The 2023 IEEE Symposium Series on Computational Intelligence (SSCI 2023) is a flagship annual meeting organized by the IEEE Computational Intelligence Society. It serves as a primary forum for multidisciplinary research in computational intelligence. SSCI 2023 will be held in Mexico City from 5-8 December 2023.

Paper Submissions: 30 June 2023
Paper Acceptance: 31 August 2023

For more information visit SSCI 2023 Call for Papers.

2023 IEEE CAI Registration is Open

The IEEE Conference on Artificial Intelligence (IEEE CAI) will take place in Santa Clara, CA, USA on 5-6 June 2023. This new conference series emphasizes AI applications in specific verticals that impact industrial technology and innovation. Key verticals include Energy, Healthcare and Life Science, Transportation and Aerospace, Earth Systems Decision Support, Industrial AI, and Ethical and Societal Implications of AI.

IEEE CAI registration is now open. Early Bird registrations ends 8 May 2023. 

IEEE CEC 2023 Registration is Open

IEEE CEC 2023 is a world-class conference that brings together researchers and practitioners in the field of evolutionary computation and computational intelligence from around the globe. The conference program includes plenary lectures, regular and special sessions, tutorials, competitions, workshops and panel discussions. The CEC 2023 will be held at the Swissôtel Chicago, 1-5 July 2023

For more information on registration for IEEE CEC 2023 please visit here.

The annual IEEE Conference on Games (IEEE CoG) seeks to be the premier venue for technical, scientific, and engineering work on video games, board games, and other types of games. Games offer a fantastic domain for computational creativity, game design, technology, education, social sciences and, undoubtedly, artificial and computational intelligence. IEEE CoG is a venue to discuss recent advances and explore future directions.

IEEE CoG 2023 will take place at Northeastern University, which is located in Boston in the United States on 21 - 24 August 2023. For early bird registration information (until 1 July) please visit the website. 

The IEEE Computational Intelligence Society sponsors many conferences each year with varying levels of financial sponsorship. We are currently looking for proposals for the 2026 World Congress on Computational Intelligence (WCCI 2026). WCCI combines the Society’s flagship conferences for evolutionary computation and fuzzy systems with the International Joint Conference on Neural Networks. IEEE WCCI 2024 will be held in Japan, we hope that some bids from other geographical will be submitted.

Proposals for the IEEE WCCI 2026 conference proposals should be submitted by 30 June 2023 (hard deadlines) to provide sufficient time for review and decision by IEEE CIS Confcom and Adcom. Please inform VP Conferences Marley Vellasco ([email protected]) and Steven Corns ([email protected]) as Chair of the Confcom Subcommittee on Future Conferences of your intention to provide a proposal or if you would like further information. The process for generating such a proposal can be found on our website.

Wiley-IEEE Press invites nominations for two book awards to recognize the authors of an outstanding textbook and an outstanding professional book published by Wiley-IEEE Press. Submission of Nominations Nominations may be submitted via our nominations site. The deadline is no later than 5 May 2023.

For information on how to nominate, visit our website. Any questions should be directed to [email protected].

Please note that only IEEE members can submit a nomination.

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. This year we have 19 lecturers in various CIS sub-fields. 

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. For more details on the  process of organizing distinguished lectures please click here.

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

Please visit the Distinguished Lectureres Program for more information. 

We are currently soliciting bid proposals to host the future International Conference on Data Science and Advanced Analytics (DSAA’2024 and DSAA’2025). DSAA is the only data science event that is jointly sponsored by IEEE, ACM, and ASA. DSAA has firmly established itself as the premier forum in the area of data science, big data, advanced analytics, statistics, and machine learning for industry, government, and academic participants. This is ensured by such features as a very competitive acceptance rate (about 10%) for regular papers, high-profile core function chairs, 10 pages in IEEE double-column format by double-blind review, and interdisciplinary and cross-domain engagement from statistics, industry, and government.

More information on DSAA and the call for bids is available here.

The IEEE History Committee carries out IEEE Milestone Program, in which it recognizes scientific and technological achievements of historical value. The recognition is approved by the IEEE Board of Directors. In order to be considered, an achievement must be at least 25 years old. This year such a recognition was given to an achievement reported by a CIS member, Stevo Bozinovski. The achievement is entitled "First control of movement of a physical object using signals emanating from a human brain, 1988." The 1988 demonstration experiment showed a robot moving along a closed line drawn on a floor, controlled by a human EEG move/stop commands.

According to the information given by Bozinovski, the significance of this event for IEEE CIS is that it points to a way by which various states of the brain (relaxation, alertness, readiness, expectation, learning, intention, etc) can be used to control various machines (robots, prostheses wheelchairs, exoskeletons, etc). Also it was established a relation between two previously distant areas of research, robotics and EEG signals. A lasting challenge of engineering solution of the psychokinesis problem was solved in this way. It is also noticeable that this event was significantly ahead of time: the second control of a robot using brain signals was achieved 11 years later, in 1999, by a team of Nicolelis at Duke University. In this 1988 work for the first time a machine learning algorithm was used in a brain-computer interface research. That machine learning algorithm made possible an IEEE Milestone event, first control of movement of a robot using brain signals.

