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Yizheng Zhao (赵一铮)Associate Professor, PhD SupervisorKnowledge Representation & Reasoning Group (KRistal) School of Artificial Intelligence National Key Laboratory for Novel Software Technology Nanjing University Research Fellow Shenzhen Research Institute of Nanjing University Address: Room A505, Siu Yat-Fu Building, Xianlin Campus, 163 Xianlin Avenue, Qixia District, Nanjing, China Email: zhaoyz [at] nju [dot] edu [dot] cn |
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I obtained my Ph.D. degree in Computer Science from The University of Manchester under the esteemed supervision and guidance of Prof. Renate A. Schmidt, within the same research group where I garnered my initial postdoc work experience. Subsequently, I joined the Department of Computer Science at The University of Oxford as a postdoc researcher, delving into the intricacies of Automata Theory and Database Theory. Since May 2019, I have held the position of Associate Professor in the School of Artificial Intelligence at Nanjing University, contributing actively to AI teaching and research.
Two essential facets of human intelligence are:
My research is situated within the realm of AI, with a particular focus on 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. As one of AI's longest-standing areas, it has been widely acknowledged that knowledge and reasoning are integral components of intelligent behavior. Presently, I am working on Description Logics (DLs) and DL-based Ontologies. DLs are logical formalisms—formal languages with well-defined syntax and semantics—used for representing knowledge about a particular domain. With a rich history in AI, DLs are designed to provide a formal, precise description of domain knowledge and facilitate efficient reasoning over that knowledge. Recently, DLs have gained significant momentum as they form the logical basis of several widely-used ontology languages, such as the W3C Web Ontology Language (OWL)
A periodically updated compilation of my publications can be accessed through the shiny DBLP database online. Additionally, Google Scholar graciously maintains pertinent metadata related to my publications.
| Full Name | Program | Enrollment | Graduation | Highlights |
|---|---|---|---|---|
| Xuan Wu (吴萱) | M.S. | 2020.9 | 2024.6 | Research intern at OSCAR of University of Oxford
One regular paper accepted to WWW2021 (co-first authorship, student travel grant) One demo paper accepted to CIKM2020 (first authorship, student travel grant) |
| Heng Zhang (张恒) | M.S. | 2019.9 | 2022.6 | |
| Yuting Gao (高雨婷) | M.S. | 2020.9 | 2023.6 | |
| Zhao Liu (刘昭) | M.S. | 2020.9 | 2023.6 | 2020 DIGIX全球校园AI算法精英大赛机器学习赛道团体第四名
One regular paper accepted to CIKM2021 (first authorship, student travel grant) Intern at ByteDance, Beijing |
| Yue Xiang (向粤) | M.S. | 2020.9 | 2023.6 | 2020 DIGIX全球校园AI算法精英大赛机器学习赛道团体第四名
One regular paper accepted to WWW2022 (first authorship) |
| Shuni Xu (许书铌) | M.S. | 2020.9 | 2023.6 | 2020 DIGIX全球校园AI算法精英大赛机器学习赛道团体第四名 |
| Zhihao Yang (杨志豪) | M.S. | 2020.9 | 2023.6 | One regular paper accepted to CIKM2024 (first authorship) |
| Yiming Deng (邓一鸣) | M.S. | 2021.9 | 2024.6 | |
| Sen Wang (王森) | M.S. | 2021.9 | 2024.6 | |
| Zhaoyue Xiao (肖棹月) | M.S. | 2021.9 | 2024.6 | |
| Xuanming Zhang (张暄铭) | B.S. | 2016.9 | 2020.6 | Enrolled as a master's student to Columbia University Admitted as a master's student to the University of Cambridge |
| Wenxing Deng (邓文星) | B.S. | 2017.9 | 2021.6 | Enrolled as a master's student to Carnegie Mellon University |
| Chang Lu (陆畅) | B.S. | 2018.9 | 2022.6 | Enrolled as a PhD student to Yale University Admitted as a PhD student to Carnegie Mellon University |
| Yu Dong (董昱) | B.S. | 2018.9 | 2022.6 | 入选2021年度腾讯“犀牛鸟精英工程人才培养计划” Enrolled as a master's student to Nanjing University |
