34th BARCELONA World Conference on Latest Computational Technologies: WCLCT-26

Call for papers/Topics

Topics of Interest for Submission include, but are Not Limited to:

1. Independent Computational Paradigms

These are distinct approaches to computing, defined by unique hardware architectures, mathematical foundations, and processing physics.

A. Quantum Computing

Processing information using the laws of quantum mechanics rather than classical bits.

• Subtopics:

  • Qubits and Superposition (processing multiple states simultaneously)

  • Quantum Entanglement (linking qubits for exponential processing power)

  • Quantum Cryptography and Post-Quantum Cryptography (PQC)

  • NISQ (Noisy Intermediate-Scale Quantum) Systems

B. Neuromorphic Computing

Hardware architectures physically modeled after the human brain’s neural structure.

• Subtopics:

  • Spiking Neural Networks (SNNs)

  • Physical Memristors (hardware that remembers electrical resistance)

  • Brain-Computer Interfaces (BCI) at the hardware level

  • Event-driven sensing and processing

C. Optical / Photonic Computing

Using light (photons) instead of electricity (electrons) to perform computational logic.

• Subtopics:

  • Silicon Photonics

  • Optical interconnects for data centers

  • Laser-based logic gates

D. DNA and Biocomputing

Using biological molecules (like DNA) or living cells to store data and perform operations.

• Subtopics:

  • DNA Data Synthesis and Storage

  • Wetware Computers (organic material combined with hardware)

  • Synthetic Biology computing circuits

2. Interrelated & Convergent Technologies

These technologies do not live in a vacuum. They heavily intersect, driving the modern digital and physical AI revolution.

A. Artificial Intelligence & Machine Learning (The Core Driver)

AI is no longer a standalone topic; it is the software backbone being integrated into all physical and cloud computation.

• Subtopics:

  • Generative AI & Large Language Models (LLMs): Transformer architectures, prompt engineering, and synthetic content generation.

  • Agentic AI & Multi-Agent Systems: AI models that can autonomously plan, use tools, and collaborate with other AI agents to execute complex workflows.

  • Explainable AI (XAI): Making the "black box" of deep learning decisions understandable to humans for legal and ethical compliance.

B. Distributed & Infrastructure Computing (The Physical Backbone)

How and where we process the massive amounts of data required by modern AI and enterprise systems.

• Subtopics:

  • Cloud 3.0 (Hybrid, Multi-, and Sovereign Cloud): Shifting from raw public cloud migration to highly regulated, localized, and specialized environments.

  • Hyperscale Edge Computing: Bringing computation as close to the physical data source as possible to eliminate latency.

  • AI Supercomputing Platforms: Massive GPU and specialized AI accelerator clusters (like TPUs) designed specifically for training foundational models.

C. Spatial & Physical Computing (The Real-World Interface)

Technologies that allow computation to understand, map, and interact with the 3D physical world.

• Subtopics:

  • Physical AI (Embodied AI): Advanced robotics and drones powered by edge AI processing.

  • Digital Twins: Virtual, real-time replicas of physical systems (factories, cities, cars) used for simulation and predictive maintenance.

  • Extended Reality (XR): The convergence of Virtual Reality (VR), Augmented Reality (AR), and spatial mapping.

D. Trust, Security, & Decentralization

As computation becomes more powerful and autonomous, the tech required to secure it must evolve.

• Subtopics:

  • Preemptive & AI-Driven Cybersecurity: Using machine learning to predict and isolate zero-day threats before they strike.

  • Confidential Computing: Encrypting and protecting sensitive data while it is actively being processed in memory.

  • Web3 & Blockchain: Decentralized ledgers, tokenization, and digital provenance (verifying whether data or media was generated by a human or an AI).