个人简介

Short Bio I obtained my Ph.D. degree in Computer Science from The University of Manchester, (by good fortune) under the supervision of Prof. Renate A. Schmidt, where in the same research group I acquired my first postdoctoral work experience. Right after this, I joined the Department of Computer Science at University of Oxford as a postdoctoral researcher, where I took a sip of Automata Theory and Database Theory. From May 2019, I have been working as an associate professor in the School of Artificial Intelligence at Nanjing University. Research Interests Two crucial facets of human intelligence: .The ability to learn from experience and perform better when confronted with similar situations or adapt to new situations .The ability to maintain an internal (abstract) state of knowledge and reason about that knowledge to draw new conclusions In Artificial Intelligence (AI), these two abilities are respectively embodied by [Machine Learning] and [Knowledge Representation and Reasoning]. My research is situated in the realm of AI, with particular interest in Logics for Knowledge Representation and Reasoning (KR or KRR). KR is concerned with the study of how beliefs, intentions, and value judgments of an intelligent agent can be expressed in a transparent, symbolic notation suitable for automated reasoning. It is one of the oldest areas of AI, as from early on researchers realized that knowledge and reasoning are two of the key components of intelligent behavior. I am currently working with Description Logics (DLs) and DL-based Ontologies. DLs are logical formalisms (formalisms = formal languages = languages with formal syntax and semantics) for representing knowledge about a domain of interest; they have a long tradition in AI, being designed so that domain knowledge can be described and so that computers can reason about this knowledge. DLs have recently gained significant momentum since they form the logical basis of widely used ontology languages such as the W3C Web Ontology Language (OWL). Publications An irregularly updated list of my publications is available online via a shiny DBLP database. Also, Google Scholar is so kind to maintain the metadata of my publications. Research Projects 基于常识知识库与反绎学习的对话管理模型 (腾讯犀牛鸟创意基金, 2021.10 - 2022.9, 主持) 大规模OWL医学本体的自动化构建与复用 (之江实验室面上项目, 2021.1 - 2022.12, 主持) 大规模医学本体上的语义差异追踪 (国家自然科学基金青年科学基金, 2021.1 - 2023.12, 主持) SNOMED CT临床医学术语集的版本差异计算 (江苏省自然科学基金面上项目, 2021.7 - 2024.6, 主持) 基于遗忘算法的知识推理技术在SNOMED CT开发升级中的应用 (中央高校基本科研业务费国际合作专项资金, 2020.5 - 2021.9, 主持) 基于知识驱动的人工智能技术的探究 (中央高校基本科研业务费, 2020.3 - 2021.9, 主持) EPSRC IAA 204: Advanced Reasoning Technologies for Medical Ontologies (英国工程与自然科学研究理事会, 2017.9 - 2018.4, 参与) EPSRC EP/M005852/1: Proof-driven Query Planning (英国工程与自然科学研究理事会, 2015.6 - 2020.12, 参与) Upcoming Group Seminars Yue Xiang 2021/11/2 19:00 -- 21:00 @A410: Conference Paper: Foundations for Uniform Interpolation and Forgetting in Expressive Description Logics [Lutz and Wolter, IJCAI'11] Xuan Wu 2021/11/8 18:00 -- 20:00 @A410: Journal Article: HiG2Vec: hierarchical representations of Gene Ontology and genes in the Poincare ball [Kim et al., Bioinformatics] Conference Paper: EL Embeddings: Geometric Construction of Models for the Description Logic EL++ [Kulmanov et al., IJCAI'19] Zhao Liu 2021/11/15 18:00 -- 20:00 @A410: Conference Paper: Just the Right Amount: Extracting Modules from Ontologies [Cuenca Grau et al., WWW'07] Yiming Deng, Sen Wang, Zhaoyue Xiao 2021/11/22 18:00 -- 20:00 @A410: Conference Paper: Semi-Supervised Abductive Learning and Its Application to Theft Judicial Sentencing [Huang et al., ICDM'20] Shuni Xu 2021/11/29 18:00 -- 20:00 @A410: Conference Paper: Small Is Beautiful: Computing Minimal Equivalent EL Concepts [Nikitina and Koopmann, AAAI'15] Zhihao Yang 2021/12/6 18:00 -- 20:00 @A410: Research Progress Report: An Empirical Comparison of Publicly-Accessible Modularization and Uniform Interpolation Tools Group Tutorial Part I 2021/12/12 9:00 -- 18:00 @A410: Book: An Introduction to the Theory of Computation [M. Sipser, 2012] Group Tutorial Part II 2021/12/20 18:00 -- 21:00 @A410: Book: An Introduction to the Theory of Computation [M. Sipser, 2012] Zhihao Yang 2021/12/30 18:00 -- 19:30 @A410: Journal Article: Dimensions of Commonsense Knowledge [Ilievski et al., KBS'21] Zhao Liu 2021/12/30 19:30 -- 21:00 @A410: Conference Paper: Use of OWL and Semantic Web Technologies at Pinterest [Gonçalves et al., ISWC'19] Yiming Deng, Sen Wang, Zhaoyue Xiao 2022/01/03 18:00 -- 21:00 @A410: Conference Paper: Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning [Li et al., ICML'20] Conference Paper: Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning" [Amizadeh et al., ICML'20] Yiming Deng, Sen Wang, Zhaoyue Xiao 2022/01/30 16:00 -- 17:30 @A410: Conference Paper: Concept Abduction and Contraction for Semantic-Based Discovery of Matches and Negotiation Spaces in an E-Marketplace [Colucci et al., ECRA'05] Info for Prospective Research Students Students interested in pursuing a research degree, either a master's or doctoral degree, in the areas of logics, knowledge representation, automated reasoning, ontologies, ontology-based knowledge systems, and other topics within my area of expertise are welcome to have a chat with me about possible projects. The core of a research degree is the successful completion of a research project that makes an original contribution to knowledge in a particular area of study. Although guided and advised by an expert, a research student takes full responsibility for their work. You will be expected to successfully plan and manage your research project and to deliver on time (and to budget) a thesis of appropriate standard. An important aspect of a research degree is the opportunity for training, not only in specialist research techniques but also in transferable skills relevant to employability and personal development. Research students are driven by naturally inquiring minds, and should have a strong passion to solve problems and advance humanity. For the present within KRistal, in desperate need are students to undertake research on the topic of ontology learning from text. In particular, the topic is concerned with identifying terms, concepts, relations, and optionally axioms from textual information and using them to construct and maintain ontologies, which can be based on the artistry of natural language processing, machine learning, data mining, and information retrieval. Hence, students with immense interest and strong footing in these areas are greatly preferred. Before deciding to join KRistal, you may want to take care of the following information: KRistal的主要研究方向是基于逻辑语义（集合论 模型论 证明论 递归论）的知识表示与推理，这个方向需要扎实的数学功底并且不好发论文，读研/博期间可能会产生焦虑情绪 目前业界在这个方向上能提供的机会很少，意味着即便读研/博期间做出了很好的研究发表了很好的论文也可能很难在大厂大公司找到“方向匹配”或“处在风口”的心仪岗位 Please be truthful to your self and respectful of your interest, make a careful, responsible decision and stay committed to your decision. If you insist on thinking & acting outside the box, hmm...welcome to join KRistal:-) Teaching At overseas universities: Object-Oriented Programming with Java (for first-year undergraduates, 2013 - 2015) Fundamentals of Artificial Intelligence (for first-year undergraduates, 2014 - 2015) Fundamentals of Computation (for first-year undergraduates, 2016 - 2017) Fundamentals of Databases (for second-year undergraduates, 2013 - 2015) Software Engineering (for second-year undergraduates, 2014 - 2015) Logic and Modeling (for second-year undergraduates, 2015 - 2018) Automated Reasoning and Verification (for graduates, 2013 - 2017) Ontology Engineering for the Semantic Web (for graduates, 2013 - 2018) Data Engineering (for graduates, 2013 - 2018) At Nanjing University: Automated Planning and Reasoning (for graduates, 2019 - 2021) Knowledge Representation and Processing (for second-year undergraduates & graduates, 2019 - 2021) Mathematical Logics (for first-year undergraduates, 2020 - 2021)