Personal Profile
Zhou Yi, male, is a professor and Doctoral Supervisor at the University of Science and Technology of China (USTC) and the director of the Knowledge Computing Laboratory. He previously served as a researcher at the Zhangjiang Laboratory and a professor at the Massey University of New Zealand, who was selected into the Shanghai High-Level Talent Program. His research focuses on artificial intelligence, mainly including:
-Cognitive Intelligence**:How machines can better represent, learn, and reason knowledge; knowledge + database management systems; understanding natural and machine languages; knowledge-based AI programming languages; automatic answering for IMO, etc.
-Brain-like Intelligence**: Designing new neural network mechanisms by deeply learning from significant discoveries in brain science.
-Combination of Cognitive and Brain-like Intelligence**: Integrating logic-based knowledge-driven symbolism and neural network-based data-driven connectionism.
-Applications of Cognitive and Brain-like Intelligence**: Applying cognitive and brain-like intelligent in fields such as operations and maintenance, asset management, education, industry, and healthcare.
Professor Zhou Yi has made significant contributions to the field of artificial intelligence. He originally proposed a new knowledge model—the Knowledge Equation—and is a foundational figure and major proponent of First-Order Answer Set Programming. He put forward the first axiom system characterizing forgetting and won the championship in the First Automatic Answering Robot Competition for the SAT Mathematical Problems. He has published over 50 papers in top AI journals and conferences, including 6 long papers in the top journal Artificial Intelligence. For a long time, he has served as a member for the programming committees of top AI conferences, including IJCAI, AAAI, and KR
Educational Background
- 2001.9 – 2006.6: Studied at the School of Computer Science and Technology, University of Science and Technology of China, majoring in Artificial Intelligence and obtaining a Ph.D. in Engineering.
- 1997.9 – 2001.7: Studied at the School of the Gifted Young, University of Science and Technology of China, obtaining a Bachelor's Degree in Engineering.
Ongoing Projects
- Ministry of Science and Technology, Science and Technology Innovation 2030—“Brain Science and Brain-like Research” major project, neural mechanisms of multisensory integration.
- Shanghai Municipal Science and Technology Commission, AI Special Project, representation and reasoning of complex knowledge based on symbolic logic.
- Key Projects of National Defense Science and Technology Innovation Special Zone, representation, reasoning, and learning of new-generation commonsense knowledge.
- Key Projects of National Defense Science and Technology Innovation Special Zone, research on cognitive intelligence computing theory.
- Shanghai Municipal Organization Department, High-Level Talent Program.
Developed Systems
- True Knowledge Learning: Application of cognitive intelligence in automatic mathematical correction, intelligent tutoring, precise error analysis, and personalized teaching.
- Cognitive Monitoring: APP for the application of multimodal AI and personalized assessment recommendations of intelligence in cognitive functions and brain diseases such as AD (in cooperation with Shanghai Mental Health Center).
- Sunshine Mood: APP for the application of multimodal AI and personalized assessment recommendations of intelligence in brain diseases including depression and anxiety (in cooperation with Shanghai Mental Health Center).
- Automatic IQ Test Competition**: Holding the automatic IQ test competition (MAIQ’20) at IJCAI’20.
- Dolphin Smart Learning**: Application of cognitive AI in adaptive education in mathematics (in cooperation with East China Normal University).
- AiFu: Automatic Mathematical Problem-Solving System for SAT (in cooperation with iFlytek and Fudan University), which inputs English mathematical problems (including algebraic problems, application problems, and geometric problems) and outputs their solution processes and answers. AiFu secured a championship in the First Automatic Answering Robot Competition for the SAT Mathematical Problems organized by SemEval-2019, with a calibration accuracy more than four times that of other teams.
- groc2.0: An enhanced version of groc (in cooperation with Vernon Asuncion, Chen Yin, and Zhang Yan). This system, based on the original groc, handles general first-order answer set logic programs with aggregation functions. When inputting a general first-order answer set logic program with aggregation functions and a database, the system will output one of its answer sets. The basic principle of this system may refer to representative paper 2.
