Academic Lectures | Omega-krr Group

AI Lecture 15: From Logic to Learning: A Computational Complexity Perspective

Mon, 20 Jul 2026 09:00:00 +0800

Speaker: Prof. Yuping Shen (Sun Yat-sen University)
Host: Yisong Wang (Guizhou University)
Time: July 20, 2026 (Monday), 9:00–11:00
Venue: Room 402, Zhishan Building, Guizhou University

Abstract

The talk reviews logic and learning from a computational-complexity perspective and discusses recent progress and conjectures involving nonmonotonic propositional logic.

Speaker biography

Prof. Shen works at the Institute of Logic and Cognition, Sun Yat-sen University. His research focuses on logic and computation, and knowledge representation and reasoning.

AI Lecture 16: Neuro-Symbolic Systems and Applications

Mon, 20 Jul 2026 09:00:00 +0800

Speaker: Prof. Maonian Wu (Huzhou University)
Host: Yisong Wang (Guizhou University)
Time: July 20, 2026 (Monday), 9:00–11:00
Venue: Room 402, Zhishan Building, Guizhou University

Abstract

The lecture reviews neuro-symbolic integration, including symbolic constraints, division of labor, and latent-space logical embedding, with examples such as AlphaGeometry.

Speaker biography

Prof. Wu leads the Department of Artificial Intelligence at Huzhou University and studies artificial intelligence and its applications.

AI Lecture 14: Computational Discrete Global Geometric Structures

Sun, 19 Jul 2026 16:00:00 +0800

Speaker: Hui Zhao (Founder and Chief Scientist, Computational Discrete Global Geometric Structures Laboratory) +- Time: July 20, 2026 (Monday), 16:00
Venue: 13F Lecture Hall, Boxue Building, East Campus, Guizhou University

Abstract

The lecture introduces computational discrete global geometric structures, including geometric programming, global intrinsic properties in discrete meshes, visualization, and applications of heuristic algorithms.

Speaker biography

Dr. Zhao has conducted research and teaching at universities and research institutes in China and abroad, focusing on computational discrete global geometric structures.

AI Lecture 13: Medical Knowledge Graphs: Technologies and Applications

Wed, 19 Nov 2025 09:00:00 +0800

Speaker: Prof. Zhisheng Huang (Vrije Universiteit Amsterdam)
Host: Yisong Wang (Guizhou University)
Time: November 19, 2025 (Wednesday), 9:00–10:30
Venue: Room 712, Chonghou Building, Guizhou University

Abstract

The lecture introduces medical knowledge graphs, their development and key technologies, and presents applications involving depression and gut microbiome knowledge graphs.

Speaker biography

Prof. Huang works in the Artificial Intelligence department at Vrije Universiteit Amsterdam and studies semantic technologies, medical AI, and knowledge graphs.

AI Lecture 12: Visual Question Answering Using ASP

Thu, 31 Oct 2024 14:00:00 +0800

Speaker: Prof. Thomas Eiter (TU Wien)
Host: Yisong Wang (Guizhou University)
Time: October 31, 2024 (Thursday), 14:00–15:00
Venue: 13F Lecture Hall, Boxue Building, Guizhou University

Abstract

The talk studies visual question answering with Answer Set Programming in a modular neuro-symbolic architecture, including explanation finding and ongoing work involving LLMs.

Speaker biography

Prof. Eiter leads the Knowledge-Based Systems Group and the Institute of Logic and Computation at TU Wien. His work covers knowledge representation and reasoning, computational logic, algorithms, and complexity in AI.

AI Lecture 11: Trustworthy AI Models and Systems for Autonomous Decision Making

Sat, 24 Aug 2024 10:00:00 +0800

Speaker: Prof. Jun Liu (Ulster University)
Host: Yisong Wang (Guizhou University)
Time: August 24, 2024 (Saturday), 10:00–12:00
Venue: Room 402, Zhishan Building, Guizhou University

Abstract

The lecture covers trustworthy AI models and systems, including transparency, explainability, fairness, robustness, trust, and reliability, with relevant case studies.

Speaker biography

Prof. Liu is Professor of Computer Science and Director of the AI Research Centre at Ulster University. His work spans computational intelligence, trustworthy AI, knowledge systems, and information fusion.

AI Lecture 10: Approximation Fixpoint Theory Generalized and its Application to Hybrid MKNF Knowledge Bases

Mon, 08 Jul 2024 14:00:00 +0800

Speaker: Prof. Jia-Huai You (University of Alberta)
Host: Yisong Wang (Guizhou University)
Time: July 8, 2024 (Monday), 14:00–15:30
Venue: Room 402, Zhishan Building, Guizhou University

Abstract

The talk applies Approximation Fixpoint Theory to hybrid MKNF knowledge bases and discusses a generalization from symmetric to arbitrary approximators.

Speaker biography

Prof. You is a professor at the University of Alberta. His research interests include artificial intelligence, logic programming, and knowledge representation and reasoning.

AI Lecture 9: Formal Design of Embedded Systems

Mon, 04 Dec 2023 11:00:00 +0800

Speaker: Prof. Naijun Zhan (Institute of Software, CAS)
Host: Yisong Wang (Guizhou University)
Time: December 4, 2023 (Monday), 11:00–11:30
Venue: Room 402, Administration Building No. 2, Guizhou University

Abstract

The lecture presents model-based formal design of embedded systems, including translations between Simulink/Stateflow and HCSP, Hybrid Hoare Logic verification, co-simulation, approximate bisimulation, and the MARS toolchain.

