Giang T. Nguyen
Scholar

Giang T. Nguyen

Google Scholar ID: U1fIVqcAAAAJ
Assistant Professor | CeTI – Cluster of Excellence | ceti.one
In-Network ComputingSoftwarized NetworksActive Perception
Citations & Impact
All-time
Citations
1,294
 
H-index
19
 
i10-index
40
 
Publications
20
 
Co-authors
13
list available
Resume (English only)
Academic Achievements
  • Received Best Paper Award at IEEE 8th International Conference on Network Softwarization (NetSoft) in 2022; Won Best Demo Award at IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) in 2019; Also awarded a Best Paper Award in 2014.
Research Experience
  • Since July 2021, he has been an Assistant Professor leading the Juniorprofessur für Haptische Kommunikationssysteme at TU Dresden, affiliated with the Faculty of Electrical and Computer Engineering; From 2019 to 2021, he co-founded and led the Networking and Edge Computing division at robotics company Wandelbots, which he also helped establish in November 2017; Between 2016 and 2019, he worked as a postdoc at the Deutsche Telekom Chair of Communication Networks at TU Dresden, focusing on network softwarization and information theory; From 2002 to 2010, he was a lecturer at the Faculty of Information Technology at Hanoi University of Civil Engineering in Vietnam.
Education
  • In 2016, he obtained his Dr.-Ing. degree from the Chair of Data Privacy and Security at TU Dresden with a dissertation titled 'Contributions to the Resilience of Peer-To-Peer Video Streaming against Denial-of-Service Attacks', under the supervision of Prof. Strufe; In 2005, he received his Master of Engineering in Telecommunications from the Asian Institute of Technology (Thailand); In 2001, he earned his Bachelor of Engineering in Telecommunications from Hanoi University of Science and Technology (Vietnam).
Background
  • Research interests include low latency, flexibility, and resilience of networked systems to enable haptic communication. He focuses on developing new protocols for service differentiation through in-network computing and programmable networks.