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Special Sessions

CIIS proposals for special sessions within the technical scope of the conference. Special sessions supplement the regular program of the conference and provide a sample of the state-of-the-art research in both academia and industry in special, novel, challenging, and emerging topics.

Special-session proposals should be submitted by the prospective organizer(s) who will commit to promoting and handling the review process of special session as Chair or Co-Chair of the event. Accepted papers will be published by conference proceedings, inclusion to indexing databases.

Proposals should include the following information:

  • Title

  • Brief descrition of the session

  • Related topics

  • Name, brief biodata and photo of organizer

  • E-mail address of main contact person

  • Please send these information to mail address ciis_info@sciei.org

Special Session I: Biologically Inspired Machine Learning-Theory and Applications

This special session is intended for like-minded researchers to present and discuss their latest research in Bio-Inspired Machine Learning (ML) without a restriction on an application domain. Bio-Inspired ML is a family of machine learning approaches that are primarily derived from the learning mechanisms of biological entities. Examples of such approaches are Artificial Immune Systems (inspired by the biological immune system), Artificial Neural Networks (inspired by biological neural networks), Reinforcement Learning (inspired by biological learning mechanisms) and the use of meta-heuristic approaches to optimise learning algorithms. Therefore, papers can range from theoretical concepts of Bio-Inspired ML to the application of Bio-Inspired ML to various domains, such as Computer Vision, Natural Language Understanding, Audio, Representation Learning, Generative Modelling and so forth.

We invite submissions presenting new and original research on topics including, but not limited to, the following.

  • Artificial Immune Systems (e.g. dendritic cell algorithm, clonal selection, negative selection)

  • Artificial Immune Networks (e.g. aiNet, fractal immune networks, fuzzy immune networks)

  • Neural Network Architectures and Applications (e.g. spiking neural networks, neuroevolution, Hopfield networks, deep neural networks)

  • Neuromorphic Computing Applications (e.g. vision, anomaly detection, gaming)

  • Reinforcement Learning (e.g. deep Q-networks, proximal policy optimisation, model-based deep RL)

  • Bio-Inspired Representation Learning (e.g. self-organising maps, autoencoders, energy-based models)

  • Bio-Inspired Learning Agents (e.g. multi-agent RL)

  • Bio-Inspired Multimodal Learning (e.g. attention mechanisms, embodied AI, contrastive learning)

  • Bio-Inspired Generative Models (e.g. GANs, VAEs)

  • Meta-Heuristic Approaches for Optimising Machine Learning Models (i.e. Neuroevolution, swarm optimisation, gene expression programming)

Organizer:

Dr. Siphesihle Sithungu, University of Johannesburg, South Africa (Email: siphesihles@uj.ac.za)

Dr. Siphesihle Sithungu is a Senior Lecturer at the Academy of Computer Science and Software Engineering at the University of Johannesburg, South Africa. He is also a professional member of BCS – The Chartered Institute for IT and the International Federation for Information Processing (IFIP) Working Group 12.9 (Computational Intelligence). Dr. Sithungu’s research interest is on Biologically Inspired Artificial Intelligence (AI), Generative AI and Critical Infrastructure Protection. His research has been published in over 20 peer-reviewed international conferences and journals and has received over 85 citations. He has participated and presented at the BRICS Young Scientists Forum and has given multiple talks and panel discussions in AI and cybersecurity-related workshops. He has been a member of the technical committee and a reviewer for the CIIS conference for 6 years, as well as a reviewer for several other international conferences.

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