Dong Wang

Dong Wang

Associate Professor

PhD, Computer Science, Illinois

Other professional appointments

Faculty Affiliate, Illinois Informatics

Research focus

Social (Human-centric) sensing, computing and intelligence; human-centered AI; big data analytics; reliable information distillation systems; human-cyber-physical systems; edge computing; Internet of Things/Everything (IoT/IoE); and smart cities.

Honors and Awards

  • 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)

Biography

Joining the iSchool in August 2021

Dong Wang is currently 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.

Publications & Papers

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%)

Yang Zhang, Ruohan Zong, Dong Wang. A Hybrid Transfer Learning Approach to Migratable Disaster Assessment in Social Media Sensing, The IEEE/ACM International Conference on Social Networks Analysis and Mining (ASONAM 2020), Full Paper, Virtual Conference, December, 2020. (Acceptance rate: 17.8%)

Daniel Zhang, Yu Ma, Sharon Hu, Dong Wang . Towards Privacy-aware Task Allocation in Social Sensing based Edge Computing Systems, IEEE Internet of Things Journal, 7.12 (2020): 11384-11400.

Md Tahmid Rashid, Daniel Zhang, Dong Wang. SocialDrone: An Integrated Social Media and Drone Sensing System for Reliable Disaster Response, IEEE International Conference on Computer Communications (IEEE INFOCOM 2020), Full Paper, Virtual Conference, 2020. (Acceptance rate: 19.8%)

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, Tanvir Amin, Tarek Abdelzaher, Lance Kaplan, et al. Using Humans as Sensors: An Estimation-theoretic Perspective. The 13th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN'14), Berlin, Germany, April 2014. (Acceptance rate: 20%)

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%)

Presentations

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

Assured Information Distillation in Social Sensing, Invited Talk at University of Notre Dame, IN, 2014