Yue (Daniel) Zhang | 张越

Email: happydzhang [at] gmail [dot] com

Hi! This is Daniel! I am a research scientist at Amazon's Alexa AI. I received my Ph.D. in Computer Science and Engineering at University of Notre Dame under the supervision of Prof. Dong Wang. I got my master's degree in Information Security from Purdue University and I attained my bachelor's degree in Information Security Engineering from SJTU. I have previously worked as a full-time Systems Engineer at Carfax, Inc.

My research area lies in the intersection of machine learning/artificial intelligence, edge computing, and human-in-the-loop systems. My research topics include:

Machine Learning, Artificial Intelligence, Data Science, Recommender Systems

Edge Computing, Federated Learning, Distributed Systems, Edge Intelligence, Mobile Sensing, IoT

Human-AI Systems, Fairness in Machine Learning, Explainable AI, Crowdsourcing

I have published 50+ peer-reviewed conference/journal papers, including 20+ first-authored ones. These papers were published in both top machine learning and top systems venues such as AAAI, RTSS, INFOCOM, ICDCS, RTAS, SEC, IoTDI, KBS, BigData, ASONAM, etc. My H-Index is 13. [CV] [Google Scholar] [Project Highlights]

I am the recipient of two of the most prestigious awards - Outstanding Graduate Research Award and Outstanding Graduate Teaching Award at the University of Notre Dame. I was offered IBM Social Good Fellowship in 2020.

NEWS - My PhD advisor Dr. Wang, director of Social Sensing lab, is actively recruiting phd students for 2021. Please see [Recruitment Flyer] and reach out!

Recent Publications

Full publication list is available here.

[IEEE IoT Journal] Towards Privacy-aware Task Allocation in Social Sensing based Edge Computing Systems
Authors: Daniel (Yue) Zhang, Yue Ma, X. Sharon Hu, and Dong Wang.
Published In: IEEE Internet of Things Journal (IF: 9.5), 2020, in press.
[IEEE Trans. on BigData] Sparse User Check-in Venue Prediction By Exploring Latent Decision Contexts From Location-Based Social Networks
Authors: Daniel (Yue) Zhang, Yang Zhang, Qi Li, and Dong Wang.
Published In: IEEE Transactions on BigData, 2020, in press.
[AAAI '20] Crowd-assisted Disaster Scene Assessment with Human-AI Interactive Attention
Authors: Daniel (Yue) Zhang, Yifeng Huang, Yang Zhang, and Dong Wang.
Published In: The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020. Oral Presentation (Acceptance rate: 20.6%)
[INFOCOM '20] SocialDrone: An Integrated Social Media and Drone Sensing System for Reliable Disaster Response
Authors: Md Tahmid Rashid, Daniel (Yue) Zhang and Dong Wang.
Published In: IEEE International Conference on Computer Communications (INFOCOM), 2020.(Acceptance rate: 19.8%)
[RTSS '19] EdgeBatch: Towards AI-empowered Optimal Task Batching in Intelligent Edge Systems
Authors: Daniel (Yue) Zhang, Nathan Vance, Yang Zhang, Md Tahmid Rashid and Dong Wang.
Published In: 40th IEEE Real-Time Systems Symposium (RTSS), 2019.
[ASONAM '19] Through The Eyes of A Poet: Classical Poetry Recommendation with Visual Input on Social Media
Authors: Daniel (Yue) Zhang, Bo Ni, Qiyu Zhi, Thomas Plummer, Qi Li, Hao Zheng, Qingkai Zeng, Yang Zhang and Dong Wang.
Published In: 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). (Acceptance rate: 14%)
[CIC '19] Social Edge Intelligence: Integrating Human and Artificial Intelligence at the Edge
Authors: Dong Wang, Daniel (Yue) Zhang, Yang Zhang, Md Tahmid Rashid, Lanyu Shang and Na Wei .
Published In: IEEE International Conference on Collaboration and Internet Computing (CIC), 2019.
[ICCCN '19] When Social Sensing Meets Edge Computing: Vision and Challenges (Invited Paper)
Authors: Daniel (Yue) Zhang, Nathan Vance and Dong Wang.
Published In: IEEE International Conference on Computer Communications and Networks (ICCCN), 2019.
[ICDCS '19] CrowdLearn: A Crowd-AI Hybrid System for Deep Learning-based Damage Assessment Applications
Authors: Daniel (Yue) Zhang, Yang Zhang, Qi Li, Thomas Plummer and Dong Wang.
Published In: IEEE International Conference on Distributed Computing Systems (ICDCS), 2019. (Acceptance rate: 19.6%)
[IoTDI '19] HeteroEdge: Taming The Heterogeneity of Edge Computing System in Social Sensing
Authors: Daniel (Yue) Zhang, Md Tahmid Rashid, Xukun Li, Nathan Vance and Dong Wang.
Published In: ACM/IEEE Conference on Internet of Things Design and Implementation (IoTDI), 2019.
[INFOCOM '19] An Integrated Top-down and Bottom-up Task Allocation Approach in Social Sensing based Edge Computing Systems
Authors: Daniel (Yue) Zhang and Dong Wang.
Published In: IEEE International Conference on Computer Communications (INFOCOM), 2019.
[BigData '18] FauxBuster: A Content-free Fauxtography Detector Using Social Media Comments
Authors: Daniel (Yue) Zhang, Lanyu Shang, Biao Geng, Shuyue Lai, Ke Li, Hongmin Zhu, Md Tanvir Amin and Dong Wang.
Published In: IEEE International Conference on Big Data (BigData), 2018.(Acceptance rate: 18.9%)
[BigData '18] StreamGuard: A Bayesian Network Approach to Copyright Infringement Detection Problem in Large-scale Live Video Sharing Systems
Authors: Daniel (Yue) Zhang, Lixing Song, Qi Li, Yang Zhang and Dong Wang.
Published In: IEEE International Conference on Big Data (BigData), 2018.(Acceptance rate: 18.9%)
[SEC '18] Cooperative-Competitive Task Allocation in Edge Computing for Delay-Sensitive Social Sensing
Authors: Daniel (Yue) Zhang, Yue Ma, Chao Zheng, Yang Zhang, X. Sharon Hu and Dong Wang.
Published In: Third ACM/IEEE Symposium on Edge Computing (SEC), 2018.
[ICDCS '17] Towards Scalable and Dynamic Social Sensing Using A Distributed Computing Framework
Authors: Daniel (Yue) Zhang, Chao Zheng, Dong Wang, Doug Thain, Chao Huang, Xin Mu and Greg Madey.
Published In: IEEE International Conference on Distributed Computing Systems (ICDCS), 2017. (Acceptance rate: 16.9%)

Yue (Daniel) Zhang | 张越

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