For more information please visit the Milestone Proposal page for the First control of movement of a physical object using signals emanating from a human brain, 1988.

Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges

Artificial Intelligence (AI) is a fast-growing research and development (R&D) discipline which is attracting increasing attention because it promises to bring vast benefits for consumers and businesses, with considerable benefits promised in productivity growth and innovation. To date, significant accomplishments have been reported in many areas that have been deemed challenging for machines, ranging from computer vision, natural language processing, audio analysis to smart sensing and many others. The technology trend in realizing success has developed towards increasingly complex and large-size AI models to solve more complex problems at superior performance and robustness. This rapid progress, however, has taken place at the expense of substantial environmental costs and resources. Read More

IEEE Computational Intelligence Magazine, May 2023

A Survey on Brain Effective Connectivity Network Learning

Human brain effective connectivity characterizes the causal effects of neural activities among different brain regions. Studies of brain effective connectivity networks (ECNs) for different populations contribute significantly to the understanding of the pathological mechanism associated with neuropsychiatric diseases and facilitate finding new brain network imaging markers for the early diagnosis and evaluation for the treatment of cerebral diseases. Read More

IEEE Transactions on Neural Networks and Learning Systems, April 2023

Random Feature-Based Collaborative Kernel Fuzzy Clustering for Distributed Peer-to-Peer Networks

Kernel clustering has the ability to get the inherent nonlinear structure of the data. But the high computational complexity and the unknown representation of the kernel space make it unavailable for the data clustering in distributed peer-to-peer (P2P) networks. To solve this issue, we propose a new series of random feature-based collaborative kernel clustering algorithms in this article. In the most basic algorithm, each node in a distributed P2P network first maps its data into a low-dimensional random feature space with the approximation of the given kernel by using the random Fourier feature mapping method. Read more

IEEE Transactions on Fuzzy Systems, February 2023

A Multiobjective Multitask Optimization Algorithm Using Transfer Rank

Multiobjective multitask optimization (MMO) attempts to solve several problems simultaneously. This is commonly done by identifying useful knowledge to transfer between tasks, thereby producing optimal solutions more quickly. In this study, an MMO algorithm using transfer rank and a KNN model is proposed to achieve this goal. The definition of transfer rank is first introduced for quantifying the priority of transfer solutions, to improve the probability of a positive result. Read More

IEEE Transactions on Evolutionary Computation, April 2023

Genetic-WFC: Extending Wave Function Collapse With Genetic Search

This article presents genetic wave function collapse (WFC), a procedural level generation algorithm that mixes genetic optimization with WFC, a local adjacency constraints propagation algorithm. We use a synthetic player to evaluate the novelty, safety, and complexity of the generated levels. Novelty is maximized when the synthetic player goes on tiles not visited for a long time, safety is related to how far it can see, and complexity evaluates the variability of the surrounding tiles. Read More

IEEE Transactions on Games, March 2023

Collision-Free Navigation in Human-Following Task Using a Cognitive Robotic System on Differential Drive Vehicles

As human–robot collaboration increases tremendously in real-world applications, a fully autonomous and reliable mobile robot for the collaboration has been a central research topic and investigated extensively in a large number of studies. One of the most pressing issues in such topic is the collision-free navigation that has a moving goal and unknown obstacles under the unstructured environment. In this article, a cognitive robotic system (CRS) is proposed for the robot to navigate itself to the moving target person without obstacle collision. Read More

IEEE Transactions on Cognitive and Developmental Systems, March 2023

Multi-view Point Cloud Registration based on Evolutionary Multitasking with Bi-Channel Knowledge Sharing Mechanism

Multi-view point cloud registration is fundamental in 3D reconstruction. Since there are close connections between point clouds captured from different viewpoints, registration performance can be enhanced if these connections be harnessed properly. Therefore, this article models the registration problem as multi-task optimization, and proposes a novel bi-channel knowledge sharing mechanism for effective and efficient problem solving. Read More

IEEE Transactions on Emerging Topics in Computational Intelligence, April 2023

• IEEE CIM Special issue on Data-Driven Learning For Autonomous Driving (31 May 2023)
• IEEE TNNLS Special issue on Trustworthy Federated Learning (1 June 2023)
• IEEE TAI Special Issue on AutoML for Non-Stationary Data (2 June 2023)
• IEEE TEVC Special Issue on Evolutionary Neural Architecture Search (30 June 2023)
• IEEE TNNLS Special Issue on Graph Learning (1 July 2023)
• IEEE TETCI Special Issue on Computational Intelligence in Mental Health (1 July 2023)
• IEEE TETCI Special Issue on Data and Knowledge-assisted Evolutionary Computation (31 July 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 Fuzzy-Deep Neural Network Learning in Sentiment Analysis (15 January 2024)