Deadline Approaching for Nominations for IEEE CIS Awards

The IEEE Computational Intelligence Society (CIS) annually recognizes significant contributions and meritorious service in the field of computational intelligence. Nominations are highly encouraged to recognize our volunteers and eminent colleagues to keep our Society alive and to promote research excellence in computational intelligence.

CIS sponsors several annual Awards. Please see the awards and nomination details on the IEEE CIS Awards.

The IEEE CIS Awards have a deadline of 30 April 2024 (strict deadline).

Mengjie Zhang
Awards Committee Chair

IEEE CIS Call for Nominations for Key Leadership Positions

The IEEE Computational Intelligence Society (CIS) is seeking nominations for the following key leadership positions (terms are in parentheses):

• President-Elect (2025), President (2026-2027)
• Vice President for Education (2025-2026)
• Vice President for Member Activities (2025-2026)
• Vice President for Publications (2025-2026)
• Five ADCOM Members-at-Large (2025-2027)

The nomination will close on 26 April 2024. For more information please visit IEEE CIS Call for Nominations. 

Remembering Jeffrey Horn (1963-2024)

It is with considerable sadness that we inform the Genetic and Evolutionary Computation (GEC) community that Jeffrey Horn, (61) passed away on 5 February 2024 in Negaunee, Michigan. Jeff received his undergraduate degree in Computer Science from Cornell University in 1985 and his Masters and Doctoral degrees from the University of Illinois at Urbana-Champaign in Computer Science in 1997. At Illinois, he was an early member of the Illinois Genetic Algorithms Laboratory (IlliGAL).

At the direction of Prof. David E. Goldberg, IlliGAL’s researchers addressed fundamental and pragmatic issues related to the working of GEC algorithms, which helped shape many leading GEC researchers of repute today. After completing his PhD, Jeff joined the Department of Mathematics and Computer Science at Northern Michigan University in 1996. Students of NMU remember him as a caring teacher and friend.  Read more

IEEE WCCI 2024 Early Bird Registration Ends Today, 15 April!

The IEEE World Congress on Computational Intelligence (IEEE WCCI 2024) is the world’s largest technical event on computational intelligence, featuring the three flagship conferences of the IEEE Computational Intelligence Society (CIS) under one roof:

• The International Joint Conference on Neural Networks (IJCNN)
• The IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
• The IEEE Congress on Evolutionary Computation (IEEE CEC)

IEEE 2024 will be held in Yokohama, Japan from 30 June - 5 July 2024. Register today to save! 

Visit 2024.ieeewcci.org for more information. 

2024 IEEE CAI Early Registration Ends on 25 April

With over 680 papers received from Asia, Europe and the United States, IEEE CAI 2024 promises to be a global hub of innovation, collaboration, and knowledge exchange. Register by 25 April to avail early bird rates!

CAI will host eminent Keynote speakers from academia and industry, Workshops on a wide range of AI topics, and a Doctoral consortium that offers a unique opportunity for doctoral students and recent graduates to interact with experienced researchers specializing in AI.

CAI is sponsored by a number of technology companies and other organizations such as Hewlett Packard Enterprise, AMD, Dell Technologies, National Supercomputing Centre Singapore and Institute of Singapore Chartered Accountants.

For more information, visit: ieeecai.org/2024

Yew-Soon Ong
General co-chair, CAI

Conferences and Deadlines Approaching in April 2024

• The submission deadline for the 2024 IEEE Latin American Conference on Computational Intelligence (IEEE LA-CCI 2024) is 20 April 2024
• The submission deadline for the 2nd International Conference on Cyber-energy Systems and Intelligent Energies (ICCSIE 2024) is 30 April 2024
• The submission deadline for the 2024 IEEE Conference on Computational Intelligence for Financial Engineering and Economics (IEEE CIFEr 2024) is 30 April 2024

IEEE CIS Conference Participation and Travel Grants

CIS is pleased to offer travel grants to support our Society members to attend and present in selected CIS-sponsored conferences. The applications for the following conferences are open or will open soon (please refer to the respective webpages):

• IEEE Conference on Artificial Intelligence (CAI 2024) (Closes on 28 April)

• IEEE World Congress on Computational Intelligence (WCCI 2024) (Closes on 19 April)

• IEEE International Conference on Development and Learning (ICDL 2024) (Closes on 17 April)

• IEEE Conference on Games (CoG 2024)

• IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2024)

For more information visit IEEE CIS Conference Participation and Travel Grants.

