New approaches for decentralized, federated and sustainable AI data processing (RIA)

Expected Outcome: Project results are expected to contribute to developing new approaches, tools and techniques that overcome the obstacles of today's centralised AI compute techniques: limits in the availability of energy and AI compute capacity in centralised standalone environments, limited availability of types of AI chips, data quality and security and latency in AI data processing. The ultimate objective is to help overcome EU’s AI compute capacity bottlenecks by offering alternative decentralised and sustainable AI compute models that enable exploitation of diverse hardware processing architectures and scaling approaches. Scope: This topic focusses on technologies and techniques that enable AI data processing to leverage distributed compute resources across the cloud and edge computing continuum throughout the whole AI model lifecycle from data collection, training, fine-tuning, a… devamı

Computer sciences, information science and bioinformaticsCloud computingEdge computing

1. %55
   NİLGÜN İNCEREİS

   Öğretim Görevlisi (uygulamalı Birim)Bartın Üniversitesi

   Ortak konular: IoT and Edge/Fog Computing

   Örtüşen yayınlar: The Aplication and Design of Computer Assissted Education Environment in the Matter of Electricity in Our Life (2012) · Data Security Techniques and Comparison of Differential Privacy Techniques in Bioinformatics (2023)

2. %55
   SAMA HABIBI

   Doktor Öğretim ÜyesiBahçeşehir Üniversitesi

   Ortak konular: IoT and Edge/Fog Computing

   Örtüşen yayınlar: A survey on integrated computing, caching, and communication in the cloud-to-edge continuum (2024) · Yardstick competition regulation for incentive mechanisms in federated learning: balancing cost optimization and fairness (2023)

3. %52
   ERHAN GÖKÇAY

   DoçentAtılım Üniversitesi

   Ortak konular: Cloud Computing and Resource Management · IoT and Edge/Fog Computing

   Örtüşen yayınlar: A New Multi-Target Compiler Architecture for Edge-Devices and Cloud Management (2022) · The Virtual Instrument: Support for Grid-Enabled Mcell Simulations (2004)

4. %51
   MURAT GÖKŞİN BAKIR

   Öğretim Görevlisi (ders Vermekle Görevli)Bahçeşehir Üniversitesi

   Ortak konular: IoT and Edge/Fog Computing

   Örtüşen yayınlar: Motion Planning With Acceleration Constraint (1992) · Integrating Multiple Methodologies, Segment Anything Model and AlexNet, for Enhanced Accuracy in Garbage Classification (2024)

5. %50
   AHMET ERCAN TOPCU

   DoçentAnkara Medipol Üniversitesi

   Ortak konular: Distributed and Parallel Computing Systems · Scientific Computing and Data Management · Cloud Computing and Resource Management

   Örtüşen yayınlar: A Systematic Review and Evaluation of Sustainable AI Algorithms and Techniques in Healthcare (2025) · Evaluating the Performance of NoSQL Databases for Big Data in Cloud Computing Environments (2025)

6. %46
   ALIREZA SOURI

   DoçentHaliç Üniversitesi

   Ortak konular: IoT and Edge/Fog Computing · Cloud Computing and Resource Management

   Örtüşen yayınlar: A Multi-Objective Approach for Optimizing Edge-Based Resource Allocation Using TOPSIS (2022) · A Multi-Objective Approach for Optimizing Edge-Based Resource Allocation Using TOPSIS (2022)

7. %45
   ESRA ŞATIR

   DoçentDüzce Üniversitesi

   Ortak konular: DNA and Biological Computing

   Örtüşen yayınlar: A DNA Data Storage Method Using Spatial Encoding Based Lossless Compression (2024) · Optimization of Interval Type-2 Fuzzy Logic Controller Using Real-Coded Quantum Clonal Selection Algorithm (2022)

8. %45
   KORHAN CENGİZ

   DoçentBiruni Üniversitesi

   Ortak konular: IoT and Edge/Fog Computing

   Örtüşen yayınlar: MediNet: Self-Supervised Framework for Multimodal Analysis and Patient Care in IoMT (2025) · Advancing Medical Recommendations With Federated Learning on Decentralized Data: A Roadmap for Implementation (2024)

9. %43
   FERHAT KUTLU

   Doktor Öğretim ÜyesiBeykoz Üniversitesi

   Ortak konular: EEG and Brain-Computer Interfaces

   Örtüşen yayınlar: AI Support for Improving Managerial Decision-Making Processes Regarding Workforce Planning (2026)

10. %42
    BETÜL AKTAŞ

    Öğretim Görevlisi (ders Vermekle Görevli)Çağ Üniversitesi

    Ortak konular: IoT and Edge/Fog Computing · Environmental Sustainability in Business

11. %41
    HASAN ÖZTÜRK

    Doktor Öğretim ÜyesiBartın Üniversitesi

    Ortak konular: Distributed and Parallel Computing Systems · Parallel Computing and Optimization Techniques

12. %41
    SEFER KURNAZ

    DoçentAltınbaş Üniversitesi

    Ortak konular: IoT and Edge/Fog Computing

    Örtüşen yayınlar: An Effective Mechanism for FOG Computing Assisted Function Based on Trustworthy Forwarding Scheme (IOT) (2024) · Federated learning for privacy-preserving skin cancer classification using deep neural networks (2026)

13. %40
    ABDULLAHI ABDU IBRAHIM

    DoçentAltınbaş Üniversitesi

    Ortak konular: IoT and Edge/Fog Computing

    Örtüşen yayınlar: An intelligent atrous convolution-based cascaded deep learning framework for enhanced privacy preservation performance in edge computing (2024) · Implementing the ACO Algorithm and Fog Nodes for Efficient Resource and Energy Allocation in Cloud Computing (2022)

14. %40
    ÖZNUR ÖZKASAP

    ProfesörKoç Üniversitesi

    Ortak konular: IoT and Edge/Fog Computing

    Örtüşen yayınlar: LightChain: Scalable DHT-Based Blockchain (2021) · Spatial and thermal aware methods for efficient workload management in distributed data centers (2024)

Uyum oranı kodla, her istekte hesaplanır. Çağrı metni (başlık, anahtar kelimeler, resmi açıklamanın başı) şu üç kaynakla karşılaştırılır: akademisyen profiliyle anlamsal yakınlık (%50), YÖKSİS anahtar kelimeleri ve OpenAlex konularındaki ortak ayırt edici terimler (%25) ve yayın içeriği — başlıklar, İngilizce özetler ve bunların Türkçe çevirileri (%25). Çeviriler sayesinde Türkçe çağrılar İngilizce yayınlarla da eşleşir. Yaygın kelimeler düşük ağırlıklıdır; %40 altı gösterilmez. Bir konu önerisidir; başvuru uygunluğu, kapasite ya da başarı değerlendirmesi değildir. Gizli profiller listelenmez.