Faculty Profile

Jing Yuan

Title
Assistant Professor
Department
Computer Science and Engineering
College
College of Engineering

    

    

      


                          

            
Curriculum Vitae

            

              Click Here to View Faculty CV
            

          

        
                          

            
Education

            



  

  


  
PhD, University of Texas at Dallas, 2018. 
Major: Computer Science





          

        
                

          
Current Scheduled Teaching*


          
CSCE 6940.962, Individual Research, Spring 2024 
CSCE 5215.005, Machine Learning, Spring 2024 


          
*
  Texas Education Code 51.974 (HB 2504) requires each institution of
  higher education to make available to the public, a syllabus for
  undergraduate lecture courses offered for credit by the institution.
  

        

      

    

  


    

    

      


        


          


            
Previous Scheduled Teaching*


            
                    

                    CSCE 6940.863, Individual Research, Fall 2023 
                    

                    CSCE 5215.002, Machine Learning, Fall 2023 Syllabus SPOT
                    

                    CSCE 5215.005, Machine Learning, Spring 2023 Syllabus SPOT
                    

                    CSCE 5900.863, Special Problems, Spring 2023 
                    

                    CSCE 5215.004, Machine Learning, Fall 2022 Syllabus SPOT

          


          
*
  Texas Education Code 51.974 (HB 2504) requires each institution of
  higher education to make available to the public, a syllabus for
  undergraduate lecture courses offered for credit by the institution.
  

        

      

    

  

  
  	

	

	  

		

		   
Published Publications



  