- groc: First-order answer set program solver (in cooperation with Vernon Asuncion, Chen Yin, and Zhang Yan). When inputting a first-order answer set logic program and a database, the solver will output one of its answer sets. The basic principle of this system may refer to representative paper 4.
- dl2asp: Default logic solver (in cooperation with Wan Hai, Chen Yin, and Zhang Yan). When inputting a default logic knowledge base, the solver will output one of its models. The basic principle is to convert default logic into answer set programs.
- asp2sat: Propositional answer set program solver (in cooperation with Vernon Asuncion and Zhang Yan). When inputting a propositional answer set logic program, the solver will output one of its answer sets. The basic principle is to transform the logic program into propositional logic by adding new variables.
- CTLupdater: Automatic temporal logic formula correction tool (in cooperation with Michael Kelly and Zhang Yan). When inputting an inconsistent temporal logic CTL knowledge base, the tool will output a consistent knowledge base corrected through calculating and correcting the model, according to the minimal change principle.
Representative Works
•SHAPE: An Unified Approach to Evaluate the Contribution and Cooperation of Individual Modalities. Pengbo Hu, Xingyu Li and Yi Zhou. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI’22). 2022.
•DDDM: A Brain-Inspired Framework for Robust Classification. Xiyuan Chen, Xingyu Li, Yi Zhou and Tianming Yang. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI’22). 2022.
•Transfer learning for fine-grained entity typing. Feng Hou, Ruili Wang, Yi Zhou Knowledge Information Systems. 63(4): 845-866. 2021.
•Improving Entity Linking through Semantic Reinforced Entity Embeddings. Feng Hou, Ruili Wang, Jun He, Yi Zhou. ACL 2020: 6843-6848. 2020.
•Visual Analytics of Genomic and Cancer Data: A Systematic Review. Zhonglin Qu, ChgnWei Lau, Yi Zhou, Quang Vinh Nguyen, Daniel R. Catchpoole. Cancer Informatics. 2019.
•How Well Do Machines Perform on IQ test: a Comparison Study on a Large-Scale Dataset. Yusen Liu, Fangyuan He, Haodi Zhang, Guozheng Rao, Zhiyong Feng, Yi Zhou. In Proceedings of IJCAI’19. 2019.
•KDSL: a Knowledge-Driven Supervised Learning Framework for Word Sense Disambiguation. Shi Yin, Yi Zhou, Chengguang Li, Shangfei Wang, Jianmin Ji, Xiaoping Chen and Ruili Wang. In Proceedings of IJCNN’19. 2019.
•AiFu at SemEval-2019 Task 10: A Symbolic and Sub-symbolic Integrated System for SAT Math Question Answering. Keyu Ding, Yifan Liu, Yi Zhou, Binbin Deng, Chaoyang Peng, Dinglong Xue, Qinzhuo Wu, Qi Zhang and Enhong Chen). In Proceedings of NAACL’19. 2019.
•Dual-enhanced Word Representations Based on Knowledge Base. Fangyuan He, Haodi Zhang, Zhiyong Feng and Yi Zhou. In Proceedings of International Semantic Web Conference 2018 (ISWC’18). 2018
•From First-Order Logic to Assertional Logic. Yi Zhou. In Proceedings of AGI’17. 2017.
•Integrating Answer Set Programming with Semantic Dictionaries for Robot Task Planning. Dongcai Lu, Yi Zhou, Feng Wu and Xiaoping Chen. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI’17). 2017.
•A Progression Semantics for First-Order Logic Programs. Yi Zhou, Yan Zhang, Artificial Intelligence. 250: 58-79. 2017.
•First-Order Disjunctive Logic Programming vs Normal Logic Programming. Yi Zhou. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI’15). 2015.
•Ordered Completion for Logic Programs with Aggregates. Vernon Asuncion, Yin Chen, Yan Zhang and Yi Zhou. Artificial Intelligence (AIJ). 224: 72-102. 2015.
•Knowledge Forgetting in Answer Set Programming. Yisong Wang, Yan Zhang Yi Zhou and Mingyi Zhang. Journal of Artificial Intelligence Research (JAIR). 50: 31-70. 2014.
