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Jin Huang
Biography
I am a postdoctoral researcher at University of Amsterdam (UvA), Amsterdam UMC, and Delft University of Technology, working on Trustworthy AI systems. I got my Ph.D. degree from University of Amsterdam (UvA), supervised by Prof. dr. Maarten de Rijke , Dr. Herke van Hoof, and Dr. Harrie Oosterhuis. Prior to that, I received my BE and ME degree in computer science from Renmin University of China under the supervision of Prof. dr. Xin Zhao and Prof. dr. Ji-Rong Wen in 2016 and 2019, respectively.
My research interest focuses on trustworthy advice-giving systems for real-world applications, especially in high-risk domains, e.g., healthcare, news recommendation, and public services.
I successfully defended my Ph.D. thesis titled Learning Recommender Systems from Biased User Interactions on 7th Feb 2024. I am looking for positions to continue my career.
Download my resumé.
Interests
- Trustworthy AI
- Advice-giving systems
- Large language models
- Reinforcement learning
Education
-
PhD in Computer Science, 2019 ~ 2024
University of Amsterdam
-
MEng in Computer Science, 2016 ~ 2019
Renmin University of China
-
BSc in Computer Science, 2012 ~ 2016
Renmin University of China
Publications
Yuyue Zhao,
Jin Huang,
David Vos,
Maarten de Rijke
(2024).
Revisiting Language Models in Neural News Recommender Systems.
In ECIR.
Jin Huang,
Harrie Oosterhuis,
Masoud Mansoury,
Herke van Hoof,
Maarten de Rijke
(2024).
Going beyond popularity and positivity bias: Correcting for multifactorial bias in recommender systems.
In SIGIR.
Ming Li,
Jin Huang,
Maarten de Rijke
(2023).
Repetition and Exploration in Offline Reinforcement Learning-based Recommendations.
In DRL4IR@CIKM workshop.
Jin Huang,
Harrie Oosterhuis,
Bunyamin Cetinkaya,
Thijs Rood,
Maarten de Rijke
(2022).
State Encoders in Reinforcement Learning for Recommendation: A Reproducibility Study.
In SIGIR.
Jin Huang,
Harrie Oosterhuis,
Maarten de Rijke
(2022).
It Is Different When Items Are Older: Debiasing Recommendations When Selection Bias and User Preferences are Dynamic.
In WSDM.
Jin Huang,
Harrie Oosterhuis,
Maarten de Rijke,
Herke van Hoof
(2020).
Keeping Dataset Biases out of the Simulation: A Debiased Simulator for Reinforcement Learning based Recommender Systems.
In RecSys.
Wayne Xin Zhao,
Gaole He,
Kunlin Yang,
Hongjian Dou,
Jin Huang,
Siqi Ouyang,
Ji-Rong Wen
(2019).
KB4Rec: A Data Set for Linking Knowledge Bases with Recommender Systems.
In Data Intelligence.
Jin Huang,
Zhaochun Ren,
Wayne Xin Zhao,
Gaole He,
Ji-Rong Wen,
Daxiang Dong
(2019).
Taxonomy-Aware Multi-Hop Reasoning Networks for Sequential Recommendation.
In WSDM.
Jin Huang,
Wayne Xin Zhao,
Hongjian Dou,
Ji-Rong Wen,
Edward Y. Chang
(2018).
Improving sequential recommendation with knowledge-enhanced memory networks.
In SIGIR.
Wayne Xin Zhao,
Jin Huang,
Ji-Rong Wen
(2016).
Learning Distributed Representations for Recommender Systems with a Network Embedding Approach.
In Asia Information Retrieval Symposium (AIRS).
Experiences
Teaching and Working
Teaching Assistant
- Human-in-the-Loop Machine Learning (MSc., Nov. - Dec. 2024) – MSc Artificial Intelligence
- University of Amsterdam, Amsterdam, The Netherlands
- Designed and gave letures; Graded exercises and exams; Answered students’ questions.
- Recommender Systems (June 2023) – MSc Artificial Intelligence
- University of Amsterdam, Amsterdam, The Netherlands
- Designed and gave letures; Supervised students to reproduce recommendation methods.
- Information Retrieval (Feb. 2023 - March 2023) – MSc Artificial Intelligence
- University of Amsterdam, Amsterdam, The Netherlands
- Graded exercises and exams; Answered students’ questions.
- Reinforcement Learning (Sep. 2021 - Oct. 2021) – MSc Artificial Intelligence
- University of Amsterdam, Amsterdam, The Netherlands
- Designed and graded exercises and exams; Answered students’ questions.
- Reinforcement Learning (Sep. 2020 - Oct. 2020) – MSc Artificial Intelligence
- University of Amsterdam, Online
- Designed and graded exercises and exams; Answered students’ questions.
Student Supervision
- Xuelong Fu (BSc., Nov. 2024 – Jan. 2025)
- Title: A Scoping Review of Current Challenges for Trustworthy AI
- Margot Pauelsen (BSc., March 2023 – June 2023)
- Title: Towards Recommending Method Optimisation: The Effect of Optimisers on Collaborative Filtering Learning
- Calvin Law (BSc., March 2023 – June 2023)
- Title: Investigating the effect of different optimizers on Out-of-distribution scenarios in Recommender Systems
- Cas Hortensius (MSc., March 2022 – June 2022)
- Title: Comparing Collaborative Filtering Recommender Systems for the Hospitality Industry;
- Helma Koopmans (MSc., Feb. 2021 – Feb. 2022)
- Title: Fairness in two-sided markets;
- Thijs Rood (BSc., April – June 2021)
- Title: Attention-based State Encoder in Reinforcement Learning for Recommendation;
- Bunyamin Çetinkaya (BSc., April – June 2021)
- Title: Improving Reinforcement Learning for Recommendation Systems with a Convolutional Neural Network-based State Encoder
- Luke de Keijzer (MSc., March – July 2020)
- Title: Improving Company “Look-a-Likes” Finding Algorithm with the use of Graph Theory.
Internship
- Applied Scientist Intern at Amazon – Seattle, USA, July 2022 – Nov. 2022
- Worked on decomposing complex user goals into a series of simple sub-questions.
- Research Intern at Microsoft Research Asia – Beijing, China, May 2018 – Nov. 2018
- Worked on designing a Knowledge Graph-based Recommender System for a financial institution and Meta-path based Recommender system.
Professional Activities
Workshop Organization
- AgentIR: 1st Workshop on Agent-based Information Retrieval at SIGIR, July 2024.
- 4th Workshop on Deep Reinforcement Learning for Information Retrieval at CIKM, Oct 2023.
Tutorial Organization
- Unbiased Learning to Rank: On Recent Advances and Practical Applications at WSDM, March 2024.
- Recent Advances in the Foundations and Applications of Unbiased Learning to Rank at SIGIR, July 2023.
Reviewer
- Conference: SIGIR 20222024, ECML PPKD 2022, CCL 2022/2023, WSDM 2023/2024/2025, ICTIR
- Journal:
- ACM Transactions on Intelligent Systems and Technology (TIST)
- ACM Transactions on Information Systems (TOIS)
- IEEE Transactions on Knowledge and Data Engineering (TKDE)
- Information Processing and Management (IPM)