Distinguished Lecturers
James C. Bezdek (2019-2021)
Computing and Information Systems
University of Melbourne
Milton, FL, USA
email: jcbezdek@gmail.com
Research Field: Cluster analysis, Visualization, Cluster validity, Streaming clustering
Lecture Topic 1: How big is too big? Clustering in BIG DATA with the Fantastic 4 (abstract)
Lecture Topic 2: Every picture tells a story: Visual Cluster Assessment in Relational Data (abstract)
Lecture Topic 3: Scalar Indices of Cluster Validity; Do you believe the outputs? (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)
Pau-Choo Chung (Julia) (2019-2021)
Department of Electrical Engineering
National Cheng Kung University
Tainan, Taiwan ROC
email: pcchung@ee.ncku.edu.tw
Research Field: Deep Learning Models for Image Analysis, CI for Medical Image Analysis, Adaptive bio-signal analysis
Lecture Topic 1: Convolutional Networks for Medical Image Analysis: Its Past, Future, and Issues (abstract)
Lecture Topic 2: Gait and Balance Analysis for the Elderly Using an Inertial-Sensor-Based Wearable Device (abstract)
Lecture Topic 3: Recent Development of Deep Learning Neural Networks for Image Analysis: An Overview (abstract)
Kalyanmoy Deb (2018-2020)
Michigan State University
428 S. Shaw Lane
East Lansing, Michiagn 48864 USA
phone: +1 517 930 0846
email: kdeb@egr.msu.edu
Research Field: Evolutionary Practical Optimization, Multi-Criterion Optimization, Evolutionary Multi-Level Optimization
Lecture Topic 1: Evolutionary Optimization for Practical Problem Solving (abstract)
Lecture Topic 2: Recent Advances in Evolutionary Multi-Criterion Optimization and Future Studies (abstract)
Lecture Topic 3: Evolutionary Multi-Level Optimization (EMLO) for Hierarchical Problem Solving (abstract)
Saman K. Halgamuge (2019-2021)
Department of Mechanical Engineering
University of Melbourne
Melbourne, Victoria, Australia
email: saman@unimelb.edu.au
Research Field: Computational Intelligence in Energy and Bioinformatics
Lecture Topic 1: An Inclusive Learning Algorithm Framework in an increasingly Networked World of Transducers (abstract)
Lecture Topic 2: Unsupervised Deep Learning meets Bioinformatics and Neural Engineering (abstract)
Lecture Topic 3: Can the Best Optimization Algorithm Please stand up? (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)
Rudolf Kruse (2018-2020)
Otto-von- Guericke University
Magdeburg, Sachsen-Anhalt 39106 Germany
phone: +49-391-67-58706
email: rudolf.kruse@ovgu.de
Research Field: Intelligent Systems: Uncertainty, Imprecision, Learning and Fusion
Lecture Topic 1: Decomposable Models: On Learning, Fusion and Revision (abstract)
Lecture Topic 2: Industrial Applications of Probabilistic Networks (abstract)
Sushmita Mitra (2019-2021)
Machine Intelligence Unit
Indian Statistical Institute
Kolkata 700108, India
email: sushmita@isical.ac.in
Research Field: Hybridization in computational intelligence, Machine learning, Biomedical imaging, Bioinformatics
Lecture Topic 1: Hybridization with Rough Sets: Application to Bioinformatics and Biomedical Imagery (abstract)
Lecture Topic 2: Mining Gene Expressions using Domain Knowledge: Application to Gene Regulation and Evaluation (abstract)
Lecture Topic 3: Intelligent Biomedical Image Analysis (abstract)
Lecture Topic 4: From Learning to Deep Learning (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)
Alice Smith (2018-2020)
Industrial and Systems Engineering and Computer Science and Software Engineering
Auburn University
Auburn, AL 36849
phone: 334 844 1460
email: smithae@auburn.edu
Research Field: Modeling and optimization of complex systems using computational intelligence
Lecture Topic 1: Blast from the Past – Revisiting Evolutionary Strategies for the Design of Engineered Systems (abstract)
Lecture Topic 2: Decision Science Inspired by Nature (abstract)
Lecture Topic 3: Evolutionary Multi-Objective Optimization (abstract)
PN Suganthan (2018-2020)
Electrical and Electronic Engineering
NTU
Nanyang Avenue
Singapore, Singapore 639798
phone: 6567905404
email: epnsugan@ntu.edu.sgepnsugan .a_t. ntu.edu.sg
Research Field: Evolutionary, Swarm, Neural Classification, Neural Forecasting
Lecture Topic 1: Numerical Optimization by Differential Evolution (abstract)
Lecture Topic 2: Non-Iterative Learning Methods for Classification and Forecasting (abstract)
Kay Chen TAN (2019-2021)
Department of Computer Science
City University of Hong Kong
Kowloon Tong, Hong Kong
email: kaytan@cityu.edu.hk
Research Field: Evolutionary Computation
Lecture Topic 1: Evolutionary Multi-objective Optimization (abstract)
Lecture Topic 2: Evolving Deep Neural Networks (abstract)
Lecture Topic 3: Evolutionary Design and Optimization (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)