About me

Qilian Yu

Recent Update: 01/30/2018

I am an engineer by weekday, a photographer by weekend. My solo exhibit was held at Davis Art Center from 11/03-11/15. 


Since I first touched the engineering filed in my high school, I have matured into an engineer, who can not only use methods offered in school but also acquire new techniques to solve real-world problems. Several issued patents explain my ambition that I am eager to absorb any innovative pieces of stuff and make use of them. I received my bachelor degree in Electrical Engineering from Zhejiang University, China, in 2014. At the beginning, I worked on wireless communication, information theory and coding theory. After I came to the USA, my focus was shifted to:   
Besides, I am also a photographer. I started my photography journey when I was still a high school kid, and so far I have spent near 10 years in photography. Like I am strongly aggressive in Engineering, I like to try everything new in photography techniques. I am not scared by the rainstorm or tsunami since I can show the thing others have never seen before and I can image how surprised viewers are when they see my works. The only thing I want to show you is how beautiful the world is. 

Educational Details

  • Ph.D. in Electrical Engineering, College of Engineering, University of California - Davis. (GPA - 3.9/4.0)
    1. Deep Learning, Reinforcement Learning, Artificial Intelligence, Scalable Machine Learning, Game Theory, Theory of Computation, Fuzzy System & Set Theory, Data Structures & Prog, Software & Obj-Orient Prog, System Theory, Linear Network, Optimization, Distribution Theory, Convex Optimization, Information Theory, Stochastic System, Graph Theory, Data Science of Communication Network, Data Mining and Analysis, Theory of Inference.
  • Online Certificates: Big Data Analysis with Scala and Spark (Cloudera), Machine Learning (Cloudera), Introduction to Hadoop and MapReduce (Udacity), Data Analysis (Udacity), Data Analysis and R (Udacity), A/B Testing (Udacity), Swift Programming Syntax (Udacity), Relational Databases (Udacity), Machine Learning (Udacity), Reinforcement Learning (Udacity)
  • Bachelor of Engineering (B.E) in Electrical Engineering, College of Information Science & Electronic EngineeringZhejiang University, China, GPA - 3.6/4.0)

Professional Experience

1. Intern Data Scientist at TalkingData (Beijing Tendcloud Tianxia Technology Co., Ltd), China (Summer 2017)
3. Session Chair for Emerging Technologies, Architectures and Services, WCNC 2017 (March 2017)
4. Research Assistant at University of California, Davis, USA (2016-now)
5. Teaching Assistant at University of California, Davis, USA (2017)
6. Research Assistant at Texas A&M University, USA (2014-2016)
7. Research Assistant at Zhejiang University, China (2013-2014)
8. Hardware Engineer Intern at Fujian Star-Net Communication Company, China (2012)


1. Community Detection in Attributed Heterogeneous Information Networks
    Keywords: Semi-supervised Learning, Community Detection, Clustering, Heterogeneous Networks
2. Network Formulation based on Deep Neural Network Proactive Learning over Large Graphs
    Keywords: Network Formation, Deep Neural Network, Proactive Learning, Learning over Graph, Big Data
3. Multi-Action Credit Distribution based Single-Pass Influence Maximization in Social Networks
    Keywords: Social Network, Big Data, Influence Maximization, Streaming Algorithm, Submodularity 
4. Feature Selection with Interactions in Logistic Regression Models using Multivariate Synergies for GWAS
    Keywords: Feature Selection, Genome-wide Association Study, Mutual Information
5. d-Knapsack Submodular Maximization and its Applications in Scientific Literature Recommendations
    Keywords: Submodular Optimization, Streaming Algorithm, Scientific Literature Recommendation
6. Submodular Streaming in Real-time News Recommendation 
    Keywords: Online Learning, Active Learning, Recommendation, Submodularity, Streaming Algorithm


1. Low-delay Progressive Decoding Method of Rateless Code (CN 20141035606)
2. Data Segmenting and Packaging Method for Physical Layer Rateless Code Transmission (CN 20141035980)
3. Stop-wait Method for Physical Layer Rateless Code Transmission (CN 201410135143)
4. Adaptive Pipeline Method for Physical Layer Rateless Code Transmission (CN 201410136267)
5. Pipeline Method for Physical Layer Rateless Code Transmission (CN 201410135621)
6. Information Sharing System based on Bar Code Identification (CN 202677457)
7. Learning Assistant based on Wireless Networking and Radio Frequency Identification (CN 201220430153)
8. Schoolbag Intelligent Management Device (CN 200720008541)


1. L. Zhang, Z. Zhang, X. Wang, Q. Yu, and Y. Chen, “On the puncturing patterns for punctured polar codes,” in 2014 IEEE International Symposium on Information Theory (ISIT),. IEEE, 2014, pp. 121–125. 
2. Q. Yu, E. L. Xu, and S. Cui, "Submodular maximization with multi-knapsack constraints and its applications in scientific literature recommendations," in 2016 IEEE Global Conference on Signal and Information Processing(GlobalSIP),. IEEE, Dec. 2016, pp. 1295-1299. 
3. E. L. Xu, X. Qian, Q. Yu, H. Zhang, and S. Cui, "Feature Selection with Interactions in Logistic Regression Models using Multivariate Synergies for a GWAS Application,"  In Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, pp. 760-761. ACM, 2017.
4. Q. Yu, H. Li, Y. Liao, and S. Cui, "Multi-Action Credit Distribution based Single-Pass Influence Maximization in Social Networks," submitted to ICASSP 2018 (accepted). 
5. Q. Yu, H. Li, Y. Liao, and S. Cui, "Fast Budgeted Influence Maximization over Multi-Action Event Log," submitted to IEEE Access (accepted).
6. Q. Yu, E. L. Xu, and S. Cui, "Streaming Algorithms for News and Scientific Literature Recommendation: Submodular Maximization with a d-Knapsack Constraint," submitted to TKDE.