Distinguished Lecturers

 

Dipankar DasguptaDipankar Dasgupta, IEEE Fellow (2022-2024) (abstract)

William Hill Professor of Computer Science

Director, Center for Information Assurance (CfIA)
The University of Memphis

Homepage: 
www.cs.memphis.edu/~dasgupta
IA center: 
cfia.memphis.edue-mail: dasgupta@memphis.edu

 

Topic 1: Computational Intelligence in Cybersecurity (abstract)

Topic 2: Adversarial Machine Learning and Defense Strategies (abstract)

Topic 3: Adaptive Multi-Factor Authentication & Cyber Identity (abstract)

Topic 4: Advances in Immunological Computation (abstract)

Topic 5: AI vs AI: Viewpoints (abstract)


 

Yiu-ming Cheung (2020-2022)
Professor, Department of Computer Science
Hong Kong Baptist University
email: ymc@comp.hkbu.edu.hk, ymcheung789@gmail.com

 

 

Lecture Topic 1: Can AI be beyond human beings ultimately? (abstract)

Lecture Topic 2: Clustering on Imbalanced Data (abstract)

Lecture Topic 3: Feature Extraction for Incomplete Data via Low-rank Tensor Decomposition with Feature Regularization (abstract)


Hisao Ishibuchi (2021-2023)
Department of Computer Science and Engineering
Southern University of Science and Technology
Shenzhen, China
email: hisao@sustech.edu.cn; hisaoi@cs.osakafu-u.ac.jp

Research Field: Evolutionary Computation, Fuzzy Systems

Lecture Topic 1: Introduction to Evolutionary Multi-Objective Optimization (abstract)

Lecture Topic 2: Fuzzy Rule-Based Classifier Design: Tradeoff between Accuracy and Interpretability (abstract)

Lecture Topic 3: Evolutionary Many-Objective Optimization (abstract)

Lecture Topic 4: Fair Performance Comparison of Evolutionary Multi-Objective Optimization Algorithms (abstract)


Chia-Feng Juang (2020-2022)
Department of Electrical Engineering,
National Chung Hsing University
Taichung, Taiwan, R.O.C.
email: cfjuang@dragon.nchu.edu.tw

Research Field: Data-driven Fuzzy Systems, Evolutionary Robots

Lecture Topic 1: Data-driven Interpretable Fuzzy Systems (abstract)

Lecture Topic 2: Evolutionary Mobile Robots Using Computational Intelligence Techniques (abstract)

Lecture Topic 3: Computational Intelligence and its Applications to Medical Diagnosis Aided Systems (abstract)

 


Sanaz Mostaghim (2020-2022)
Faculty of Computer Science
Otto von Guericke University Magdeburg
Magdeburg, Germany
email: sanaz.mostaghim@ovgu.de

Research Field: Techniques of Computational Intelligence with focus on Multi-Objective Optimization and Decision-Making Algorithms

Lecture Topic 1: Recent Advances in Evolutionary Multi-Objective Optimization (abstract)

Lecture Topic 2: Multi-Criteria Decision-Making Algorithms: From individual to collective autonomous decision-making (abstract)

Lecture Topic 3: Recent Advances in Swarm Intelligence and Swarm Robotics (abstract)


Yi Lu Murphey (2020-2022)
Department of ECE
University of Michigan-Dearborn
Michigan, USA
email: yilu@umich.edu

Research Field: Machine learning and Intelligent Systems, Computer Vision, Pattern Analysis, and Information Technology

Lecture Topic 1: Intelligent Vehicles and Transportation Systems (abstract)

Lecture Topic 2: Personalized Driver Workload Estimation Using Deep Neural Network Learning from Physiological and Vehicle Sign (abstract)

Lecture Topic 3: Optimal Power Management based on Q-Learning and Neuro-Dynamic Programming for Plug-in Hybrid Electric Vehicles (abstract)


Pierre-Yves Oudeyer (2021-2023)
Inria
200 avenue de la vieille tour
33405 Talence, France
email: pierre-yves.oudeyer@inria.fr

Research Field: Artificial intelligence, machine learning, developmental robotics

Lecture Topic 1: Developmental machine learning: Machines that learn like children ... and help children learn better (abstract)

Lecture Topic 2: How baby robots help us understand complex dynamics in development (abstract)

Lecture Topic 3: Intrinsic motivation, curiosity, and learning: Theory and applications in educational technologies (abstract)


Gary G. Yen (2021-2023)
School of Electrical & Computer Engineering
Oklahoma State University
CStillwater, OK 74078, USA
email: gyen@okstate.edu

