision (ECCV'24) Workshop on Computational Aspects of Deep Learning.
    Best Paper Award
    [Paper | BibTex]

  • Ph.D. Thesis: Efficient Architecture and Data Manipulation for Deep Learning Systems
    Yu Zheng, 2024.

    • 2023


  • AttFL: A Personalized Federated Learning Framework for Time-series Mobile and Embedded Sensor Data Processing
    JaeYeon Park, Kichang Lee, Sungmin Lee, Mi Zhang, JeongGil Ko.
    ACM international joint conference on Pervasive and Ubiquitous Computing (UbiComp'23).
    [Paper | BibTex]

  • FedMultimodal: A Benchmark For Multimodal Federated Learning
    Tiantian Feng, Digbalay Bose, Tuo Zhang, Rajat Hebbar, Anil Ramakrishna, Rahul Gupta, Mi Zhang, Salman Avestimehr, and Shrikanth Narayanan.
    ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'23).
    [Paper | BibTex]

  • FedAudio: A Federated Learning Benchmark for Audio Tasks
    Tuo Zhang, Tiantian Feng, Samiul Alam, Sunwoo Lee, Mi Zhang, Shrikanth Narayanan, and Salman Avestimehr.
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'23).
    [Paper | BibTex]

  • TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training
    Tuo Zhang, Lei Gao, Sunwoo Lee, Mi Zhang, and Salman Avestimehr.
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR'23) Workshop on Federated Learning for Computer Vision.
    [Paper | BibTex]

  • NELoRa-Bench: A Benchmark for Neural-enhanced LoRa Demodulation
    Jialuo Du, Yidong Ren, Mi Zhang, Yunhao Liu, and Zhichao Cao.
    International Conference on Learning Representations (ICLR'23) Workshop on Machine Learning for IoT (Oral).
    [Paper | BibTex]

  • VideoCoCa: Video-Text Modeling with Zero-Shot Transfer from Contrastive Captioners
    Shen Yan, Tao Zhu, Zirui Wang, Yuan Cao, Mi Zhang, Soham Ghosh, Yonghui Wu, Jiahui Yu.
    arXiv:2212.04979
    [Paper | BibTex]

  • AutoTaskFormer: Searching Vision Transformers for Multi-task Learning
    Yang Liu, Shen Yan, Yuge Zhang, Kan Ren, Quanlu Zhang, Zebin Ren, Deng Cai, Mi Zhang.
    arXiv:2304.08756
    [Paper | BibTex]

  • Master Thesis: Federated Learning Benchmarks and Frameworks for Artificial Intelligence of Things
    Samiul Alam, 2023.

    • 2022


  • FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction
    Samiul Alam, Luyang Liu, Ming Yan, and Mi Zhang.
    Conference on Neural Information Processing Systems (NeurIPS'22).
    Acceptance Rate: 2665/10411 = 25.6%
    [Paper | BibTex | Code｜ Poster]

  • PyramidFL: A Fine-grained Client Selection Framework for Efficient Federated Learning
    Chenning Li, Xiao Zeng, Mi Zhang, and Zhichao Cao.
    ACM International Conference on Mobile Computing and Networking (MobiCom'22).
    Acceptance Rate: 56/314 = 17.8%
    [Paper | BibTex]

  • FedSEA: A Semi-Asynchronous Federated Learning Framework for Extremely Heterogeneous Devices
    Jingwei Sun, Ang Li, Lin Duan, Samiul Alam, Xuliang Deng, Xin Guo, Haiming Wang, Maria Gorlatova, Mi Zhang, Hai Li, Yiran Chen.
    ACM Conference on Embedded Networked Sensor Systems (SenSys'22).
    Acceptance Rate: 52/208 = 25%
    [Paper | BibTex]

  • FedTune: Automatic Tuning of Federated Learning Hyper-Parameters from System Perspective
    Huanle Zhang, Mi Zhang, Xin Liu, Prasant Mohapatra, and Michael Delucia.
    IEEE Military Communications Conference (MILCOM'22).
    [Paper | BibTex]

  • Deep AutoAugment
    Yu Zheng, Zhi Zhang, Shen Yan, and Mi Zhang.
    International Conference on Learning Representations (ICLR'22).
    Acceptance Rate: 1095/3391 = 32.3%
    [Paper | BibTex | Code｜ Leaderboard | Poster | Slides]
    Media Coverage: [Synced]

  • Multiview Transformers for Video Recognition
    Shen Yan, Xuehan Xiong, Anurag Arnab, Zhichao Lu, Mi Zhang, Chen Sun, Cordelia Schmid.
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'22).
    Acceptance Rate: 2067/8161 = 25.3%
    [Paper | BibTex | Code | Leaderboard]

  • Ph.D. Thesis: New Perspectives in Neural Architecture Search: Architecture Embeddings, Efficient Performance Estimations, and their Applications
    Shen Yan, 2022.

