Yang Zhang, Ph.D.

About Me

Hello, this is Yang Zhang! I am a Teaching Assistant Professor and AI researcher at the School of Information Sciences (iSchool) at the University of Illinois Urbana-Champaign (UIUC). I am also affiliated with the Gradudate College, the Illinois Informatics Institute, and the Social Sensing & Intelligence Lab at UIUC. Previously, I worked as a W.J. Cody Research Associate at Argonne National Laboratory. I received my Ph.D. in Computer Science from the University of Notre Dame, advised by Dr. Dong Wang, an M.S. in Data Science from Indiana University Bloomington, and a B.E. in Software Engineering from Wuhan University.

Research Interests

Human-AI/LLM Collaboration

• Human-AI alignment and collaboration in generative models
• Collaborative neural architecture and hyperparameter searh with human-AI interaction
• Development of Co-Learning Frameworks for Integrating Human Intelligence with AI/LLM

AI/Deep Learning Modeling Challenges

• Addressing data sparsity in AI models and enhancing learning from limited data
• Tackling information multimodality for more comprehensive AI understanding
• Ensuring the trustworthiness and universality of AI models across diverse applications

Human-Centered AI Applications

• Disaster informatics and using AI for effective response and management
• Detection and mitigation of public health misinformation through AI
• AI-driven drug discovery for accelerating therapeutic development
• Enhancing intelligence in infrastructure inspection through AI-driven approaches

Awards and Honors

• [2023, 2024] Teachers Ranked as Excellent, University of Illinois
• [2022] Best Paper Award, ACM/IEEE ASONAM
• [2022] Best Paper Honorable Mention, IEEE SMARTCOMP
• [2021] Outstanding Graduate Research Assistant Award, University of Notre Dame
• [2021] Video Presentation Award, ACM/IEEE IWQoS
• [2020] W. J. Cody Associate Award, Argonne National Laboratory
• [2018, 2019] Conference Travel Award, IEEE
• [2015] Data Science Scholar Fellowship, Indiana Unviersity
• [2010, 2011] First Class Scholarship, Wuhan Unviersity

Recent Publications

For a comprehensive list of my scholarly contributions, please visit my Google Scholar profile.

[WWW] Y. Zhang, R. Zong, L. Shang, H. Zeng, Z. Yue, D. Wang. SymLearn: A Symbiotic Crowd-AI Collective Learning Framework to Web-based Healthcare Policy Adherence Assessment. International World Wide Web Conference, Austin, Texas, 2024.

[WWW] L. Shang, Y. Zhang, B. Chen, R. Zong, Z. Yue, H. Zeng, B. Wei, D. Wang. MMAdapt: A Knowledge-guided Multi-source Multi-class Domain Adaptive Framework for Early Health Misinformation Detection. International World Wide Web Conference, Austin, Texas, 2024.

[ICDCS] H. Zeng, Z. Yue, Q. Jiang, Y. Zhang, L. Shang, R. Zong, D. Wang. Mitigating Demographic Bias of Federated Learning Models via Robust-Fair Domain Smoothing: A Domain-Shifting Approach. IEEE International Conference on Distributed Computing Systems, Jersey City, New Jersey, 2024.

[NAACL-HLT] Z. Yue, H. Zeng, Y. Lu, L. Shang, Y. Zhang, D. Wang. Evidence-Driven Retrieval Augmented Response Generation for Online Misinformation. 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies, Mexico City, Mexico, 2024.

[ICWSM] L. Shang, B. Cheng, A. Vora, Y. Zhang, Z. Yue, X. Cai, D. Wang. A Social and News Media Driven Dataset and Analytical Platform Towards Understanding Societal Impact of Drought. International AAAI Conference on Web and Social Media, Buffalo, New York, 2024.

[ICWSM] L. Shang, Y. Zhang, Z. Yue, J. Choi, H. Zeng, D. Wang. Domain Adaptive Graph Learning Framework to Early Detection of Emergent Healthcare Misinformation on Social Media. International AAAI Conference on Web and Social Media, Buffalo, New York, 2024.

[SECON] Y. Zhang, R. Zong, L. Shang, H. Zeng, Z. Yue, and D. Wang. A Symbiotic Human-AI Co-Learning Framework for Healthcare Policy Adherence Assessment in Social Sensing. IEEE International Conference on Sensing, Communication and Networking, Madrid, Spain, 2023.

[IJCAI] Y. Zhang, R. Zong, L. Shang, H. Zeng, Z. Yue, and D. Wang. On Optimizing Model Generality in AI-based Disaster Damage Assessment: A Subjective Logic-driven Crowd-AI Hybrid Learning Approach. International Joint Conference on Artificial Intelligence, Macao, SAR, 2023.

