Howdy! I am a second-year Ph.D. student in the Computer Science & Engineering Department at Texas A&M University, advised by Prof. James Caverlee. I'm broadly interested in the area of data mining, machine learning and recommender systems. Specifically, my research focuses on fairness issues in recommender systems and neural network techniques for recommendation.

I obtained my Bachelor's degree from Wuhan University in China before coming to TAMU.

Publications

• Fairness-Aware Tensor-Based Recommendation. (acceptance rate: 17%) [pdf]
  The 27th ACM International Conference on Information and Knowledge Management (CIKM), 2018.
  Ziwei Zhu, Xia Hu, and James Caverlee.


• Fairness-Aware Recommendation of Information Curators [pdf]
  The 2nd FATREC Workshop on Responsible Recommendation at RecSys, 2018.
  Ziwei Zhu, Jianling Wang, Yin Zhang, and James Caverlee.


• Pseudo-Implicit Feedback for Alleviating Data Sparsity in Top-K Recommendation (short paper). (acceptance rate: 20%) [pdf]
  The 2018 IEEE International Conference on Data Mining (ICDM), 2018.
  Yun He, Haochen Chen, Ziwei Zhu, and James Caverlee.


• Modeling and Detecting Student Attention and Interest Level Using Wearable Computers. [pdf]
  IEEE International Conference on Wearable and Implantable Body Sensor Networks (BSN), 2017.
  Ziwei Zhu, Sebastian Ober, Roozbeh Jafari.

Industry Experience

• Software engineering intern, Analysys, Beijing, China, Jun 2015 - Aug 2015.

Teaching

• Teaching Assistant: CSCE 206 Structured Programming in C, TAMU, Fall, 2017

Technical Talks

• Fairness-Aware Tensor-Based Recommendation. CIKM, Turin, Italy, 2018.

Professional Services

• Journal Reviewer: Transactions on Knowledge and Data Engineering, IEEE Intelligent Systems, Information Retrieval Journal
• Conference Reviewer:
• External Reviewer:

Selected Awards

• National Scholarship in 2013
• Top Level Scholarship for Excellent Student in 2014