Feras M. Awaysheh

Feras M. Awaysheh
Position
Senior Research/Academic Staff
Address
Narva mnt 18, 51009 Tartu
Office No
3105
data

                  The Sun Rise, Giving Light... Data Rises; giving Wisdom (Feras M. Awaysheh).

 

Dr. Feras M. Awaysheh is an Assistant Professor in Big Data Systems at the Data Systems Group. He received his Ph.D. in Big Data and Cloud Computing from CiTIUS research center, the University of Santiago de Compostela (honors with distinction), Spain, in 2020. He holds an MSc. degree (with Distinction.) in Computer Networks and Information Security from the New York Institute of Technology (NYiT) 2011 and a BSc. in Software Engineering from Al Balqa' Applied University, Jordan 2008. Dr. Awaysheh worked as a visiting research fellow in both Charles Darwin University, Australia, and the EPCC research center at Edinburgh University, the UK, in 2019 and 2020, respectively.         

His research interest covers mainly Big Data (BD) deployment architectures and their applications. Dr. Awaysheh's interests include BD Engineer, i.e., modeling, designing, and optimizing platforms for BD frameworks across multiple deployment architectures and environments using containerization technology. His recent research interests focus on related technologies and include High-Performance Data Analytics, Data Streaming, IoT, and Edge/Fog deployment architectures. Besides, the development of privacy-preserving and security frameworks for cloud-enabled solutions and Edge Intelligence systems, including Federated Learning.

                                                                                   

Teaching:  Data Engineering (LTAT.02.007), Big Data Management (LTAT.02.003), Advanced Database (LTAT.02.010), Data Systems Research Group Seminar (LTAT.05.013), and Edge Intelligence (LTAT.06.017).   

Selected Publications

Google Schooler with full publication list can be found here

  • Big Data Resource Management & Networks: Taxonomy, Survey, and Future Directions. IEEE Communications Surveys & Tutorials. Published 2021 [PDF]
  • An Attribute-Based Access Control for Cloud-Enabled Industrial Smart Vehicles. IEEE Transactions on Industrial Informatics. Published 2021 [PDF]
  • An In-depth Investigation of Large-scale RDF Relational Schema Optimizations Using Spark-SQL. DOLAP. Published 2021 [PDF]
  • A Blockchain-Based Multi-Factor Authentication Model for a Cloud-Enabled Internet of Vehicles. Sensors. Published 2021 [PDF]
  • Security by Design for Big Data Frameworks Over Cloud Computing. IEEE Transactions on Engineering Management. Published 2021 [PDF]
  • A Survey on Clustering Algorithms in Wireless Sensor Networks: Challenges, Research, and Trends. IEEE International Computer Symposium. Published 2021 [PDF]
  • Active Machine Learning Adversarial Attack Detection in the User Feedback Process. IEEE Access. Published 2021 [PDF]
  • From the Cloud to the Edge: Towards a Distributed and Light Weight Secure Big Data Pipelines for IoT Applications. Book Chapter CRC Trust, Security, and Privacy for Big Data. Accepted 2021