I am a senior researcher at the eXascale Infolab, University of Fribourg. I obtained my PhD in 2017 from Delft University of Technology, Netherlands, where I worked in the Web Information Systems group. Prior to that, I completed my master program (with cum laude) in Eindhoven University of Technology, Netherlands, in 2013. Before, I received my bachelor degree from Zhejiang University, China, in 2011. During my study, I worked as a research intern in Philips Research, Eindhoven, Netherlands, and as a machine learning scientist in Amazon, Seattle, US.

My research focuses on building effective Human-AI Loop Systems that combine human and machine intelligence to solve complex tasks at scale. The topic lies at the intersection of human computation, machine learning, recommendation, and user modeling. My work finds its natural application in human computation, recommendation, question answering, and urban computing systems.

• 01/19 - Three full papers accepted at WWW'19. Two on human & machine intelligence for debugging nosiy training sets and knowledge graph construction, respectively, and one on recommendation in LBSNs.
• 07/18 - I start to serve on the editorial board of the journal of Human Computation, and will serve on the program committee of AAAI ICWSM'19, ACM CHIIR'19, and ACM IUI'19.
• 07/18 - Full paper "Recurrent Knowledge Graph Embedding for Effective Recommendation" accepted at ACM RecSys'18.
• 03/18 - Full paper "How do Crowdworker Communities and Microtask Markets Influence Each Other? A Data-Driven Study on Amazon Mechanical Turk" accepted at AAAI HCOMP'18.
• 03/18 - Full paper "Social Gamification in Enterprise Crowdsourcing" accepted at ACM WebSci'18.
• 03/18 - Dataset paper "LearningQ: A Large-scale Dataset for Educational Question Generation" accepted at AAAI ICWSM'18.
• 12/17 - Full paper "Leveraging Crowdsourcing Data for Deep Active Learning - An Application: Learning Intents in Alexa" accepted at WWW'18.
• 11/17 - I defended my PhD thesis titled "Crowd Knowledge Creation Acceleration". Committee members: Philippe Cudré-Mauroux, Wolfgang Nejdl, Lora Aroyo, Alan Hanjalic, and my advisors Alessandro Bozzon and Geert-Jan Houben. Check the news on our department website.
• 10/17 - I interned as a Scientist at the Alexa Shopping Machine Learning team in Amazon, Seattle, on Deep Active Learning from Crowds.
• 09/17 - I was invited to serve on the Program Committee of WWW'18, AAAI ICWSM'18, ACM IUI'18, and ACM SAC'18. In addition, I am the Web master for ACM UMAP'18; check out the website!
• 08/17 - We organized the workshop Recommender Systems for Citizens (CitRec) at ACM RecSys'17. Find the proceedings here.
• 08/17 - Full paper "Interacting Attention-Gated Recurrent Networks for Recommendation" accepted at ACM CIKM'17.
• 07/17 - Our paper "Clarity is a Worthwhile Quality - On the Role of Task Clarity in Microtask Crowdsourcing" won the Douglas Engelbart Best Paper Award in ACM HT'17!
• 04/17 - Full paper "MRLR: Multi-level Representation Learning for Personalized Ranking in Recommendation" accepted at IJCAI'17.
• 03/17 - I gave 3 lectures in TU Delft Msc course Information Retrieval.
• 11/16 - Full paper "Exploiting both Vertical and Horizontal Dimensions of Feature Hierarchy for Effective Recommendation" accepted at AAAI'17.
• 09/16 - I visited MIT the Senseable City Lab.
• 07/16 - Full paper "Modeling Task Complexity in Crowdsourcing" accepted at AAAI HCOMP'16.
• 06/16 - Full paper "Learning Hierarchical Feature Influence for Recommendation by Recursive Regularization" accepted at ACM RecSys'16.
• 05/16 - Our position paper "On the Improvement of Quality and Reliability of Trust Cues in Micro-task Crowdsourcing" in TRUSTINCW @ACM WebSci'16 won the Best Paper Award!

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