PAPER SUBMISSION INSTRUCTIONS  [FOR REVIEW MANUSCRIPT]

• Prospective authors are invited to submit manuscripts reporting original unpublished research and recent developments in the topics related to the conference.
• It is required that the manuscript follows the standard IEEE camera-ready format (IEEE standard format, double column, 10-point font). Review Submissions must include only title, abstract, keywords but exclude the author and affiliation with an email address. Papers should be according to the Double blind review format. Please double-check the paper size in your page setup to make sure you are using the letter-size paper layout (8.5 inch X 11 inch). The paper should not contain page numbers or any special headers or footers.
• In order to achieve the same appearance for all manuscripts, UEMCON requires the usage of the IEEE templates in Microsoft Word (US Letter) and LaTeX format can be found at  IEEE Manuscript Templates for Conference Proceedings.
• UEMCON conducts a plagiarism check on all submitted papers. Plagiarism and self-plagiarism apply to all works.

Paper Categories

• Regular Paper – 7 pages maximum (3 additional pages allowed but at an extra charge)
• Short Paper (Work-in-Progress) – 6 pages maximum (2 additional pages allowed but at an extra charge)

Regular papers should present novel perspectives within the general scope of the conference. Short papers (Work-in-Progress) are an opportunity to present preliminary or interim results. 

Topics and technical areas of interest include but are not limited to the following:

Part I: Artificial Intelligence & ML

1. Core AI Algorithms & Deep Learning Foundations
Algorithmic Frameworks: Applied Machine Learning, fundamental AI algorithms, and optimization modeling.
Neural Architectures: Deep AI Learning, neural networks, and embedded neural networks for real-time analytics.

2. Next-Gen Foundation Models & Multimodal AI
Advanced Modeling: Next-gen foundation models and multimodal AI architectures, Natural Language & Interaction.
Next-generation AI paradigms and emerging intelligent technologies.

3. Edge AI & Distributed Intelligence
Decentralized Learning: Federated learning in ubiquitous networks.
Behavioral AI: AI for human behavior prediction, context-aware adaptation, and real-time analytics.
Distributed Systems: Intelligent edge nodes and distributed learning architectures.

4. Applied AI, Governance, and Responsible Deployment (Integrated Track)
Healthcare & Life Sciences: AI in Biomedicine, clinical healthcare systems, and Bioinformatics.
Physical & Environmental Sciences: AI for photonics/optical computing, and AI in Climate Change mitigation.
Socio-Educational Systems: Smart scheduling/optimization, and AI in Education.
Safety & Alignment: AI alignment, safety protocols, and model interpretability.

Part II: Advanced Computing, IoT, & Systems

1. IoT Architecture, Protocols, & Security
System : IoT System Architecture, IoT enabling technologies, and basic IoT Architectures & Protocols.
Networking & Transport: IoT Protocols and Transports.
System Integrity: Hardware-level and network-level Security for IoT.

2. Ubiquitous & Pervasive Computing
Ambient Environments: Ubiquitous and Pervasive Computing Systems, context-aware systems.
Infrastructure: Middleware for pervasive systems and ubiquitous sensor networks.

3. Embedded Systems & Edge Infrastructure
Hardware Engineering: Real-time embedded systems in daily life and software engineering for IoT/IoE (Internet of Everything).
Edge Computing: Edge computing frameworks for latency-sensitive applications.
Hardware Efficiency: Ultra-low power electronics for always-on, constrained devices.

4. Energy-Aware & Sustainable Computing
Green Hardware: Energy harvesting for ubiquitous devices and sustainable materials in consumer electronics.
Green Infrastructure: Green cloud and fog computing for mobile ecosystems.
Efficient Networking: Low-power wireless communication protocols.

5. Next-Gen Infrastructure, Consumer Devices & UX
Enterprise Systems: Cloud Computing and Data Center Systems.
Smart Spaces: IoT-based smart homes/cities and cross-device orchestration.
Human-Computer Interaction (HCI): Next-Gen consumer devices, ambient displays, seamless interfaces, context-aware UX/UI design, and AR integration.