Dr. Parwinder Singh

Assistant Professor

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Biography

Parwinder Singh is a Postdoc at Aarhus University focusing on Convergence Technologies, Responsible AI, and Industry 4.0. His research involves developing innovative methodologies to enhance digital traceability, resource sharing, and system services using Blockchain technology. Singh's work aims to explore the theoretical underpinnings of traditional distributed architectonic paradigms, system modeling, and empirical validation. He is dedicated to extending Cloud-Edge-Device paradigms and exploiting the convergence capabilities of Internet of Things (IoT), Distributed Ledger Technology (DLT), Edge Computing, and Artificial Intelligence/Machine Learning (AI/ML). He emphasizes creating cross-domain data-driven value chains to foster sustainable business models. His approach integrates Design Science Research, Software Architectural Design patterns, and various methodological frameworks to address challenges in industrial and academic settings. He is currently engaged in collaborative projects at Eindhoven University of Technology, focusing on AI and data harmonization in dataspace ecosystems. Singh also teaches digital backend courses related to Cloud Computing and Blockchain while supervising theses on Digitalization and Dataspace.

Research Interests

Experience

Postdoc

2022-01-01 — Present

Aarhus University • Herning, Denmark

Conducting research in Convergence Technologies and Responsible AI, focusing on digitalization and dataspace applications.

Requirements for Aarhus University

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Overall
Required:6.5
TOEFL
Total
Required:83
Prerequisites
Bachelor's degree in a relevant field Specific credit requirements in programming, algorithms, and computer systems
Application Checklist
  • Official Bachelor's degree certificate
  • Official transcripts of records
  • Course descriptions
  • Curriculum Vitae (CV)
  • Documentation of English language proficiency
Specialization Notes

Department of Computer Science offers tracks in Software Efficiency, Cryptography, and Data Science.