International Conference on Latest Computational Technologies on March 22-24, 2027 in Bangkok, Thailand - Conference Index

International Conference on Latest Computational Technologies on March 22-24, 2027 in Bangkok, Thailand

International Conference on Latest Computational Technologies March 22, 2027 - Bangkok, Thailand

BANGKOK 13th International Conference on Latest Computational Technologies (ICLCT-27) scheduled on March 22-24, 2027 Bangkok (Thailand) is for the engineers, practitioners, scientists, researchers, scholars, and students from all around the world and it also includes the industry people to present ongoing research activities, and hence to foster research relations between Academia and industry. The conference is sponsored by Eminent Association of Pioneers (EAP). This conference provides opportunities for the delegates to share new ideas and application experiences face to face, to establish business or research relations and to find global partners for future collaboration. All the submitted conference papers will be peer reviewed by the program/technical committees of the Conference.

Topics

Topics of interest for submission include any topics related to:

1. Independent Core Disciplines

These represent the fundamental pillars of modern computing—each a vast, specialized field of research and development on its own.

Quantum Computing

Quantum Mechanics Foundations: Superposition, entanglement, and quantum tunneling.

Quantum Hardware Architecture: Superconducting qubits, trapped ion systems, topological qubits, and photonic quantum computing.

Quantum Algorithms: Shor’s algorithm (cryptography), Grover’s algorithm (database search), and Variational Quantum Eigensolvers (VQE).

Quantum Error Correction (QEC): Surface codes, fault-tolerant quantum computing, and noise mitigation in NISQ (Noisy Intermediate-Scale Quantum) systems.

Advanced Artificial Intelligence & Machine Learning

Generative AI and Foundation Models: Large Language Models (LLMs), Multimodal AI (integrating text, audio, video, and code), and Diffusion models.

Deep Learning & Neural Architectures: Transformers, Graph Neural Networks (GNNs), and Neuromorphic computing architectures.

Reinforcement Learning (RL): Deep Q-networks, Policy gradient methods, and Reinforcement Learning from Human Feedback (RLHF).

AI Explainability and Ethics (XAI): Interpretability frameworks, bias mitigation, and alignment theory.

Distributed Systems & Next-Gen Cloud Infrastructure

Edge and Fog Computing: Decentralized data processing, real-time analytics at the network edge, and IoT integration.

Serverless and Microservices Architectures: Containerization (Docker, Kubernetes), service meshes, and event-driven computing.

High-Performance Computing (HPC): Exascale computing, massive parallel processing, and supercomputer cluster management.

Cybersecurity & Cryptographic Technologies

Post-Quantum Cryptography (PQC): Lattice-based cryptography, multivariate cryptography, and stateless hash-based signatures.

Zero-Trust Architectures: Continuous authentication, micro-segmentation, and identity-centric security.

Privacy-Enhancing Technologies (PETs): Homomorphic encryption, secure multi-party computation (SMPC), and differential privacy.

2. Interrelated Cross-Disciplinary Fields

These subtopics exist at the intersections where two or more core computational technologies merge to create highly powerful, hybrid capabilities.

AI + Quantum Computing (Quantum Machine Learning)

Quantum Neural Networks (QNNs): Designing neural network layers that run on quantum hardware.

Quantum-Enhanced Optimization: Using quantum annealers and algorithms to accelerate complex ML training datasets.

Quantum Data Processing: Developing algorithms to handle inherently quantum-state data.

AI + Cloud/Edge Infrastructure (Edge AI & MLOps)

TinyML: Optimizing deep learning models to run on ultra-low-power microcontrollers and edge hardware.

Federated Learning: Training AI models distributively across decentralized edge devices without sharing raw data.

Machine Learning Operations (MLOps): Automated pipelines for deploying, monitoring, and maintaining AI models in cloud environments.

Cybersecurity + Distributed Systems (Blockchain & Web3)

Decentralized Ledgers: Consensus mechanisms (Proof of Stake, Proof of History), smart contracts, and fault-tolerant state machines.

Decentralized Identity (DID): Sovereign identity frameworks built on distributed cryptographic networks.

Secure Cloud Storage: Sharded, encrypted data distribution across peer-to-peer cloud node networks.

Cybersecurity + AI (Adversarial AI & Defenses)

AI-Driven Threat Detection: Using machine learning to identify zero-day exploits, anomalies, and polymorphic malware in real-time.

Adversarial Machine Learning: Protecting AI models from data poisoning, prompt injection, and model inversion attacks.

Automated Penetration Testing: Using autonomous AI agents to simulate complex cyber-attacks and patch software vulnerabilities.

3. Advanced Multi-Disciplinary Frontiers

These cutting-edge domains bring together all the core elements—AI, quantum, distributed cloud systems, and elite security—to redefine human technological capabilities.

Autonomous Cognitive Agents: Fully autonomous software or robotic entities that utilize Edge AI, cloud data meshes, and advanced reasoning models to make real-time decisions without human intervention.

Digital Twins and Spatial Computing: Building highly accurate, real-time digital replicas of physical assets, cities, or industrial systems using IoT (distributed systems), cloud rendering, and AI predictive analytics.

Bio-Digital & Neuromorphic Integration: Creating hardware inspired by the human brain (neuromorphic chips) and exploring DNA data storage, bridging organic biology with extreme computational systems.

Synthetic Biology AI & Molecular Modeling: Utilizing advanced deep learning (like evolutionary protein models) powered by supercomputing and quantum simulation to structurally engineer new medicines and sustainable materials

Name: EARET
Website: http://earet.org

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