    • 2021


  • A Field Guide to Federated Optimization
    Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Aguera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecny, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtarik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu.
    [Paper | BibTex]

  • Mercury: Efficient On-Device Distributed DNN Training via Stochastic Importance Sampling
    Xiao Zeng, Ming Yan, and Mi Zhang.
    ACM Conference on Embedded Networked Sensor Systems (SenSys'21).
    Acceptance Rate: 25/139 = 18%
    [Paper | BibTex]

  • FedMask: Joint Computation and Communication-Efficient Personalized Federated Learning via Heterogeneous Masking
    Ang Li, Jingwei Sun, Xiao Zeng, Mi Zhang, Hai Li, and Yiran Chen.
    ACM Conference on Embedded Networked Sensor Systems (SenSys'21).
    Acceptance Rate: 25/139 = 18%
    [Paper | BibTex]

  • NELoRa: Towards Ultra-low SNR LoRa Communication with Neural-enhanced Demodulation
    Chenning Li, Hanqing Guo, Shuai Tong, Xiao Zeng, Zhichao Cao, Mi Zhang, Qiben Yan, Li Xiao, Jiliang Wang, and Yunhao Liu.
    ACM Conference on Embedded Networked Sensor Systems (SenSys'21).
    Acceptance Rate: 25/139 = 18%
    Best Paper Award | ACM SIGMOBILE Research Highlight [Highlight Article]
    [Paper | BibTex]

  • DeepLoRa: Learning Accurate Path Loss Model for Long Distance Links in LPWAN
    Li Liu, Yuguang Yao, Zhichao Cao, and Mi Zhang.
    IEEE International Conference on Computer Communications (INFOCOM'21).
    Acceptance Rate: 252/1266 = 19.9%
    [Paper | BibTex]

  • CATE: Computation-aware Neural Architecture Encoding with Transformers
    Shen Yan, Kaiqiang Song, Fei Liu, and Mi Zhang.
    International Conference on Machine Learning (ICML'21).
    Acceptance Rate: 166/5513 = 3% (Long Talk)
    [Paper | BibTex | Code | Poster | Presentation]

  • Deep AutoAugment
    Yu Zheng, Zhi Zhang, Shen Yan, and Mi Zhang.
    International Conference on Machine Learning (ICML'21) Workshop on Machine Learning for Data.
    Note: the full version is accepted to ICLR'22.

  • Towards Position-Independent Sensing for Gesture Recognition with Wi-Fi
    Ruiyang Gao, Mi Zhang, Jie Zhang, Yang Li, Enze Yi, Dan Wu, Leye Wang, and Daqing Zhang.
    ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'21).
    [Paper | BibTex]

  • Ph.D. Thesis: Collaborative Distributed Deep Learning Systems on the Edges
    Xiao Zeng, 2021.

    • 2020


  • Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?
    Shen Yan, Yu Zheng, Wei Ao, Xiao Zeng, and Mi Zhang.
    Conference on Neural Information Processing Systems (NeurIPS'20).
    Acceptance Rate: 1900/9454 = 20.1%
    [Paper | BibTex | Code | Poster | Presentation]

  • FedML: A Research Library and Benchmark for Federated Machine Learning
    Chaoyang He, Songze Li, Jinhyun So, Xiao Zeng, Mi Zhang, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram, Salman Avestimehr.
    Conference on Neural Information Processing Systems (NeurIPS'20) Federated Learning Workshop (Spotlight).
    Best Paper Award
    [Paper | BibTex | Code]

  • MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and Resolution
    Taojiannan Yang, Sijie Zhu, Chen Chen, Shen Yan, Mi Zhang, and Andrew Willis.
    European Conference on Computer Vision (ECCV'20).
    Acceptance Rate: 104/5025 = 2% (Oral)
    [Paper | BibTex | Code]