Yi Mei
Travel Grant Subcommittee Chair

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

Live CIS Webinar: Multiobjective Bilevel Optimization, Algorithms and Applications

Speaker: Prof. Efrén Mezura-Montes, Artificial Intelligence Research Institute, University of Veracruz, MEXICO
Date and Time: Thursday, 25 April 2024 5:00 PM - 6:00 PM GMT

After a gentle introduction to the multiobjective bilevel optimization (MOBO) problem, considering the optimistic and pessimistic positions, this webinar presents a classification of methods that solve it, considering both exact and approximate approaches. The pros and cons of both options are analyzed and discussed. Moreover, a set of different applications where MOBO has been utilized to model and successfully solve real-world problems is presented. Finally, fertile paths of research are detected. 

Keeley Crockett
Webinars Committee Chair

Missed the last CIS Webinar: Ethical & Societal Implications of AI?

View below

View Archived CIS Webinars on the CIS YouTube Channel

IEEE CIS Welcomes New Chapters

CIS would like to congratulate and welcome the new chapters that were formed in the first quarter of 2024!

• Madanapalle Inst of Tech & Science Computational Intelligence Society Student Branch Chapter - Hyderabad Section
• Inst of Aeronautical Engineering-Hyderabad Computational Intelligence Society Student Branch Chapter - Hyderabad Section
• Vimal Jyothi Engineering College-Kannur Computational Intelligence Society Student Branch Chapter - Kerala Section
• IEEE Kenya Section Computational Intelligence, Antennas and Propagation & Vehicular Technology Joint Societies Joint Chapter
• Kalyani Government Engineering College Computational Intelligence Society Student Branch Chapter - Kolkata Section
• IEEE Guadalajara Section Computational Intelligence Society Chapter
• International Multidisciplinary School Computational Intelligence Society Student Branch Chapter - Tunisia Section
• Narula Institute of Technology Computational Intelligence Society Student Branch Chapter - Kolkata Section

For more information on our Chapters and Chapter leadership contacts, click here.

Meet a CIS Member: Fangfang Zhang

Meet:  Fangfang Zhang, Vice Chair of CIS Task Force on Evolutionary Scheduling and Combinatorial Optimisation

What is your title, and place of work? (or Technical Field of Research)?

I am a lecturer with the Centre for Data Science and Artificial Intelligence & School of Engineering and Computer Science, Victoria University of Wellington (VUW), Wellington, New Zealand. Read More

2024 Call for Summer School Proposals

The IEEE Computational Intelligence Society (CIS) is pleased to offer funding to support the organization of summer schools in the field of computational intelligence. Funding is available to partially cover the costs of tuition, accommodation, and other expenses associated with running a summer school.

The deadline for submitting proposals is 30 April 2024. Please visit IEEE Summer Schools for more information. 

Chun-Rong Huang
Summer Schools Subcommittee Chair

• IEEE TCDS Special Issue on Neuro-Inspired Learning for Robotics (1 May 2024)
• IEEE TCDS Special Issue on Embodied AI in Indoor Robotics: Bridging Perception, Interaction, and Autonomy (31 May 2024)
• IEEE CIM Special Issue on Advancing Computational Intelligence in Autonomous Learning and Optimization Systems (1 July 2024)
• IEEE TEVC Special Issue on Evolutionary Bilevel Optimization (1 August 2024)
• IEEE TEVC Special Issue on Evolutionary Dynamic Optimization (1 September 2024)
• IEEE TCDS Special Issue on Bridging the Gap between Machine and Brain in Speech Processing (30 September 2024)

