Fatemeh Golpayegani | Artificial Intelligence | Best Researcher Award

Dr. Fatemeh Golpayegani | Artificial Intelligence | Best Researcher Award 

Assistant Professor | University College Dublin | Ireland

📜 Short Bio:

Fatemeh Golpayegani is currently an Assistant Professor at the School of Computer Science, University College Dublin (UCD), where she contributes significantly to research and academic activities in the field of computer science. Her expertise lies in multi-agent systems, edge computing, and intelligent transport systems.

Profile:

SCOPUS

🎓 Education:

Fatemeh pursued her academic journey with a strong foundation in computer science:

  • Ph.D. in Computer Science (2013-2018)
    Trinity College Dublin, Dublin, Ireland
    Thesis Title: “Collaboration community formation in open systems for agents with multiple goals.”
    Supervised by Prof. Siobhan Clarke.
  • M.Sc. in Computer (Software) Engineering (2010-2012)
    Sharif University of Technology, Tehran, Iran
    Thesis Title: “Development of a process line engineering approach based on product line engineering methods for engineering agent-oriented methodologies.”
  • B.Sc. Hons in Computer (Software) Engineering (2006-2010)
    Alzahra University, Tehran, Iran

👩‍🏫 Experience:

Fatemeh has held various academic and professional roles:

  • Assistant Professor (Dec 2020 – Present)
    School of Computer Science, UCD, Dublin, Ireland
  • Postdoctoral Researcher (June 2018 – Jan 2019)
    CONNECT, School of Computer Science and Statistics, Trinity College Dublin, Ireland
  • Software Engineer (Sept 2010 – Aug 2013)
    ITOrbit, Tehran, Iran

🔍 Research Interest:

Her research interests encompass:

Multi-agent Systems, Edge Computing, Intelligent Transport Systems, Agent-based Modeling

🏆 Award:

Fatemeh Golpayegani is recognized as a member of the Young Academy of Ireland (2023-2027), highlighting her contribution to advancing research and cultural life in Ireland.

📚 Publications:

Fatemeh has contributed significantly to her field with numerous peer-reviewed publications. A selection of her notable works include:

Adaptation in Edge Computing: A review on design principles and research challenges
Published in ACM Transactions on Autonomous and Adaptive Systems, 2024. Cited by: 15

Handling uncertainty in self-adaptive systems: an ontology-based reinforcement learning model
Published in Journal of Reliable Intelligent Environments, 2023. Cited by: 20

Towards the Use of Hypermedia MAS and Microservices for Web Scale Agent-Based Simulation
Published in SN Computer Science, 2022.

Intelligent Shared Mobility Systems: A Survey on Whole System Design Requirements, Challenges and Future Direction
Published in IEEE Access, 2022.

Using Social Dependence to Enable Neighbourly Behaviour in Open Multi-agent Systems
Published in ACM Transactions on Intelligent Systems and Technology (TIST), 2019.

These publications underscore her research breadth and impact in areas such as adaptive systems, shared mobility, and multi-agent collaboration.

 

Monika Nagy-Huber | Machine Learning | Best Researcher Award

Mrs. Monika Nagy-Huber | Machine Learning | Best Researcher Award

Ms. Universität Basel, Switzerland

Monika Timea Nagy-Huber is currently pursuing a PhD in Computer Science at the University of Basel, specializing in Physics-informed Machine Learning Algorithms under the supervision of Prof. Dr. Volker Roth in the Biomedical Data Analysis research group. She earned her Master of Science in Mathematics from the same university, focusing on Numerics (Partial Differential Equations for Wave Equations) and Algebra-Geometry-Number Theory (Elliptic Curves). Her master’s thesis, titled “The Local Discontinuous Galerkin Method with Local Time Stepping Method for solving the Wave Equation,” received a grade of 5.5. Monika also holds a Bachelor of Science in Mathematics from the University of Basel, completed in 2016.

Profile

Google scholar

Personal Data 🌐

Last Name: Nagy-Huber
First Name: Monika Timea
E-Mail: monika.nagy@unibas.ch
Nationality: Swiss

University Education 🎓

PhD in Computer Science, University of Basel
09/2019 – Present

Supervisor: Prof. Dr. Volker Roth

Research Group: Biomedical Data Analysis

Specialization: Physics-informed Machine Learning Algorithms

Master of Science in Mathematics, University of Basel
02/2016 – 02/2019

Areas of Specialization: Numerics (Partial Differential Equations for Wave Equations), Algebra-Geometry-Number Theory (Elliptic Curves)

Master’s Thesis: “The Local Discontinuous Galerkin Method with Local Time Stepping Method for solving the Wave Equation”

Grade: 5.5

Supervisor: Prof. Dr. Marcus J. Grote

Bachelor of Science in Mathematics, University of Basel
09/2011 – 02/2016

Publications:

The effect of lysergic acid diethylamide (LSD) on whole-brain functional and effective connectivity

CITED BY 17

Learning invariances with generalised input-convex neural networks

CITED BY 5

Mesh-free Eulerian Physics-Informed Neural Networks

CITED BY 1

Mesh-free Eulerian physics-informed neural networks

CITED BY 1