IEEE CIS Officer Announcements 

We are please to announce the following IEEE CIS Vice Presidents who were appointed at the CIS Adcom meeting on 4 June 2023: 

The Annual IEEE International Conference on Fuzzy Systems, well known as FUZZ-IEEE, is one of the premier international conferences in the field of fuzzy sets and systems.

Join us in Songdo Incheon, Korea from 13-17 August 2023.

We have an incredible lineup of keynote speakers you won't want to miss!

• Dr. Hao Ying, Wayne State University, USA
• Jerry Mendel, Emeritus Professor of Electrical Engineering, University of Southern California
• Sanghamitra Bandyopadhyay, Indian Statistical Institute

Registration is open! Click here to register: https://fuzz-ieee.org/ registration

For more information on our keynote speakers, please visit: https://fuzz-ieee.org/keynotes

The IEEE CIS Distinguished Lecturer Program (DLP) aims at serving the Computational Intelligence community by providing stimulating lectures given by distinguished IEEE CIS professionals and scholars. It also aims at helping young researchers (masters and doctoral students) providing suggestions/guidance on their research problems as well as promoting computational intelligence tools and techniques among undergraduate students to make them interested in CIS fields of interest. Distinguished Lecturers present novel basic and/or applied research results in their CIS sub-field. Their lectures offer insights into the trends and challenges of their CIS sub-field and their vision for the given sub-field. In any given year, selected IEEE CIS Distinguished Lecturers (DLs) have a balanced representation of CIS sub-fields and include representatives from academia, industry and government while spanning different IEEE regions. The program supports local CIS Chapters by enabling a major chapter event which can considerably improve a chapter’s visibility to their existing IEEE CIS members, other IEEE society members and the wider CIS community in their area. It is expected that DLP events actively seek to recruit new CIS professionals to both the CIS field and to IEEE CIS.

It should be noted that this program is NOT intended as a means to finance speakers for conferences/workshops or symposia.

Please visit Organizing Distinguished Lectures for more information. 

The committee shall evaluate the relevant values and merits of each nominee using both qualitative and quantitative evidence. The quantitative measures indicated in section III.1 are part of the input to be considered by the committee. Other criteria include, but are not limited to, qualitative assessments of the nominees work, geographical lecturer distribution requirements, or the need to include lecture topics that would not be, otherwise, well represented. The committee may consider exceptions to these criteria on a case by case basis.

Deadline: 30 August 2023

For more information please visit Nominatiing and Appointing DLs.

2024 IEEE CIS Student Grand Competition on Computational Intelligence in Biomedicine and Healthcare

We welcome participants to present computational intelligence solutions for core issues in smart medicine, smart healthcare, and smart hospital including but not limited to personalized, predictive, preventive, and participatory medicine and healthcare solutions. In the preliminary contest, the judge committee will select 10 teams based on the uploaded proposals. In the final contest, the selected teams need to physically or virtually attend the 2024 IEEE World Congress on Computational Intelligence (WCCI) in Japan for real-time demonstration and presentation of their systems.

Prize per team:

• 1st Place Award: US$1,500 + Certificate
• 2nd Place Award: US$1,000 + Certificate
• 3rd Place Award: US$600 + Certificate
• Honorable Mention: Certificate

Website: https://sites.google.com/view/cishackathon

Submission Due: 31 October 2023

Preliminary Contest: 3 January 2024

Final Contest: 1 July 2024

Evolutionary Multi-Objective Optimization in Searching for Various Antimicrobial Peptides

Antimicrobial peptides (AMPs), which are parts of the innate immune response found among all classes of life, are promising in broad-spectrum antibiotics and drug-resistant infection treatments. Although AMPs effectively kill bacteria, numerous AMPs widely distributed in the sequence space remain unknown to humans. Therefore, the de novo design of AMPs involves the exploration of vast sequence space to identify peptides with high antimicrobial activity and good diversity among the known AMPs. Computational intelligence approaches have successfully identified some AMPs; however, most of them fail to address the diversity of the obtained AMPs. Read More

IEEE Computational Intelligence Magazine, May 2023

Improving the Accuracy of Spiking Neural Networks for Radar Gesture Recognition Through Preprocessing

Event-based neural networks are currently being explored as efficient solutions for performing AI tasks at the extreme edge. To fully exploit their potential, event-based neural networks coupled to adequate preprocessing must be investigated. Within this context, we demonstrate a 4-b-weight spiking neural network (SNN) for radar gesture recognition, achieving a state-of-the-art 93% accuracy within only four processing time steps while using only one convolutional layer and two fully connected layers. This solution consumes very little energy and area if implemented in event-based hardware, which makes it suited for embedded extreme-edge applications. Read More

