Academic Profile : Faculty

Han Yu.jpg picture
Asst Prof Yu Han
Nanyang Assistant Professor, School of Computer Science and Engineering
External Links
 
Dr Han Yu is a Nanyang Assistant Professor (NAP) in the School of Computer Science and Engineering (SCSE), Nanyang Technological University (NTU), Singapore. He has been a Visiting Scholar at the Department of Computer Science and Engineering, Hong Kong University of Science and Technology (HKUST) from 2017 to 2018. Between 2015 and 2018, he held the prestigious Lee Kuan Yew Post-Doctoral Fellowship (LKY PDF) at the Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY). Before joining NTU, he worked as an Embedded Software Engineer at Hewlett-Packard (HP) Pte Ltd, Singapore. He obtained his PhD from the School of Computer Science and Engineering, NTU in 2014. During his PhD study, he held the prestigious Singapore Millennium Foundation (SMF) PhD Scholarship. His research focuses on online convex optimization, ethical AI, federated machine learning and their applications in complex collaborative systems such as crowdsourcing. He has published over 150 research papers in book chapters, leading international conferences and journals including AAAI, IJCAI, CVPR, SIGIR, ASE, ACM MM, CIKM, AAMAS, NAACL, ICME and ACM/IEEE Transactions. He co-authored the book "Federated Learning" - the first monograph on the topic of federated learning. His research work has been recognized with 25 awards from conferences and journals. He is an Associate Editor of IEEE TNNLS. He is a founding Co-PI of the Trustworthy Federated Ubiquitous Learning (TrustFUL) Research Lab (https://trustful.federated-learning.org/).
Crowdsourcing and Human Computation
Ethical Artificial Intelligence (AI)
Federated Learning
Trust and Reputation Management
 
  • AI-Powered Crowd-computing
  • Next-Generation Brain-Computer-Brain Platform – A Holistic Solution for the Restoration & Enhancement of Brain Functions (NOURISH)
  • Towards Real-time, Seamless, and Ubiquitous Edge Intelligence-empowered Metaverse
  • Trust-based Open Collaborative Federated Learning
  • TrustFUL: Trustworthy Federated Ubiquitous Learning
  • TrustFUL: Trustworthy Federated Ubiquitous Learning (SCSE)
  • TrustFUL: Trustworthy Federated Ubiquitous Learning (WeBank)
US 2016/0379296 A1: Method And Apparatus For Algorithmic Control Of The Acceptance Of Orders By An E-Commerce Enterprise (2021)
Abstract: This invention proposes an autonomous interaction decision support apparatus to provide the operator of an e-commerce business with a recommendation of which received orders to perform. The apparatus autonomously tracks situational information comprising the existing level of work of the e-business, for each of multiple products and/or services offered by the business, and also a desired level of work. In this way, the recommendation protects both the reputation of the business and achieves work-life balance for the business owner.
Awards
2022: Best Paper Award, AI for Transportation Workshop, AAAI-22 - "DADFNet: Dual Attention and Dual Frequency-Guided Dehazing Network for Video-Empowered Intelligent Transportation".
2022: Innovative Applications of AI Award, AAAI - "Contribution-Aware Federated Learning for Smart Healthcare".
2022: Innovative Applications of AI Award, AAAI - "Intelligent Online Selling Point Extraction for E-Commerce Recommendation".
2022: Innovative Applications of AI Award, AAAI - "Automatic Product Copywriting for E-Commerce".
2022: Innovative Applications of AI Award, AAAI - "Prior-Guided Transfer Learning for Enhancing Item Representation in E-commerce".
2021: Best Paper Award, "Personalised Federated Learning: A Combinational Approach," STCAI'21.
2021: PREMIA Best Student Paper Runners Up Award, "Noise-resistant Deep Metric Learning with Ranking-based Instance Selection", CVPR'21.
2021: PREMIA Best Presentation Award, "Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection", NAACL-HLT'21.
2021: Innovative Applications of AI Award, AAAI - "Enhancing E-commerce Recommender System Adaptability with Online Deep Controllable Learning-To-Rank".
2020: Innovative Applications of AI Award, AAAI - "FedVision: An Online Visual Object Detection Platform powered by Federated Learning".
2020: Innovative Applications of AI Award, AAAI - "Accelerating Ranking in E-Commerce Search Engines through Contextual Factor Selection".
2020: Innovative Applications of AI Award, AAAI - "PIDS: An Intelligent Electric Power Management Platform".
2019: Innovation Award, IJCAI'19 - "Fair and Explainable Dynamic Engagement of Crowd Workers".
2019: Most Educational Video Award, IJCAI'19 - "Learning Federated Learning".
2018: Most Societally Beneficial Video Award, IJCAI'18 - "Persuasive AI Companions for Active Independent Ageing".
2018: Innovative Applications of AI Award, AAAI - "SmartHS: An AI Platform for Improving Government Service Provision".
2017: Best Student Paper Award, IJIT - "Towards Trust-aware Health Monitoring Body Area Sensor Network".
2016: Best Poster Award, ICCSE'16 - "Efficient Crowd-powered Active Learning for Reliable Review Evaluation".
2016: Best Paper Award, ICCSE'16 - "Towards Data-driven Software Engineering Skills Assessment".
2016: Best Paper Award, SCSM'16 - "Towards Emotionally Intelligent Machines: Taking Social Contexts into Account".
2016: Best Student Poster Award, AAAI-16 - "Efficient Collaborative Crowdsourcing".
2016: Best Video - People's Choice Award, AAAI-16 - "Artificial Intelligence for Liveable Cities".
2015: Best Demo Award, WI-IAT'15 - "Agent Augmented Inter-generational Crowdsourcing".
2015: Best Application Video Award, IJCAI'15 - "Goal Oriented Teachable Agent in Virtual Learning Environment".
2011: Best Paper Award, ICCT'11 - "Dynamic Witness Selection for Trustworthy Distributed Cooperative Sensing in Cognitive Radio Networks"
 
Fellowships & Other Recognition
2015 - 2018: Lee Kuan Yew Post-Doctoral Fellow (LKY PDF)
 
Courses Taught
AI6101, CET794, CET799, CZ2004, CZ3003, CZ3005, CZ4031