•Preferred First-order Answer Set Programs. Vernon Asuncion, Yan Zhang, Yi Zhou. ACM Transaction on Computational Logic (TOCL). 15(2):11. 2014.
•From Disjunctive to Normal Logic Programs via Unfolding and Shifting. Yi Zhou. In Proceedings of the Twenty-first European Conference on Artificial Intelligence (ECAI’14). 2014
•First-Order Default Logic Revisited. Yi Zhou. In Proceedings of the 14th International Conference on The Principles of Knowledge Representation and Reasoning (KR’14). 2014.
•Ordered Completion for First-order Logic Programs on Finite Structures (with Vernon Asuncion, Fangzhen Lin and Yan Zhang). Artificial Intelligence (AIJ). 177-179, 1-24, 2012.
•Ordered Completion for Logic Programs with Aggregates. (with Vernon Asuncion and Yan Zhang). In Proceedings of the Twenty-sixth AAAI conference on Artificial Intelligence (AAAI’12). 2012.
•Forgetting in Logic Programs under Strong Equivalence (with Yisong Wang, Yan Zhang and Mingyi Zhang). In Proceedings of the 13th International Conference on The Principles of Knowledge Representation and Reasoning (KR’12). 2012.
•RDL: Enhancing Description Logics with Rules (with Yan Zhang). In Proceedings of the 25 th Australia Joint Conference on Artificial Intelligence (AI’12). 2012.
•Loop Separable Programs and Their First-order Definability (with Yin Chen, Fangzhen Lin and Yan Zhang). Artificial Intelligence (AIJ). 175(3-4), 890-913, 2011.
•A Logical Study of Partial Entailment (with Yan Zhang). Journal of Artificial Intelligence Research (JAIR), 40, 25-56, 2011.
•From Answer Set Logic Programming to Circumscription via Logic of GK (with Fangzhen Lin). Artificial Intelligence, 175(1): 267-271. 2011.
•Bounded Forgetting (with Yan Zhang). In Proceedings of the Twenty-fifth AAAI conference on Artificial Intelligence (AAAI’11). 2011.
•Progression Semantics for Disjunctive Programs (with Yan Zhang). In Proceedings of the Twenty-fifth AAAI conference on Artificial Intelligence (AAAI’11). 2011.
•Translating Theories into Logic Programs. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI’11). 2011.
•Foundations of Tree-like Local Model Updates (with Yan Zhang and Michael Kelly). In proceedings of 19th European Conference on Artificial Intelligence (ECAI’10). 2010.
•Some Negative Results on First-order Definability of Answer Set Programs (with Yin Chen and Yan Zhang). In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI’10). 2010.
•Ordered Completion for First-Order Logic Programs on Finite Structures (with Vernon Asuncion, Fangzhen Lin and Yan Zhang). In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI’10). 2010.
•On the Progression Semantics and Boundedness of Answer Set Programs (with Yan Zhang). In Proceedings of the Twelfth International Conference on the Principles of Knowledge Representation and Reasoning (KR’10). 2010.
•Forgetting Revisited (with Yan Zhang). In Proceedings of the Twelfth International Conference on the Principles of Knowledge Representation and Reasoning (KR’10). 2010.
•Knowledge Forgetting: Properties and Applications (with Yan Zhang). Artificial Intelligence. 173(16-17), 1525-1537. 2009.
•General Default Logic (with Fangzhen Lin and Yan Zhang). Annals of Mathematics and Artificial Intelligence. 57(2), 125-160. 2009.
•Partial Goal Satisfaction and Goal Change (with Leon van der Torre and Yan Zhang). In Proceedings of the Seventh International Conference on Autonomous Agents and Multiagent Systems (AAMAS’08): 413-420, 2008.
•From Answer Set Logic Programming to Circumscription via Logic of GK (with Fangzhen Lin). In proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI’07): 441-446, 2007.
•Partial Implication Semantics for Desirable Propositions (with Xiaoping Chen). In proceedings of the Ninth International Conference on Principles of Knowledge Representation and Reasoning (KR’04): 606-612, 2004.
Admissions Directions
· Master: Signal and Information Processing, Artificial Intelligence
· Ph.D.: Signal and Information Processing, Artificial Intelligence