Dong Wang

Faculty Affiliate, National Center for Supercomputing Applications (NCSA)
Faculty Affiliate, Information Trust Institute
Faculty Affiliate, Illinois Informatics
Faculty Affiliate, Center for Social and Behavioral Science (CSBS)

• Best Paper Award, 2022 ACM/IEEE International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
• Best Paper Honorable Mention, 8th IEEE International Conference on Smart Computing (SMARTCOMP)
• NSF CAREER Award 
• Google Faculty Research Award 
• ARO Young Investigator Program Award (YIP)
• NSF CISE Research Initiation Initiative (CRII) Award 
• Wing Kai Cheng Fellowship, University of Illinois
• Best Paper Award, 16th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS)

Dong Wang joined the School of Information Sciences at the University of Illinois as an associate professor in August 2021. He previously served as an associate professor in the Computer Science and Engineering Department at the University of Notre Dame. His honors include the NSF CAREER Award, Google Faculty Research Award, Young Investigator Program (YIP) Award from the US Army Research Office, NSF CRII Award, Wing Kai Cheng Fellowship from the University of Illinois, and the Best Paper Award of IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS).

Wang’s work has been applied in a wide range of real-world applications such as misinformation detection, social network analysis, crowd-based disaster response, intelligent transportation, urban planning, and environment monitoring. He has published over 100 technical papers in peer reviewed conferences and journals. His research on social sensing, intelligence and computing resulted in software tools that found applications in academia, industry, and government research labs. He authored a monograph, "Social Sensing: Building Reliable Systems on Unreliable Data," which was published by Elsevier in 2015. Wang holds a PhD in computer science from the University of Illinois at Urbana Champaign.

• Spring 2023 - Independent Study - IS389DW
• Spring 2023 - Computer Networks - IS496CN3
• Spring 2023 - Computer Networks - IS496CN4

By appointment, please contact professor.

Zhenrui Yue, Huimin Zeng, Ziyi Kou, Lanyu Shang, Dong Wang. Contrastive Domain Adaptation for Early Misinformation Detection: A Case Study on COVID-19, 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), Full Paper, Georgia USA, October, 2022.
 
Md Tahmid Rashid, Dong Wang. CovidTrak: A Vision on Social Intelligence-Empowered COVID-19 Contact Tracing, IEEE Transactions on Computational Social Systems (TCSS), in press, 2022.
 
Huimin Zeng, Zhenrui Yue, Yang Zhang, Ziyi Kou, Lanyu Shang, Dong Wang. On Attacking Out-Domain Uncertainty Estimation in Deep Neural Networks, the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI 2022), Full Paper, Messe Wien, Vienna, Austria, July, 2022. (Acceptance rate: 15%)
 
Lanyu Shang, Yang Zhang, Quanhui Ye, Na Wei, Dong Wang. SmartWaterSens: A Crowdsensing-based Approach to Groundwater Contamination Estimation, IEEE International Conference on Smart Computing (SMARTCOMP 22), Full Paper, Espoo, Finland, June, 2022. (Best Paper Honorable Mention)
 
Daniel Zhang, Ziyi Kou, Dong Wang. FedSens: A Federated Learning Approach for Smart Health Sensing with Class Imbalance in Resource Constrained Edge Computing, IEEE International Conference on Computer Communications (IEEE INFOCOM 2021), Full Paper, Virtual Conference, May, 2021. (Acceptance rate: 19.9%)
 
Dong Wang, Boleslaw K. Szymanski, Tarek Abdelzaher, Heng Ji, Lance Kaplan. The Age of Social Sensing, IEEE Computer, 52, no. 1 (2019): 36-45.
 
Daniel Zhang, Yang Zhang, Qi Li, Thomas Plummer, Dong Wang. CrowdLearn: A Crowd-AI Hybrid System for Deep Learning-based Damage Assessment Applications, The 39th IEEE International Conference on Distributed Computing (ICDCS 2019), Full Paper, Dallas, Texas, 2019. (Acceptance rate: 19.6%)
 
Daniel Zhang, Lanyu Shang, Biao Geng, Shuyue Lai, Ke Li, Hongmin Zhu, Md Tanvir Amin, Dong Wang. FauxBuster: A Content-free Fauxtography Detector Using Social Media Comments, 2018 IEEE International Conference on Big Data (IEEE BigData 2018), Full Paper, Seattle, December, 2018. (Acceptance rate: 18.9%)
 
Dong Wang, Tarek Abdelzaher, and Lance Kaplan. Social Sensing: Building Reliable Systems on Unreliable Data. 1st Edition. Elsevier, 2015.
 
Dong Wang, Lance Kaplan, Hieu Le and Tarek Abdelzaher. On Truth Discovery in Social Sensing: A Maximum Likelihood Estimation Approach. The 11th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN'12), Beijing, China April 2012. (Acceptance rate: 15%)

Dong Wang, Vision of Social Informatics: the Perspectives from Social (Human-centric) Sensing and Intelligence, invited talk at National Research Council of Italy, July, 2022. 

Dong Wang, Addressing Data Heterogeneity and Sparsity in Human-centric Smart City Applications, invited panel talk at 8th International Conference on Networking, Systems and Security (NSysS 2021), Virtual, December, 2021.

Dong Wang, Misinformation Detection and Explanation by Exploring the Power of Social Intelligence, Center for Social and Behavioral Science, University of Illinois at Urbana- Champaign, Urbana, November, 2021.

The Era of Human-centric Sensing, Computing and Intelligence, Invited Talk at Case Western Reserve University, Cleveland, Ohio, 2020

Harnessing the Power of Crowd for Human-centric Computing Systems, Invited Talk at the University of Illinois, 2020

Social Sensing based Edge Computing Systems, Invited Talk at University of Washington, Seattle, 2018

Towards Scalable and Responsive Social Sensing, Invited Talk at University of North Carolina at Chapel Hill, 2018

Building Reliable Cyber-Physical Systems with Human-in-the-loop, Invited Talk at Indiana University, Bloomington, Indiana, 2017

Big Data in Cyber-Physical Systems, Invited Talk at University of Pittsburgh, Pittsburgh, PA, 2015

Data Reliability Challenge of Future Cyber-Physical Systems for Smart Cities, NSF Early Career Investigators Workshop on CPS and Smart City, Seattle, WA, 2015