International cooperation in AI (IA)

Expected Outcome: Project results are expected to contribute to one of the following outcomes: Faster uptake of tailored and enhanced AI solutions at innovation hubs in low- and middle-income countries by training and optimising them with local data and applied research. Easier large-scale deployment of local AI solutions in low and middle-income countries by increasing the efficiency of system demonstration in relevant, operational environments . Strengthened local innovation ecosystems that foster sustainable socio-economic impact by addressing key societal challenges in areas such as education, healthcare, agriculture, and environmental sustainability. Scope: System prototype, testing, validation, and demonstration in operational environment aligned to EU initiatives, such as the International Digital Strategy for the EU [1] and the AI Continent Action Plan [2] , to strengthen local A… more

Artificial intelligence, intelligent systems, multi agent systemsGenAIinternational cooperation

1. %55
   CEM ÖZKURT

   Doktor Öğretim ÜyesiSakarya Üniversitesi

   Shared topics: Digital Transformation in Industry

2. %49
   LÜTVİYE ÖZGE TEMUR

   Araştırma GörevlisiAltınbaş Üniversitesi

   Shared topics: Digital Transformation in Industry

3. %46
   CANSU KADAKOĞLU

   Araştırma GörevlisiMalatya Turgut Özal Üniversitesi

   Shared topics: Digital Transformation in Industry

4. %46
   SENEM HAZEL ARSLANTAŞ

   Araştırma GörevlisiAksaray Üniversitesi

   Shared topics: Digital Economy and Work Transformation

5. %46
   SONER KIZILOLUK

   Doktor Öğretim ÜyesiMalatya Turgut Özal Üniversitesi

   Research topics: Metaheuristic Optimization Algorithms Research · Smart Agriculture and AI · AI in cancer detection

6. %45
   HARUN BİNGÖL

   DoçentMalatya Turgut Özal Üniversitesi

   Research topics: Metaheuristic Optimization Algorithms Research · AI in cancer detection · Advanced Neural Network Applications

7. %44
   ECE GELAL SOYAK

   Doktor Öğretim ÜyesiBahçeşehir Üniversitesi

   Shared topics: Cooperative Communication and Network Coding

8. %43
   ENES FURKAN ERKAN

   Doktor Öğretim ÜyesiSakarya Üniversitesi

   Shared topics: Digital Transformation in Industry

9. %43
   EREN KAMBER

   Doktor Öğretim ÜyesiAlanya Alaaddin Keykubat Üniversitesi

   Shared topics: Digital Transformation in Industry

10. %43
    SELMAN KULAÇ

    ProfesörDüzce Üniversitesi

    Shared topics: Cooperative Communication and Network Coding

11. %43
    SERDAR BİROĞUL

    ProfesörDüzce Üniversitesi

    Shared topics: Digital Transformation in Industry

12. %41
    ALİ HAKAN IŞIK

    ProfesörBurdur Mehmet Akif Ersoy Üniversitesi

    Research topics: AI in cancer detection · Blockchain Technology Applications and Security · Smart Agriculture and AI

13. %41
    GONCA BUYRUKOĞLU

    Doktor Öğretim ÜyesiAbdullah Gül Üniversitesi

    Research topics: AI in cancer detection · Statistical Methods and Inference · Artificial Intelligence in Healthcare

14. %41
    MURAT AKBIYIK

    Öğretim Görevlisi (ders Vermekle Görevli)Biruni Üniversitesi

    Shared topics: Digital literacy in education

15. %41
    UĞUR ÇEKMEZ

    Doktor Öğretim ÜyesiBiruni Üniversitesi

    Shared topics: Distributed Control Multi-Agent Systems

16. %41
    YÜKSEL YURTAY

    DoçentSakarya Üniversitesi

    Research topics: Smart Agriculture and AI · Metaheuristic Optimization Algorithms Research · Quality and Supply Management

17. %40
    CEMRE EDA ERKILIÇ

    DoçentAnkara Hacı Bayram Veli Üniversitesi

    Research topics: Turkish Urban and Social Issues · Efficiency Analysis Using DEA · Healthcare professionals’ stress and burnout

18. %40
    MEHMET ASİF ALAN

    Öğretim Görevlisi (uygulamalı Birim)Bayburt Üniversitesi

    Shared topics: Digital Transformation in Industry · International Business and FDI

The fit is computed by code on every request: semantic similarity (55%) between the call text (title, EU keywords, start of the official description) and the academic’s YÖKSİS fields, keywords and OpenAlex topics, plus shared distinctive terms (45%; common words weigh little). Below 40% is not shown. A subject hint only — not an eligibility, capacity or merit assessment. Hidden profiles are never listed.