  • FlexDNN: Input-Adaptive On-Device Deep Learning for Efficient Mobile Vision
    Biyi Fang, Xiao Zeng, Faen Zhang, Hui Xu, and Mi Zhang.
    ACM/IEEE Symposium on Edge Computing (SEC'20).
    Acceptance Rate: 21/96 = 21.9%
    Best Paper Award Nominee
    [Paper | BibTex]

  • Distream: Scaling Live Video Analytics with Workload-Adaptive Distributed Edge Intelligence
    Xiao Zeng, Biyi Fang, Haichen Shen, and Mi Zhang.
    ACM Conference on Embedded Networked Sensor Systems (SenSys'20).
    Acceptance Rate: 43/213 = 20.2%
    [Paper | BibTex]

  • Wi-Fi See It All: Generative Adversarial Network-augmented Versatile Wi-Fi Imaging
    Chenning Li, Zheng Liu, Yuguang Yao, Zhichao Cao, Mi Zhang, and Yunhao Liu.
    ACM Conference on Embedded Networked Sensor Systems (SenSys'20).
    Acceptance Rate: 43/213 = 20.2%
    [Paper | BibTex]

  • SecWIR: Securing Smart Home IoT Communications via Wi-Fi Routers with Embedded Intelligence
    Xinyu Lei, Guan-Hua Tu, Chi-Yu Li, Tian Xie, and Mi Zhang.
    ACM International Conference on Mobile Systems, Applications, and Services (MobiSys'20).
    Acceptance Rate: 34/175 = 19.4%
    [Paper | BibTex]

  • SCYLLA: QoE-aware Continuous Mobile Vision with FPGA-based Dynamic Deep Neural Network Reconfiguration
    Shuang Jiang, Zhiyao Ma, Xiao Zeng, Chenren Xu, Mi Zhang, Chen Zhang, and Yunxin Liu.
    IEEE International Conference on Computer Communications (INFOCOM'20).
    Acceptance Rate: 268/1354 = 19.8%
    [Paper | BibTex]

  • Deep Learning in the Era of Edge Computing: Challenges and Opportunities
    Mi Zhang, Faen Zhang, Nicholas D. Lane, Yuanchao Shu, Xiao Zeng, Biyi Fang, Shen Yan, and Hui Xu.
    Book chapter in Fog Computing: Theory and Practice, Wiley, 2020.
    Invited Article
    [Paper | BibTex]

    • 2019


  • MSUNet: A Framework for Designing Tiny Neural Networks for On-Device AI
    Yu Zheng*, Shen Yan*, and Mi Zhang.
    Conference on Neural Information Processing Systems (NeurIPS'19) Google MicroNet Challenge.
    Google MicroNet Challenge (CIFAR-100 Track) 4th Place Winner (1st Place in U.S. and Canada)
    [Code]
    Media Coverage: [MSU Today]

  • HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking
    Shen Yan, Biyi Fang, Faen Zhang, Yu Zheng, Xiao Zeng, Hui Xu, and Mi Zhang.
    International Conference on Computer Vision (ICCV'19) Neural Architects Workshop.
    Best Paper Award Candidate
    [Paper | BibTex]
    Media Coverage: [JiQiZhiXin]

  • Federated Learning: The Future of Distributed Machine Learning
    Mi Zhang.
    SyncedReview @ Medium, 2019.
    [Link]
    Invited Article

  • AutoML Mobile: Automated ML Model Design for Every Mobile Device
    Mi Zhang.
    SyncedReview @ Medium, 2019.
    [Link]
    Invited Article

  • Mobile Sensing of Alertness, Sleep, and Circadian Rhythm: Hardware and Software Platforms
    Akane Sano, Tauhidur Rahman, Mi Zhang, Deepak Ganesan, and Tanzeem Choudhury.
    ACM SIGMOBILE Mobile Computing and Communications Review (GetMobile), Volume 23, Issue 3, 2019.
    Invited Article
    [Paper | BibTex]

  • Communication Challenges in the IoT
    Mi Zhang, Xiaofan Jiang, and Steve Hodges.
    IEEE Pervasive Computing Magazine (IEEE Pervasive Computing), Volume 18, Issue 1, 2019.
    Impact Factor: 4.41
    Guest Editors' Introduction

  • Ph.D. Thesis: Adaptive On-device Deep Learning Systems
    Biyi Fang, 2019.