  
Published Intellectual Contributions


  
Book Chapter
Yuan, J., Wu, W., Varanasi, S.  (2018). Approximation and Heuristics for Community Detection. Handbook of Approximation Algorithms and Metaheuristics, Second Edition: Contemporary and Emerging Applications, Volume 2, Chapter 37. 
Yuan, J., Wu, W., Xu, W.  (2018). Approximation for Influence Maximization. Handbook of Approximation Algorithms and Metaheuristics, Second Edition: Contemporary and Emerging Applications, Volume 2, Chapter 36. 
Li, C., Yuan, J., Du, D.  (2018). Social Influence-Based Optimization Problems. Open Problems in Optimization and Data Analysis, Chapter 2. 
Conference Proceeding
Yuan, J., Tang, S.  (2023). Approximating Decision Trees with Priority Hypotheses. The 29th International Computing and Combinatorics Conference, COCOON 2023. 
Tang, S., Yuan, J., Mensah-Boateng, T.  (2023). Achieving Long-term Fairness in Submodular Maximization through Randomization. The 19th Cologne-Twente Workshop on Graphs and Combinatorial Optimization, CTW 2023. 
Yuan, J., Tang, S.  (2023). Worst-Case Adaptive Submodular Cover. The 22nd International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2023. 
Tang, S., Yuan, J.  (2022). Optimal Sampling Gaps for Adaptive Submodular Maximization. The 36th AAAI Conference on Artificial Intelligence, AAAI 2022. 
Tang, S., Yuan, J.  (2022). Streaming Adaptive Submodular Maximization. The 16th International Conference on Algorithmic Aspects in Information and Management. 
Tang, S., Yuan, J.  (2021). Adaptive Cascade Submodular Maximization. The 20th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2021. 
Tang, S., Yuan, J.  (2020). Adaptive Robust Submodular Optimization and Beyond. The 14th International Conference on Algorithmic Aspects in Information and Management, AAIM 2020. 
Tang, S., Yuan, J., Mookerjee, V.  (2020). Optimizing Ad Allocation in Mobile Advertising. The 21st ACM International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, ACM Mobihoc 2020. 
Yuan, J., Wu, W., Li, Y., Du, D.  (2017). Active Friending in Online Social Networks. The 4th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, IEEE/ACM BDCAT 2017. 
Yuan, J., Tang, S.  (2017). Adaptive Discount Allocation in Social Networks. The 18th ACM International Symposium on Mobile Ad Hoc Networking and Computing, ACM Mobihoc 2017. 
Tang, S., Zhou, Y., Han, K., Zhang, Z., Yuan, J., Wu, W.  (2017). Networked Stochastic Multi-armed Bandits with Combinatorial Strategies. The 37th IEEE International Conference on Distributed Computing Systems, IEEE ICDCS 2017. 
Yuan, J., Tang, S.  (2017). No Time to Observe: Adaptive Influence Maximization with Partial Feedback. The 26th International Joint Conference on Artificial Intelligence, IJCAI 2017. 
Tang, S., Yuan, J.  (2016). Optimizing Ad Allocation in Social Advertising. The 25th ACM International Conference on Information and Knowledge Management, ACM CIKM 2016. 
Journal Article
Tang, S., Yuan, J.  (2023). Group Equality in Adaptive Submodular Maximization. INFORMS Journal on Computing. INFORMS. 
Tang, S., Yuan, J.  (2023). Partial-Adaptive Submodular Maximization. Lecture Notes in Computer Science. 13889, . Springer. 
Yuan, J., Tang, S.  (2023). Group fairness in non-monotone submodular maximization. Journal of Combinatorial Optimization. 45(3), 88. Springer. 
Tang, S., Yuan, J.  (2023). Streaming Adaptive Submodular Maximization. Theoretical Computer Science. 944, 113644. Elsevier. 
Tang, S., Yuan, J.  (2022). Assortment Optimization with Repeated Exposures and Product-dependent Patience Cost. Operations Research Letters. 50(1), 8-15. 
Tang, S., Yuan, J.  (2022). Partial-monotone adaptive submodular maximization. Journal of Combinatorial Optimization. 45(1), 35. Springer. 
Yang, W., Ma, J., Li, Y., Yan, R., Yuan, J., Wu, W., Li, D.  (2019). Marginal Gains to Maximize Content Spread in Social Networks. 6(3), 479-490. IEEE Transactions on Computational Social Systems. 
Yang, W., Yuan, J., Wu, W., Ma, J., Du, D.  (2019). Maximizing Activity Profit in Social Networks. 6(1), 117-126. IEEE Transactions on Computational Social Systems. 
Zhang, Z., Wu, W., Yuan, J., Du, D.  (2018). Breach-free Sleep-Wakeup Scheduling for Barrier Coverage with Heterogeneous Wireless Sensors. 26(5), 2404-2413. IEEE/ACM Transactions on Networking. 
Zhu, J., Zhu, J., Ghosh, S., Wu, W., Yuan, J.  (2018). Social Influence Maximization in Hypergraph in Social Networks. 6(4), 801-811. IEEE Transactions on Network Science and Engineering. 
Tu, J., Wu, L., Yuan, J., Cui, L.  (2017). On the Vertex Cover P3 Problem Parameterized by Treewidth. 34(2), 414-425. Journal of Combinatorial Optimization. 
Yuan, J., He, L., Dragut, E., Meng, W., Yu, C.  (2017). Result Merging for Structured Queries on the Deep Web with Active Relevance Weight Estimation. 64, 93-103. Information Systems. 



	
		
		
	  

	

	

  
    
	

	

	  

		

		   
Awarded Grants



  
  
  	  
          
Contracts, Grants and Sponsored Research  

 	 
	 	 
  
Grant - Research   
Yuan, J. (Principal), Wang, J. (Co-Principal), "Fundamental Trade-offs and Algorithms in Fairness-aware Adaptive Learning Systems," Sponsored by CAHSI-Google, National, $80000 Funded. (September 1, 2023 – August 31, 2024).
Yuan, J. (Principal), "Conference Travel Support Award," Sponsored by UNT, University of North Texas, $1000 Funded. (June 2024 – June 2024).



	
		
		
	  

	

	

	
	

  
  
  

  	

		

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					Overall
Summative Rating		
					Challenge and
Engagement Index		
					Response Rate
					
				

			
			
				

					
					
out of 5		
					
out of 7		
					%
 of 
students responded		
					
					
				

			
		


		
    
			
  • Overall Summative Rating (median):
    
			This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
				
      
					
    • The course as a whole was
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    • The course content was
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    • The instructor’s contribution to the course was
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    • The instructor’s effectiveness in teaching the subject matter was
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  • Challenge and Engagement Index:
    
			This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
				
      
					
    • Do you expect your grade in this course to be
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    • The intellectual challenge presented was
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    • The amount of effort you put into this course was
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    • The amount of effort to succeed in this course was
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    • Your involvement in course (doing assignments, attending classes, etc.) was
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