- Submissions Due: 1 September 2022
- Preliminary Notification: 2 December 2022
- Revisions Due: 6 January 2023
- Final Versions Due: (Tentative) February 2023
Publication: March/April 2023
Artificial intelligence (AI) is now pervasive in several areas, offering significant benefits. Machine learning (ML) and deep learning (DL) techniques enable machines to analyze a large volume of data, learn, offer recommendations, and make decisions. However, the present AI and ML models are limited to solving specific problems in a narrow domain and present major limitations and concerns.
We look forward to next-gen AI that features better capabilities and addresses current AI limitations and concerns. To realize next-gen AI, researchers and developers are working on several areas: enhanced explainability; improved trust, and reliability; new AI paradigms such as federated learning, bio-inspired AI models, neuro-symbolic AI, and quantum AI; specialized AI hardware, software, and data models; enriched AI-human collaboration (collaborative intelligence) and attempts to move closer to artificial general intelligence (AGI), to name a few. The next-generation AI would be more capable, more exciting, and also more challenging.
This special issue will examine next-generation AI advances and applications that will shape the future.
We solicit high-quality feature articles on the following and other related topics for this issue. Besides research articles, we also welcome tutorials, experience reports, and case studies on next-gen AI.
Topics of Coverage:
- Biologically inspired AI models
- Neuromorphic computing
- Spiking neuron models
- Explainable AI
- Human-level AI
- Generative AI
- Quantum AI
- Distributed DL models
- Federated learning
- Human-AI collaboration and human-centered AI
- Hardware AI accelerators
- AI and learning from multimodal data
- Security of AI
- Trustworthy AI
- Ethical considerations in AI
- AI regulation
- AI for cybersecurity
- AI in speech and natural language processing
- Computer vision
- Robotics and autonomous systems
- Neuro-symbolic AI
- Next-gen AI applications (in digital twins, industry, healthcare, automotive, financial services, manufacturing, agriculture, and other areas)
For author information and guidelines on submission criteria, please visit IT Professional‘s Author Information page. Please submit papers through the ScholarOne system, and be sure to select the special-issue name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal.
Please contact the guest editors at email@example.com.
- Aswani Kumar Cherukuri, Vellore Institute of Technology, India
- San Murugesan, BRITE Professional Services, Australia
- Lia Morra, Politecnico di Torino, Italy
- Darshika G. Perera, University of Colorado, Colorado Springs, USA