    • 2018


  • NestDNN: Resource-Aware Multi-Tenant On-Device Deep Learning for Continuous Mobile Vision
    Biyi Fang*, Xiao Zeng*, and Mi Zhang.
    ACM International Conference on Mobile Computing and Networking (MobiCom'18).
    Acceptance Rate: 42/187 = 22.5%
    [Paper | BibTex | Video]
    Media Coverage: [JiQiZhiXin]

  • Efficient Federated Learning via Variational Dropout
    Wei Du, Xiao Zeng, Ming Yan, and Mi Zhang.
    OpenReview
    [Paper]

  • The Dark Side of Operational Wi-Fi Calling Services
    Tian Xie, Guan-Hua Tu, Chi-Yu Li, Chunyi Peng, Jiawei Li, and Mi Zhang.
    IEEE Conference on Communications and Network Security (CNS'18).
    Acceptance Rate: 52/181 = 28.7%
    Best Paper Award | Google Security Reward
    [Paper | BibTex]

  • When Virtual Reality Meets Internet of Things in the Gym: Enabling Immersive Interactive Machine Exercises
    Fazlay Rabbi*, Taiwoo Park*, Biyi Fang, Mi Zhang, and Youngki Lee.
    ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'18).
    [Paper | BibTex]

  • When Mixed Reality Meets Internet of Things: Toward the Realization of Ubiquitous Mixed Reality
    Taiwoo Park, Mi Zhang, and Youngki Lee.
    ACM SIGMOBILE Mobile Computing and Communications Review (GetMobile), Volume 22, Issue 1, 2018.
    Invited Article
    [Paper | BibTex]

  • Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study
    Jingbo Meng, Syed Ali Hussain, David C. Mohr, Mary Czerwinski, and Mi Zhang.
    Journal of Medical Internet Research (JMIR) Special Issue on Computing and Mental Health, 2018.
    Impact Factor: 5.175
    [Link | Paper | BibTex]

    • 2017


  • MobileDeepPill: A Small-Footprint Mobile Deep Learning System for Recognizing Unconstrained Pill Images
    Xiao Zeng, Kai Cao, and Mi Zhang.
    ACM International Conference on Mobile Systems, Applications, and Services (MobiSys'17).
    Acceptance Rate: 34/188 = 18%
    NIH Pill Image Recognition Challenge First Place Winner
    [Paper | BibTex | Video]
    Media Coverage: [NIH | ABC 7 (TV) | MSU Today]

  • DeepASL: Enabling Ubiquitous and Non-Intrusive Word and Sentence-Level Sign Language Translation
    Biyi Fang, Jillian Co, and Mi Zhang.
    ACM Conference on Embedded Networked Sensor Systems (SenSys'17).
    Acceptance Rate: 26/151 = 17%
    [Paper | BibTex]
    Media Coverage: [NSF (video) | MSU (video) | NVIDIA | Smithsonian | NPR (radio interview) | MSU Today | AAU | Futurity]

  • SharpEar: Real-Time Speech Enhancement in Noisy Environments (Poster)
    Xiao Zeng, Kai Cao, Haochen Sun, and Mi Zhang.
    ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'17).
    NSF Hearables Challenge Third Place Winner
    Invited Presentation
    Media Coverage: [NSF | ACM TechNews | MSU Today | AAU | R&D Magazine | The University Network]

  • Helping Universities Combat Depression with Mobile Technology
    Mi Zhang, David C. Mohr, and Jingbo Meng.
    The Conversation, 2017.
    Invited Article
    [Link]
    Media Coverage: [NSF (video) | Smithsonian | MSU Today | EdTech | Campus Technology | eCampusNews]

    • 2016


  • BodyScan: Enabling Radio-based Sensing on Wearable Devices for Contactless Activity and Vital Sign Monitoring
    Biyi Fang, Nicholas D. Lane, Mi Zhang, Aidan Boran, and Fahim Kawsar.
    ACM International Conference on Mobile Systems, Applications, and Services (MobiSys'16).
    Acceptance Rate: 31/197 = 15.7%
    [Paper | BibTex | Video]

