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.

Related Topics

  • 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)


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

Dr.Siphesihle Sithungu received his PhD in Computer Science, with a focus on Bio-Inspired Generative Modelling, at the University of Johannesburg, South Africa, in 2024. He is currently a Lecturer at the Academy of Computer Science and Software Engineering at the University of Johannesburg, where he teaches Data Structures, Object Orientated Programming, Critical Information Infrastructure Protection and Advanced Artificial Intelligence (AI). His research interest is on the applications of AI to optimise complex systems, with a specific focus on Biologically Inspired Artificial Intelligence, Multi-Agent Systems, Generative Modelling and Critical Infrastructures. His research has been published in 18 peer-reviewed international conferences and journals and has received over 45 citations. He was part of the BRICS Young Scientists Conclave in 2021 where he discussed his PhD research and gave multiple talks in workshops organised by a government agency in South Africa, where he also served as a panel member. He has been a member of the technical committee and a reviewer for the CIIS conference for 5 years.

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Special Session II: Artificial Intelligence and Its Application

Artificial intelligence (AI) is essentially the field of computer science focused on creating intelligent machines. This session would likely explore how AI works, its different capabilities, and the many ways AI is being applied in various fields such as healthcare, business, education and entertainment. Among the main topics covered in this session are: (a) the use of AI to automate a variety of tasks, from tedious labor to intricate data analysis; (b) the use of AI to enable machines to learn from data without explicit programming; (c) machine learning algorithms utilized in applications ranging from spam filtering to facial recognition software; and (d) the focus of AI on the understanding and production of human language by computers.

Topics of interest include, but are not limited to:

  • Natural language processing

  • Deep learning

  • Learning Reinforcement

  • Computer Vision

  • Crowdsourcing and Human Computation

  • Algorithmic game theory

  • AI in IoT

  • AI in cybersecurity

  • AI in Education

  • Large scale machine learning

  • Neural networks

  • Pattern recognition

  • Speech recognition

  • Mathematical modelling

  • Ethics in AI


Dr. Eric Blancaflor, Mapua University, Philippines ( Email: ebblancaflor@mapua.edu.ph)

Dr. Eric Blancaflor is a Professor at Mapua University, Philippines. He earned a Bachelor of Science in Electronics Engineering from Mapua University in 1999, a Master's in Engineering major in Computer Engineering from the University of the City of Manila in 2005, and a Doctor of Technology from Technological University of the Philippines in 2021. His research interests cover Cybersecurity, Network and Systems Administration, Web and Mobile Development, Artificial Intelligence, and the Internet of Things. Dr. Blancaflor has published over ninety-three (93) full paper articles in Scopus-indexed international conferences and journals. His relevant IT certifications include Cisco Certified Networking Professional Enterprise, Cisco Certified Specialist Enterprise Advanced Infrastructure Implementation, Cisco Certified Specialist Enterprise core, Cisco Certified Network Associate CCNA, CompTIA Security + SY-601, and EC-Council Certified Security Specialist ECSS. He is an associate member of the National Research Council of the Philippines

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