13th International Conference on Computer Science, Engineering and Information Technology (CSEIT 2026)
July 16 ~ 17, 2026, London, United Kingdom Scope & Topics The 13th International Conference on Computer Science, Engineering and Information Technology (CSEIT 2026) serves as a premier international forum for researchers, practitioners, and industry professionals to present and discuss the latest innovations, trends, and challenges across the broad spectrum of computing. As the fields of Computer Science, Engineering, and Information Technology continue to evolve at an unprecedented pace, CSEIT 2026 aims to foster collaboration, inspire new ideas, and showcase cutting edge developments that are shaping the future of technology.
The conference welcomes significant contributions that advance theoretical foundations, propose novel methodologies, or demonstrate impactful applications. CSEIT 2026 encourages participation from both academia and industry, providing a dynamic platform where emerging researchers, seasoned experts, and technology leaders can exchange insights, share experiences, and explore new research directions .
Authors are invited to submit original research articles, case studies, survey papers, and industrial experiences that highlight meaningful progress and breakthroughs. Submissions may address any of the conference themes, including—but not limited to—the following areas: Topics of interest include, but are not limited to, the following.
Artificial Intelligence, Machine Learning and Data Science
- Machine Learning, Deep Learning and Representation Learning
- Foundation Models and Large Language Models (LLMs)
- Multimodal AI (Vision–Language, Speech–Language, Multisensory AI)
- Generative AI (Diffusion Models, GANs, Text to X Systems)
- AI Agents, Autonomous AI Systems and Tool Using AI
- Reinforcement Learning, Multi Agent Systems and Decision Making
- Neuro Symbolic AI, Reasoning and Logical Inference
- Graph Machine Learning and Network Science
- Data Centric AI, Data Quality, Labeling and Synthetic Data
- Federated Learning, Edge AI and On Device ML
- Efficient AI: Quantization, Distillation, Sparse Models and Low Rank Adaptation
- Explainable, Trustworthy, Robust and Responsible AI
- AI Safety, Alignment, Red Teaming and Governance
- AI for Science, Healthcare, Climate, Materials and Chemistry
Natural Language Processing and Speech Technologies
- Natural Language Understanding and Generation
- Retrieval Augmented Generation (RAG) and Prompt Engineering
- LLM Evaluation, Safety, Jailbreak Detection and Alignment
- Multilingual, Low Resource and Cross Lingual NLP
- Information Retrieval, Search and Question Answering
- Speech Recognition, Synthesis and Spoken Dialogue Systems
- Computational Linguistics and Language Modeling
Computer Vision, Graphics and Immersive Technologies
- Image Processing, Pattern Recognition and Object Detection
- 3D Vision, Scene Understanding and Reconstruction
- Vision Transformers and Diffusion Models for Vision
- AR/VR/MR, Digital Twins and Immersive Environments
- Graphics, Rendering, Simulation and Animation
- Synthetic Data Generation and Data Centric Vision
- Embodied Vision and Perception for Robotics
Systems, Architecture and High Performance Computing
- Computer Architecture, Accelerators (GPU/TPU/NPU) and Heterogeneous Computing
- AI Native Operating Systems and AI First Infrastructure
- Parallel, Distributed and High Performance Computing
- Distributed Training for Large Scale Models
- Cloud, Edge, Fog and Serverless Computing
- Operating Systems, Virtualization and Containerization
- AI Systems, ML Infrastructure and Model Serving
- Energy Efficient, Sustainable and Carbon Aware Computing
- Real Time, Embedded and Cyber Physical Systems
Networking, Communications and Cyber Physical Systems
- Computer Networks, Protocols and Internet Architecture
- AI Driven Networking and Autonomous Network Control
- In Network Computing, SmartNICs and P4/eBPF Acceleration
- 5G/6G, Non Terrestrial Networks and Satellite Internet
- IoT, Ubiquitous Computing and Smart Environments
- Networked AI Systems and Distributed Intelligence
- Network Digital Twins and Large Scale Network Simulation
Security, Privacy and Cryptography
- Cybersecurity, Threat Detection and Malware Analysis
- LLM Security: Prompt Injection, Model Extraction and Data Poisoning
- AI Generated Threats: Deepfakes, Synthetic Identities and Automated Attacks
- Cryptography, Post Quantum Cryptography and Secure Protocols
- Blockchain, Distributed Ledgers and Web3 Security
- Privacy Preserving Computation (MPC, HE, Differential Privacy, FL)
- Secure ML Pipelines and Supply Chain Security
- Secure Hardware, TEEs and Side Channel Defenses
- Identity, Access Control and Trust Management
Software Engineering, Programming Languages and DevOps
- Software Engineering Methods, Tools and Processes
- AI Augmented Software Development (Code Agents, Program Repair, Debugging)
- Software Engineering for ML Systems (MLOps, ModelOps)
- Programming Languages, Compilers and Runtime Systems
- Software Testing, Verification and Validation
- Requirements Engineering, Architecture and Design
- Empirical Software Engineering and Developer Productivity
Databases, Data Engineering and Knowledge Technologies
- Database Systems, Query Processing and Optimization
- Distributed Databases, NoSQL/NewSQL and Cloud Native Data Systems
- Vector Databases, Embedding Stores and AI Native Data Systems
- Data Lakehouse Architectures and Unified Batch/Streaming
- Streaming Data Systems and Real Time Analytics
- Learned Indexes and ML Enhanced Query Optimization
- Knowledge Graphs, Semantic Web and Ontologies
- Data Governance, Quality, Lineage and Versioning
- Intelligent Information Systems and Information Retrieval
Human–Computer Interaction and User Experience
- Human–AI Interaction, Co Creation and AI Assisted Workflows
- AI Mediated Communication and Digital Humans
- User Experience, Interaction Design and Usability
- Assistive Technologies and Accessibility
- Social Computing, Digital Behavior and Computational Social Science
- Ethics, Societal Impacts and Responsible Technology
Modeling, Simulation and Theoretical Foundations
- Algorithms, Complexity Theory and Theoretical Computer Science
- Formal Methods, Verification and Model Checking
- Modeling and Simulation of Complex Systems
- Digital Twins, Agent Based Modeling and Computational Modeling
- Mathematical Foundations of Computing
Emerging Technologies and Interdisciplinary Computing
- Quantum Computing, Quantum Algorithms and Quantum Machine Learning
- Neuromorphic Computing and Brain Inspired Systems
- Robotics, Autonomous Vehicles and Intelligent Control
- Spatial Computing, Geospatial AI and GIS
- Bioinformatics, Computational Biology and Synthetic Biology
- Sustainable Computing, Green IT and Climate Tech
- Space Computing, Autonomous Space Systems and On Orbit AI
Paper Submission Authors are invited to submit papers through the conference Submission System by May 02, 2026. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed). Selected papers from CSEIT 2026, after further revisions, will be published in the special issue of the following journals. Important Dates | Submission Deadline | : | May 02, 2026 | | Authors Notification | : | June 20, 2026 | | Final Manuscript Due | : | June 27, 2026 |
Co - Located Event ***** The invited talk proposals can be submitted to cseit@cseit2026.org
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