  • HeadScan: A Wearable System for Radio-based Sensing of Head and Mouth-related Activities
    Biyi Fang, Nicholas D. Lane, Mi Zhang, and Fahim Kawsar.
    ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN'16).
    Acceptance Rate: 23/117 = 19.7%
    [Paper | BibTex]
    Media Coverage: [Stanford Medicine | MedGadget | Futurity | MSU Today | Fox 2 (TV interview) | ReadWrite]

  • AirSense: An Intelligent Home-based Sensing System for Indoor Air Quality Analytics
    Biyi Fang, Qiumin Xu, Taiwoo Park, and Mi Zhang.
    ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'16).
    Acceptance Rate: 114/481 = 23.7%
    [Paper | BibTex]
    Media Coverage: [The Atlantic | Futurity | MSU Today]

    • 2015


  • DoppleSleep: A Contactless Unobtrusive Sleep Sensing System Using Short-Range Doppler Radar
    Tauhidur Rahman, Alexander Adams, Ruth Ravichandran, Mi Zhang, Shwetak Patel, Julie Kientz, and Tanzeem Choudhury.
    ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'15).
    Acceptance Rate: 93/394 = 23.6%
    Best Paper Award Honorable Mention
    [Paper | BibTex]
    Media Coverage: [MIT Technology Review]

  • MyBehavior: Automatic Personalized Health Feedback from User Behavior and Preference using Smartphones
    Mashfiqui Rabbi, Min Hane Aung, Mi Zhang, and Tanzeem Choudhury.
    ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'15).
    Acceptance Rate: 93/394 = 23.6%
    [Paper | BibTex]
    Media Coverage: [MIT Technology Review | Mashable]

  • Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study
    Sohrob Saeb, Mi Zhang, Christopher J. Karr, Stephen M. Schueller, Marya E. Corden, Konrad P. Kording, and David C. Mohr.
    Journal of Medical Internet Research (JMIR), Volume 17, Issue 7, Pages e175, 2015.
    Impact Factor: 5.175
    JMIR All-Time Top Article
    [Link | Paper | BibTex]
    Media Coverage: [TIME | CNN | TechCrunch | The Verge | CBS News | Fox News | Discovery News | Daily Mail | The Times | Newsweek | Mirror | The Telegraph | The Washington Post | The Huffington Post | Los Angeles Times | Chicago Tribune | Futurity | WebMD | US News]

  • The Relationship between Clinical, Momentary, and Sensor-based Assessment of Depression
    Sohrob Saeb, Mi Zhang, Mary Kwasney, Christopher J. Karr, Konrad Kording, and David C. Mohr.
    International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth'15).
    Acceptance Rate: 38%
    [Paper | BibTex]

  • Automated Personalized Feedback for Physical Activity and Dietary Behavior Change with Mobile Phones: A Randomized Controlled Trial on Adults
    Mashfiqui Rabbi, Angela Pfammatter, Mi Zhang, Bonnie Spring, and Tanzeem Choudhury.
    Journal of Medical Internet Research (JMIR) mHealth and uHealth, Volume 3, Issue 2, Pages e42, 2015.
    Impact Factor: 4.636
    [Link | Paper | BibTex]
    Media Coverage: [MobiHealth News]

  • An Intelligent Crowd-Worker Selection Approach for Reliable Content Labeling of Food Images
    Mashfiqui Rabbi, Jean Costa, Fabian Okeke, Max Schachere, Mi Zhang, and Tanzeem Choudhury.
    ACM International Conference on Wireless Health (WH'15).
    Acceptance Rate: 28/106 = 26.4%
    [Paper | BibTex]

    • 2014


  • BodyBeat: A Mobile System for Sensing Non-Speech Body Sounds
    Tauhidur Rahman, Alexander Adams, Mi Zhang, Erin Cherry, Bobby Zhou, Huaishu Peng, and Tanzeem Choudhury.
    ACM International Conference on Mobile Systems, Applications, and Services (MobiSys'14).
    Acceptance Rate: 25/185 = 13.5%
    ACM SIGMOBILE Research Highlight [Highlight Article]
    [Paper | BibTex]
    Media Coverage: [MIT Technology Review | Wall Street Journal | New Scientist]

  • Towards Accurate Non-Intrusive Recollection of Stress Levels Using Mobile Sensing and Contextual Recall
    Tauhidur Rahman, Mi Zhang, Stephen Voida, and Tanzeem Choudhury.
    International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth'14).
    Acceptance Rate: 26%
    [Paper | BibTex]