SPAIC: A Spike-Based Artificial Intelligence Computing Framework

Neuromorphic computing is an emerging research field that aims to develop new intelligent systems by integrating theories and technologies from multiple disciplines, such as neuroscience, deep learning and microelectronics. Various software frameworks have been developed for related fields, but an efficient framework dedicated to spike-based computing models and algorithms is lacking. Read more

IEEE Computational Intelligence Magazine, February 2024

Evolutionary Multiform Optimization With Two-Stage Bidirectional Knowledge Transfer Strategy for Point Cloud Registration

Point cloud registration is an important task in computer vision, where the goal is to estimate a transformation to align a pair of point clouds. Most of the existing registration methods face the problems of poor robustness and getting stuck in local optima. Evolutionary multitasking is an effective paradigm to enhance global search capability and improve convergence characteristics through knowledge transfer across multiple related tasks. Read more

IEEE Transactions on Evolutionary Computation, February 2024

Fuzzy Centered Explainable Network for Reinforcement Learning

The explainability of reinforcement learning (RL) models has received vast amount of interest as its applications have widened. Most existing explainable RL models focus on improving the explainability of an agent's observations instead of the relationships between agent states and actions. This study presents a fuzzy centered explainable network (FCEN) for RL tasks to interpret the relationships between agent states and actions. The proposed FCEN leverages the interpretability of fuzzy neural networks to establish if–then rules and a generative model to visualize learned knowledge. Read more

IEEE Transactions on Fuzzy Systems, January 2024

Bayesian Proper Orthogonal Decomposition for Learnable Reduced-Order Models With Uncertainty Quantification

Designing and/or controlling complex systems in science and engineering relies on appropriate mathematical modeling of systems dynamics. Classical differential equation-based solutions in applied/computational mathematics are often computationally demanding. Recently, the connection between reduced-order models of high-dimensional differential equation systems and surrogate machine learning models has been explored. Read more

IEEE Transactions on Transactions on Artificial Intelligence, March 2024

Hierarchical Multivariate Representation Learning for Face Sketch Recognition

Face Sketch Recognition (FSR) is extremely challenging because of the heterogeneous gap between sketches and images. Relying on the ability to generative models, prior generation-based works have dominated FSR for a long time by decomposing FSR into two steps, namely, heterogeneous data synthesis and homogeneous data matching. However, decomposing FSR into two steps introduces noise and uncertainty, and the first step, heterogeneous data synthesis, is an even general and challenging problem. Read more

IEEE Transactions Emerging Topics in Computational Intelligence, April 2024

Reinforcement Learning Control With Knowledge Shaping

We aim at creating a transfer reinforcement learning framework that allows the design of learning controllers to leverage prior knowledge extracted from previously learned tasks and previous data to improve the learning performance of new tasks. Toward this goal, we formalize knowledge transfer by expressing knowledge in the value function in our problem construct, which is referred to as reinforcement learning with knowledge shaping (RL-KS). Read more

IEEE Transactions on Neural Networks and Learning Systems, March 2024

Automated Gameplay Testing and Validation With Curiosity-Conditioned Proximal Trajectories

This article proposes a novel deep reinforcement learning algorithm to perform automated analysis and detection of gameplay issues in complex 3-D navigation environments. The curiosity-conditioned proximal trajectories (CCPT) method combines curiosity and imitation learning to train agents that methodically explore in the proximity of known trajectories derived from expert demonstrations. We show how our new algorithm can explore complex environments, discovering gameplay issues, and design oversights in the process, and recognize and highlight them directly to game designers. Read more

IEEE Transactions on Games, March 2024

Learning Skills From Demonstrations: A Trend From Motion Primitives to Experience Abstraction

The uses of robots are changing from static environments in factories to encompass novel concepts such as human–robot collaboration in unstructured settings. Preprogramming all the functionalities for robots becomes impractical, and hence, robots need to learn how to react to new events autonomously, just like humans. However, humans, unlike machines, are naturally skilled in responding to unexpected circumstances based on either experiences or observations. Hence, embedding such anthropoid behaviors into robots entails the development of neuro-cognitive models that emulate motor skills under a robot learning paradigm. Read more

IEEE Transactions Cognitive and Developmental Systems, February 2024

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