Research Field: Evolutionary Multiobjective Optimization, Dynamic Optimization, Evolving Deep Neural Networks Architectures

Lecture Topic 1: State-of-the-art evolutionary algorithms for many objective optimization and its real-world applications (abstract)

Lecture Topic 2: Visualization in many-objective optimization (abstract)

Lecture Topic 3: Evolutionary dynamic multiobjective optimization (abstract)

Lecture Topic 4: Evolving deep neural networks architectures (abstract)


Mengjie Zhang (2020-2022)
Evolutionary Computation Research Group
School of Engineering and Computer Science
Wellington Faculty of Engineering
Victoria University of Wellington
P. O. Box 600, Wellington, New Zealand
email: mengjie.zhang@ecs.vuw.ac.nz

Research Field: Evolutionary Computation

Lecture Topic 1: Automated/Evolutionary Deep Learning and Applications to Image Classification (abstract)

Lecture Topic 2: Evolutionary Computation for Feature Selection and Dimensionality Reduction (abstract)

Lecture Topic 3: Overview of Genetic Programming and Applications (abstract)

Lecture Topic 4: EMO Applications to Machine Learning and Combinatorial Optimisation Tasks (abstract)

Lecture Topic 5: Evolutionary Machine Learning (abstract)


Carlos CoelloCarlos A. Coello Coello (2022-2024)
CINVESTAV-IPN, Department of Computer Science, 
Mexico City, MEXICO
email: 
carlos.coellocoello@cinvestav.mx

 

Lecture Topic 1: An Overview of Evolutionary Multi-Objective Optimization (abstract)

Lecture Topic 2: Recent Research Topics in Evolutionary Multiobjective Optimization: A Personal Perspective (abstract)

Lecture Topic 3: Where is the research on evolutionary multi-objective optimization heading to? (abstract)


JiePhotoWebsiteJie Lu (2022-2024) 
University of Technology Sydney 
email: jie.lu@uts.edu.au

 


Lecture
 
Topic 1: Fuzzy Transfer Learning (abstract)

Lecture Topic 2: Concept Drift Detection and Adaptation (abstract)

Lecture Topic 3: Recommender Systems using Computational Intelligence: Methodologies and Applications (for undergraduate students and industries) (abstract)

Lecture Topic 4: Data - Learning - Decision: Innovation and Impact (for undergraduate students and industries)  (abstract)


Nikhil PalNikhil Ranjan Pal (2022-2024) 
Electronics and Communication Sciences Unit
Head, Center for Machine learning and Artificial Intelligence
Indian Statistical Institute
Calcutta 700108, India
email: nrpal59@gmail.com

 Lecture Topic 1: Neural networks with some applications for beginners (For undergraduate students) (abstract)

Lecture Topic 2: Fuzzy systems for dimensionality reduction and manifold learning (abstract)

Lecture Topic 3: Artificial Intelligence Everywhere – how ready are we for it? (abstract)

Lecture Topic 4:  How to make my neural and neuro-fuzzy systems parsimonious?(abstract)


Tingwen Huang

Tingwen Huang (2022 - 2024)
Texas A&M University at Qatar,
Doha, Qatar
email:tingwen.huang@qatar.tamu.edu

 

 Lecture Topic 1: Efficient Computational Approaches and Their Applications (abstract)

Lecture Topic 2: Distributed Consensus of Multi-Agent Systems with or without Attacks (abstract)

Lecture Topic 3: Dynamics of Neural Networks and Their Applications (abstract)


HHussein Abbass (2022 - 2024)
School of Engineering and Information Technology
University of New South Wales,
Canberra, Australia
email: h.abbass@unsw.edu.au
 

 
Lecture Topic 1: Artificial Intelligence: Past, Present and Future (abstract)

Lecture Topic 2: A Proposed Presentation to Undergraduate Students and Industry Analysts Machine Learning for Data Science: An Introduction (abstract)

Lecture Topic 3: Shepherding: Biologically inspired Distributed AI-Enabled Human Swarm Teaming (abstract)

Lecture Topic 4: From Machine Learning to Machine Education (abstract)


UM3

Ujjwal Maulik (2022 - 2024)
Department of Computer Science and Engineering
JADAVPUR UNIVERSITY 
email: ujjwal.maulik@jadavpuruniversity.in, ujjwal_maulik@yahoo.com

 

 
Lecture Topic 1: Artificial Intelligence for Healthcare (abstract)

Lecture Topic 2: Machine Learning and Data Science: Fundamental and Challenges(abstract)

Lecture Topic 3: Computational Intelligence for Computational Biology(abstract)

Lecture Topic 4: Single and Multi-objective Data Clustering (abstract)