Academic Profile : Faculty

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Prof Miao Chun Yan
Chair, School of Computer Science and Engineering
President’s Chair in Computer Science
Professor, School of Computer Science and Engineering
External Links
 
Dr. Jaclyn, Chunyan Miao is a Full Professor in the School of Computer Engineering at Nanyang Technological University (NTU). Her research focus is on infusing intelligent agents into interactive new media (virtual, mixed, mobile and pervasive media) to create novel experiences and dimensions in game design, interactive narrative and other real world agent systems. She has done significant research work her research areas and published over 30 top quality international conference and journal papers. She believes that intelligence/agent augmentation will have a major impact on future new media systems.
Dr. Jaclyn, Chunyan Miao's area of expertise are Agent, Multi-Agent Systems (MAS), Agent Oriented Software Engineering (AOSE), Semantic Web/Grid, Agent Augmented Interactive Media/gaming/storytelling, Agent Mediated e-services?mobile agents for wireless communications. Her current research works focus on infusing intelligent agents into interactive new media (virtual, mixed, mobile and pervasive media) to create novel experiences and dimensions in game design, interactive narrative and other real world agent systems.
 
  • Alibaba-NTU Singapore Joint Research Institute
  • An End-to-end Adaptive AI-Assisted 3H Care (A3C) System
  • Joint NTU-Alibaba Research Institute
  • Joint NTU-WeBank Research Centre on Fintech
  • Joint SDU-NTU Centre for Artificial Intelligence Research(C-FAIR) - Smart Community Research and Talent Programme
  • Monetary Academic Resources for Research
  • Senior-friendly Persuasive AI Companions for an Aging Population
  • The Joint NTU-WeBank Research Centre Of Eco-Intelligent Applications ("THEIA")
  • TrustFUL: Trustworthy Federated Ubiquitous Learning
  • TrustFUL: Trustworthy Federated Ubiquitous Learning (SCSE)
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.

US 2015/0278676 A1: A Curosity-Based Emotion Modelling Method And System For Virtual Companions (2019)
Abstract: The invention proposes that a software agent for assisting a user in a virtual environment defined by a first concept map, maintains a record of its experiences in the form of a second concept map. The concept maps are compared to obtain a measure of stimulation. The measure of stimulation is used to derive a comparison value indicative an emotional state of the user, and the comparison value is used in a reward function to guide the behavior of the software agent.

US 2018/0012261 A1: Computerized Method And System For Personalized Storytelling (2019)
Abstract: A method and system are proposed for presenting information relating to a product to a potential customer for the product, upon the user scanning a 2D barcode using a mobile device. The information is presented to the customer as a story generated by an agent-based storytelling system. The story is personalized to the customer using online multimedia. It can be used to conduct mobile branding and advertisement, and is able thereby to augment offline shopping with online shopping experience.

US 2017/0140409 A1: Computerized Method and System for Automating Rewards to Customers (2019)
Abstract: A computerized reward mechanism system is proposed which makes use both of presently collected data relating to the customer, and a database of historical data relating to the customer. Using this information, the system performs a customer preference analysis, which results in selecting rewards which are adapted to the customers' personal needs. In one form, the system is positioned at a shopping center, and includes cameras for recognising past customers by image processing. This may be done without requiring customers to participate in a process of signing up to use the system. The presently collected data include responses to questions put to the customer relating to his present shopping experience. Customer honesty is considered in the step of determining which rewards to offer the consumer, to encourage the consumers to express their feelings more clearly.

US 2015/0278688 A1: A Episodic And Semantic Memory Based Remembrance Agent Modeling Method And System For Virtual Companions (2018)
Abstract: A remembrance agent is proposed, to be hosted on a wearable computer. The remembrance agent employs a first database (WK) of knowledge about the world in the form of concept maps. Events (“episodes”) experienced by a user are each classified as relating to one or more of the concepts in WK. The episodes are used to produce a second database (episodic memory, EM), and the classification is also used to update a third database (semantic memory, SM) organised using the concepts. The semantic memory thus summarizes the user's interaction with the concepts during the episodes. A current situation of the user is classified according to the concepts, and the classification is used, with the EM and SM, to provide to the user information relevant to the current situation.