Speaker biography

Prof. Zhan is a research professor at the Institute of Software, Chinese Academy of Sciences. His interests include real-time and hybrid systems, program verification, modal and temporal logics, and concurrent computation.

AI Lecture 8: Generative AI in the Era of Large Models: Opportunities and Challenges

Fri, 30 Jun 2023 10:30:00 +0800

Speaker: Prof. Haijun Zhang (HIT Shenzhen)
Host: Yongjun Zhang (Guizhou University)
Time: June 30, 2023 (Friday), from 10:30
Venue: 13F Lecture Hall, Boxue Building, Guizhou University

Abstract

The lecture reviews the history of AI and ChatGPT, generative AI and generative fashion AI, presents the team’s AIGC research, and discusses future fashion intelligence in a metaverse setting.

Speaker biography

Prof. Zhang is a professor and doctoral supervisor at HIT Shenzhen. His research includes data mining, machine learning, generative AI, and fashion intelligence.

AI Lecture 7: Using Language Models for Knowledge Acquisition in Natural Language Reasoning Problems

Fri, 09 Jun 2023 10:00:00 +0800

Speaker: Prof. Fangzhen Lin (HKUST)
Host: Yisong Wang (Guizhou University)
Time: June 9, 2023 (Friday), 10:00–11:00
Venue: Room 402, Zhishan Building, Guizhou University

Abstract

The talk compares asking an LLM to solve natural-language reasoning problems directly with using the model to extract facts before passing them to a theorem prover.

Speaker biography

Prof. Lin earned his PhD in Computer Science from Stanford University in 1991 and is an AAAI Fellow. His research includes nonmonotonic reasoning, autonomous agents, logic programming, and reasoning about action.

AI Lecture 6: A Modular Approach to Datalog Reasoning

Sat, 06 May 2023 15:00:00 +0800

Speaker: Dr. Pan Hu (Shanghai Jiao Tong University)
Host: Yisong Wang (Guizhou University)
Time: May 6, 2023 (Saturday), 15:00–16:00
Venue: Room 402, Administration Building No. 2, Guizhou University

Abstract

The talk presents a modular Datalog reasoning framework that combines standard and customized algorithms through rule modules, including transitivity, symmetry-transitivity, chain rules, and cyclic bodies.

Speaker biography

Dr. Hu is a lecturer and master’s supervisor at Shanghai Jiao Tong University. His research focuses on knowledge representation and reasoning.

AI Lecture 5: Semantic-Guided Zero-Shot Learning

Mon, 03 Apr 2023 19:30:00 +0800

Speaker: Dr. Shiming Chen (CMU)
Host: Yisong Wang (Guizhou University)
Time: April 3, 2023 (Monday), 19:30–21:00
Venue: 13F Meeting Room, Boxue Building, Guizhou University

Abstract

Zero-shot learning transfers semantic knowledge from seen to unseen classes. This talk presents a series of studies on effective visual-semantic interaction for zero-shot learning.

Speaker biography

Dr. Chen studies computer vision and machine learning, including zero-shot learning, generative modeling, vision-language learning, and causal representation learning.

AI Lecture 4: Automated Prototype Generation from Requirements Model

Thu, 17 Oct 2019 10:30:00 +0800

Speaker: Dr. Yilong Yang +- Time: October 17, 2019 (Thursday), 10:30–11:30
Venue: Room 621, Boxue Building, Guizhou University

Abstract

The talk presents RM2PT, an approach and tool for automatically generating software prototypes from formal requirements models for requirements validation.

Speaker biography

Dr. Yang earned his PhD in Software Engineering from the University of Macau in 2019 and was a Fellow at UNU-IIST. His research focuses on automated and intelligent software engineering.

AI Lecture 3: Building a Fast CSP Solver based on SAT

Mon, 17 Jun 2019 10:00:00 +0800

Speaker: Prof. Neng-Fa Zhou (CUNY) +- Time: June 17, 2019 (Monday), 10:00–11:00
Venue: Room 701, Boxue Building, Guizhou University

Abstract

This tutorial introduces the inner workings of PicatSAT, a SAT-based CSP solver in Picat that won prizes in the 2018 XCSP Competition and MiniZinc Challenge.

Speaker biography

Prof. Zhou teaches Computer and Information Science at Brooklyn College and the Graduate Center, CUNY. He earned his bachelor’s degree from Nanjing University and his master’s and doctoral degrees from Kyushu University.

AI Lecture 2: A Mathematical Engineering Perspective on Machine Learning

Fri, 17 May 2019 10:00:00 +0800

Speaker: Prof. Zhihua Zhang (Peking University) +- Time: May 17, 2019 (Friday), 10:00–12:00
Venue: Room 701, Boxue Building, Guizhou University

Abstract

The talk reviews key stages in the development of machine learning, discusses four foundational principles, and proposes understanding machine learning as mathematical engineering.

Speaker biography

Prof. Zhang works at the School of Mathematical Sciences and the Beijing Institute of Big Data Research, Peking University. His research focuses on statistical machine learning and artificial intelligence.

AI Lecture 1: Understanding the World and Machine Learning

Mon, 01 Apr 2019 09:00:00 +0800

Speaker: Prof. Xizhi Wu +- Time: April 1, 2019 (Monday), 9:00–11:00
Venue: Room 701, Boxue Building, Guizhou University

Abstract

This lecture discusses the relationship between understanding the world, scientific thinking, machine learning, data science, and statistics.

Speaker biography

Prof. Wu studied mathematics and mechanics at Peking University and earned a PhD in Statistics from the University of North Carolina at Chapel Hill. His research spans sequential analysis, regression diagnostics, model selection, robust statistics, and Bayesian statistics.