[WWW] Y. Zhang, L. Shang, R. Zong, H. Zeng, Z. Yue, and D. Wang. CollabEquality: A Crowd-AI Collaborative Learning Framework to Address Class-wise Inequality in Web-based Disaster Response. International World Wide Web Conference, Austin, Texas, 2023.

[AAAI] Y. Zhang, Z. Kou, L. Shang, H. Zhen, Z. Yue, and D. Wang. A Crowd-AI Duo Relational Graph Learning Framework Towards Social Impact Aware Photo Classification. Thirty-Seven AAAI Conference on Artificial Intelligence, Washington, DC, 2023.

[WWW] R. Zong, Y. Zhang, L. Shang, and D. Wang. ContrastFaux: Sparse Semi-supervised Fauxtography Detection on the Web using Multi-view Contrastive Learning. International World Wide Web Conference, Austin, Texas, 2023.

[HCOMP] R. Zong, Y. Zhang, F. Stinar, L. Shang, H. Zeng, N. Bosch, and D. Wang. A Crowd-AI Collaborative Approach to Address Demographic Bias for Student Performance Prediction in Online Education. AAAI Conference on Human Computation and Crowdsourcing, Delft, Netherlands, 2023.

[IJCAI] H. Zeng, Z. Yue, L. Shang, Y. Zhang, and D. Wang. Adversarial Robustness of Demographic Fairness in Face Attribute Recognition. International Joint Conference on Artificial Intelligence, Macao, SAR, 2023.

[CIKM] H. Zeng, Z. Yue, Y. Zhang, L. Shang, and D. Wang. Manipulating Out-Domain Uncertainty Estimation in Deep Neural Networks via Targeted Clean-Label Poisoning. ACM International Conference on Information and Knowledge Management, Birmingham, UK, 2023.

[ACL] Z. Yue, H. Zeng, Y. Zhang, L. Shang, and D. Wang. MetaAdapt: Domain Adaptive Few-Shot Misinformation Detection via Similarity-Based Meta Learning. Annual Meeting of the Association for Computational Linguistics, Toronto, Canada, 2023.

[CSCW] Y. Zhang, R. Zong, L. Shang, Z. Kou, and D. Wang. CrowdNAS: A Crowd-guided Neural Architecture Searching Approach to Disaster Damage Assessment. ACM Conference on Computer-Supported Cooperative Work and Social Computing, Virtual Conference, 2022.

[CSCW] Y. Zhang, R. Zong, L. Shang, Z. Kou, H. Zeng, and D. Wang. CrowdOptim: A Crowd-driven Neural Network Hyperparameter Optimization Approach to AI-based Smart Urban Sensing. ACM Conference on Computer-Supported Cooperative Work and Social Computing, Virtual Conference, 2022.

[CSCW] Z. Kou, Y. Zhang, D. Y. Zhang, and D. Wang. CrowdGraph: A Crowdsourcing Multi-modal Knowledge Graph Approach to Explainable Fauxtography Detection. ACM Conference on Computer-Supported Cooperative Work and Social Computing, Virtual Conference, 2022.

Teaching

Fall 2024 (In Progress)

• IS 455 Database Design and Prototyping

Spring 2024 (Teachers Ranked as Excellent)

• IS 455 Database Design and Prototyping
• IS 327 Concepts of Machine Learning

Fall 2023 (Teachers Ranked as Excellent)

• IS 455 Database Design and Prototyping
• IS 206 Introduction to Database Concepts and Applications

Spring 2023 (Teachers Ranked as Excellent)

• IS 455 Database Design and Prototyping

Services

Conference Reviewers

• ACL Rolling Review
• ACM Collective Intelligence Conference
• IEEE/ACM International Conference on Advances in Social Network Analysis and Mining
• International Joint Conference on Artificial Intelligence
• AAAI Conference on Artificial Intelligence
• ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
• IEEE International Conference on Cluster Computing
• IEEE International Conference on Distributed Computing in Sensor Systems
• ACM/IEEE International Conference on Internet of Things Design and Implementation
• IEEE International Conference on Computer Communications and Networks

Journal Reviewers

• IEEE Transactions on Big Data
• Elsevier Information Processing and Management
• Elsevier Computers & Industrial Engineering
• Frontiers in Big Data
• Elsevier Computer Networks
• Elsevier Knowledge-Based Systems
• IEEE Transactions on Mobile Computing
• Springer Neural Computing and Applications
• Elsevier Computers, Environment and Urban Systems
• Springer International Journal of Data Science and Analytics

Other Services

• Action Editor/Area Chair, ACL Rolling Review (ARR)
• Editorial Board, Frontiers in Big Data
• Session Chair, IEEE Cluster 2021

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