| Haixiang Gan (淦海翔) | B.S. | 2018.9 | 2022.6 | Enrolled as a master's student to Nanjing University |
| Dingwei Shi (施顶威) | B.S. | 2018.9 | 2022.6 | Enrolled as a master's student to Nanjing University |
| Chengjia Wang (王成佳) | B.S. | 2018.9 | 2022.6 | |
| Tianci Zhang (张恬慈) | B.S. | 2018.9 | 2022.6 | |
| Ruiqing Zhao (赵瑞卿) | B.S. | 2018.9 | 2022.6 | 入选2021年度腾讯“犀牛鸟精英工程人才培养计划” Employed as an AI engineer at Bilibili, Shanghai |
| Xinhao Zhu (朱鑫浩) | B.S. | 2018.9 | 2022.6 | 入选2021年度腾讯“犀牛鸟精英工程人才培养计划” Enrolled as a PhD student to Nanjing University |
| Le Guan (官乐) | B.S. | 2019.9 | 2023.6 | 入选2021年度微软亚洲研究院Ada Workshop夏令营 |
| Yi Lu (鲁毅) | B.S. | 2019.9 | 2023.6 | |
| Chenyang Ji (季晨阳) | B.S. | 2019.9 | 2023.6 | |
| Yuxuan Shi (石雨萱) | B.S. | 2019.9 | 2023.6 | |
| Shirui Wang (王诗睿) | B.S. | 2019.9 | 2023.6 | |
| Yuhuan Li (李雨桓) | B.S. | 2020.9 | 2024.6 | |
| Xinwen Zhang (张馨文) | B.S. | 2020.9 | 2024.6 |
Students who are interested in pursuing a research degree, whether at the master's or doctoral level, in the fields of logics, knowledge representation, automated reasoning, ontologies, ontology-based knowledge systems, and other topics within my area of expertise are encouraged to engage in a discussion with me regarding potential 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 assumes full responsibility for his/her work, and is expected to adeptly plan and manage a research project and to deliver on time 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 fueled by naturally inquisitive minds and should possess a fervent passion for problem-solving and advancing human knowledge.
Before deciding to join KRistal, you might want to take note of the following information:KRistal's primary area of investigation centers on knowledge representation and reasoning, grounded in logics
encompassing set theory, model theory, proof theory, and recursion theory (aka computability theory). This research trajectory necessitates a robust mathematical foundation and may present challenges in publishing academic papers,
potentially engendering feelings of anxiety during the course of your studies.
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，读硕/博期间可能会产生焦虑情绪
Currently, the industry offers limited opportunities in this area, which means that even with excellent research and well-received
publications during Master's or Ph.D. studies, it could still be difficult to find a desirable position at a leading company that aligns impeccably
with this research direction or is at the forefront of the industry.
目前业界在这个方向上能提供的机会很少，意味着即便读硕/博期间做出了很好的研究或者发表了很好的论文也可能很难在大公司找到“方向匹配”或“处于行业风口”的工作岗位
Please be honest with yourself and diligently consider personal interests when arriving at decisions. Prudent and responsible decision-making is crucial, as is steadfast commitment to the chosen path. Should your predilections favor inventive thinking and non-conformist actions, we cordially invite you to become a member of KRistal. While KRistal's primary emphasis has traditionally been on the pursuit of fundamental research, our interests have recently begun to gravitate also toward applied research. More specifically, we are broadening our scope by devoting significant efforts to the practical implementation of theoretical insights in matters of commercial or societal import. Our efforts involve exploring and employing KR-based and logic-based methodologies in knowledge-intensive fields and applications, such as those found in medicine and biology. By engaging in these real-world applications, we aim to provide an effective means of validating our theoretical findings and discovering new avenues for further research. Through the continuous refinement of our understanding in practical contexts, we aspire to contribute meaningfully to the advancement of human knowledge and the enhancement of societal well-being.