IEEE Transactions on Neural Networks and Learning Systems, June 2023

Fuzzy Clustering With Knowledge Extraction and Granulation

Knowledge-based clustering algorithms can improve traditional clustering models by introducing domain knowledge to identify the underlying data structure. While there have been several approaches to clustering with the guidance of knowledge tidbits, most of them mainly focus on numeric knowledge without considering the uncertain nature of information. To capture the uncertainty of information, pure numeric knowledge tidbits are expanded to knowledge granules in this article. Then, two questions arise: how to obtain granular knowledge and how to use those knowledge granules in clustering. To the end, a novel knowledge extraction and granulation (KEG) method and a granular knowledge-based fuzzy clustering model are proposed in this study.  Read more

IEEE Transactions on Fuzzy Systems, April 2023

Learning Adaptive Differential Evolution by Natural Evolution Strategies

Adaptive parameter control is critical in the design and application of evolutionary algorithm (EA), so does in differential evolution. In the past decade, many adaptive evolutionary algorithms have been proposed, in which online information collected until current generation during the evolutionary search procedure is used to determine the algorithmic parameters for the next generation. Recent studies often assume that the algorithmic parameters follow some distributions, while the distributions' parameters (called hyper-parameters) are updated by the collected information. Performances of these adaptive EAs depend highly on the hyper-parameters. Read More

IEEE Transactions on Emerging Topics in Computational Intelligence, June 2023

Cooperative Coevolutionary CMA-ES With Landscape-Aware Grouping in Noisy Environments

Many real-world optimization tasks suffer from noise. So far, the research on noise-tolerant optimization algorithms is still restricted to low-dimensional problems with less than 100 decision variables. In reality, many problems are high dimensional. Cooperative coevolutionary (CC) algorithms based on a divide-and-conquer strategy are promising in solving complex high-dimensional problems. However, noisy fitness evaluations pose a challenge in problem decomposition for CC. The state-of-the-art grouping methods, such as differential grouping (DG) and recursive DG, are unable to work properly in noisy environments. Because it is impossible to distinguish whether the change of one variable’s difference value is caused by noise or the perturbation of its interacting variables.Read More

IEEE Transactions on Evolutionary Computation, June 2023

Games for Change—A Comparative Systematic Review of Persuasive Strategies in Games for Behavior Change

Games for change is a growing research field and studies have shown that these games can promote positive behavior change using various persuasive strategies. This article presents a systematic review of 130 persuasive games from the literature published in the last 21 years (2001–2021) to 1) highlight the current trends in the field with respect to domains, year, country, technology platforms, and genre; 2) identify what strategies are employed in the games and their comparative analysis across domains; 3) uncover various ways the persuasive strategies are operationalized in games; 4) explore for possible relationships between persuasive games effectiveness and the number of strategies employed Read More

IEEE Transactions on Games, June 2023

A Reinforcement Learning System for Generating Instantaneous Quality Random Sequences

Random numbers are essential to most computer applications. Still, producing high-quality random sequences is a big challenge. Inspired by the success of artificial neural networks and reinforcement learning, we propose a novel and effective end-to-end learning system to generate pseudorandom sequences that operates under the upside-down reinforcement learning framework. It is based on manipulating the generalized information entropy metric to derive commands that instantaneously guide the agent toward the optimal random behavior. Using a wide range of evaluation tests, the proposed approach is compared against three state-of-the-art accredited pseudorandom number generators (PRNGs). Read More

IEEE Transactions on Artificial Intelligence, June 2023

• IEEE TAI Special Issue on Conversational AI (30 July 2023)

• IEEE TETCI Special Issue on Data and Knowledge-assisted Evolutionary Computation (31 July 2023)

• IEEE ToG Special Issue on Human-Centred AI in Game Evaluation (1 October 2023)

• IEEE TAI Special Issue on Responsible AI Engineering (1 October 2023)

• IEEE TFS Special Issue on Fuzzy Systems Toward Human-Inspired Computational Intelligence in Complex Systems (31 October 2023)

• IEEE TFS Special Issue on Smart Fuzzy Optimization in Sustainable Manufacturing and Supply Chain Management (1 November 2023)

• IEEE TFS Special Issue on Advances in fuzzy deep learning algorithms for biomedical data (1 December 2023)

• IEEE TETCI Special Issue on Quantum Computing meets Computational Intelligence: A New Vision for Smart Systems (20 December 2023)

• IEEE TFS Special Issue on Deep Neuro-Fuzzy Approaches for Intelligent Big Data Processing (30 December 2023)

• IEEE TETCI Special Issue on Advances in Methodologies for Metaheuristic Algorithms (31 December 2023)

• IEEE TFS Special Issue on Fuzzy-Deep Neural Network Learning in Sentiment Analysis (15 January 2024)

IEEE CIS sponsors and co-sponsors a number of conferences across the globe.