    • 2013 and Earlier


  • Human Daily Activity Recognition with Sparse Representation Using Wearable Sensors
     Mi Zhang and Alexander A. Sawchuk.
    IEEE Journal of Biomedical and Health Informatics (J-BHI), Volume 17, Issue 3, Pages 553-560, 2013.
    Impact Factor: 3.451

  • Towards Practical Energy Expenditure Estimation with Mobile Phones
     Harshvardhan Vathsangam, Mi Zhang, Alexander Tarashansky, Alexander A. Sawchuk, and Gaurav S. Sukhatme.
    The Annual Asilomar Conference on Signals, Systems, and Computers (ASILOMAR), 2013.

  • Motion Primitive-Based Human Activity Recognition Using a Bag-of-Features Approach
     Mi Zhang and Alexander A. Sawchuk.
    ACM SIGHIT International Health Informatics Symposium (IHI), 2012.
    Acceptance Rate: 18%

  • Towards Pervasive Physical Rehabilitation Using Microsoft Kinect
     Chien-Yen Chang, Belinda Lange, Mi Zhang, Sebastian Koenig, Phil Requejo, Noom Somboon, Alexander Sawchuk, Albert Rizzo.
    International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2012.
    Acceptance Rate: 30%

  • Beyond the Standard Clinical Rating Scales: Fine-Grained Assessment of Post-Stroke Motor Functionality Using Wearable Inertial Sensors
     Mi Zhang, Belinda Lange, Chien-Yen Chang, Alexander A. Sawchuk, and Albert A. Rizzo.
    International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2012.

  • USC-HAD: A Daily Activity Dataset for Ubiquitous Activity Recognition Using Wearable Sensors
     Mi Zhang and Alexander A. Sawchuk.
    ACM International Conference on Ubiquitous Computing (UbiComp) Workshop, 2012.

  • A Preliminary Study of Sensing Appliance Usage for Human Activity Recognition Using Mobile Magnetometer
     Mi Zhang and Alexander A. Sawchuk.
    ACM International Conference on Ubiquitous Computing (UbiComp) Workshop, 2012.

  • Sparse Representation for Motion Primitive-Based Human Activity Modeling and Recognition Using Wearable Sensors
     Mi Zhang, Wenyao Xu, Alexander A. Sawchuk, and Majid Sarrafzadeh.
    International Conference on Pattern Recognition (ICPR), 2012.

  • Robust Human Activity and Sensor Location Co-Recognition via Sparse Signal Representation
     Wenyao Xu, Mi Zhang, Alexander A. Sawchuk, and Majid Sarrafzadeh.
    IEEE Transactions on Biomedical Engineering (TBME), Volume 59, Issue 11, Pages 3169-3176, 2012.
    Impact Factor: 3.577

  • Co-Recognition of Human Activity and Sensor Location via Compressed Sensing in Wearable Body Sensor Networks
     Wenyao Xu, Mi Zhang, Alexander A. Sawchuk, and Majid Sarrafzadeh.
    IEEE International Conference on Wearable and Implantable Body Sensor Networks (BSN), 2012.

  • Manifold Learning and Recognition of Human Activity Using Body-Area Sensors
     Mi Zhang and Alexander A. Sawchuk.
    IEEE International Conference on Machine Learning and Applications (ICMLA), 2011.
    Acceptance Rate: 27%

  • A Feature Selection-Based Framework for Human Activity Recognition Using Wearable Multimodal Sensors
     Mi Zhang and Alexander A. Sawchuk.
    International Conference on Body Area Networks (BodyNets), 2011.

  • Context-Aware Fall Detection Using A Bayesian Network
     Mi Zhang and Alexander A. Sawchuk.
    ACM International Conference on Ubiquitous Computing (UbiComp) Workshop, 2011.

  • OCRdroid: A Framework to Digitize Text Using Mobile Phones
     Mi Zhang, Anand Joshi, Ritesh Kadmawala, Karthik Dantu, Sameera Poduri, and Gaurav S. Sukhatme.
    International Conference on Mobile Computing, Applications and Services (MobiCASE), 2009.

  • A Customizable Framework of Body Area Sensor Network for Rehabilitation
     Mi Zhang and Alexander A. Sawchuk.
    International Symposium on Applied Sciences in Biomedical and Communication Technologies (ISABEL), 2009.



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