Fatemeh Golpayegani | Artificial Intelligence | Best Researcher Award

Dr. Fatemeh Golpayegani | Artificial Intelligence | Best Researcher AwardΒ 

Assistant Professor | University College Dublin | Ireland

πŸ“œ 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

πŸŽ“ 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

πŸ‘©β€πŸ« 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

πŸ” Research Interest:

Her research interests encompass:

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

πŸ† 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.

πŸ“š 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.

 

Vinit Katariya | Deep Learning | Best Researcher Award

Dr. Vinit Katariya | Deep Learning | Best Researcher Award

Post Doctoral Researcher | University of North Carolina at Charlotte |Β United States

Short Bio 🌐

Vinit Katariya is a Machine Learning Researcher based in Charlotte, NC. His expertise spans machine learning modeling and algorithm design, with a focus on Python, C, and frameworks like PyTorch. He is dedicated to solving complex, large-scale problems with real-world impact.

Profile

Google Scholar

Education πŸ“š

Vinit Katariya earned his Doctor of Philosophy in Electrical Engineering from the University of North Carolina at Charlotte in December 2023, under the guidance of Dr. Hamed Tabkhi. His research focused on innovative applications of deep learning in transportation and IoT systems.

Experience πŸ’Ό

As a Postdoctoral Researcher at UNC Charlotte, Vinit leads projects on speed estimation and smart city solutions, collaborating with international teams to enhance real-world video analytics and transportation efficiency.

Research Interest 🧠

Vinit Katariya’s research interests include deep learning applications in transportation safety, IoT edge computing, and anomaly detection using AI frameworks on embedded platforms.

Awards πŸ†

  • Best Demo Award – ICCPS 2023
  • UNC Charlotte Graduate School Summer Scholarship – May 2022

Publications πŸ“„

Vinit Katariya has co-authored articles in high-impact journals and conferences, including: