Prof. Dr. Lin Wang

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Prof. Dr. Lin Wang

Computer Networks

Head - Professor

Phone:
+49 5251 60-5375
Fax (External):
+49 5251 60-5377
E-mail:
Office:
O3.149
Web (External):
Visitor:
Pohlweg 51
33098 Paderborn
Brief Profile

Lin Wang is currently a Full Professor (W3) and Head of the Computer Networks group in the Department of Computer Science at Paderborn University. He received his Ph.D. in Computer Science from the Institute of Computing Technology, Chinese Academy of Sciences in 2015. Before joining Paderborn University, he was a tenured Assistant Professor at Vrije Universiteit Amsterdam. Before that, he held (visiting) positions at TU Darmstadt, SnT Luxembourg, and IMDEA Networks Institute. His research is focused on networked systems at the edge and in the cloud, with the goal of achieving performance and sustainability. He has served as a referee for several funding agencies (e.g., DFG, ISF, and HK-RGC), on the program committees of major conferences (e.g., SoCC, Middleware, INFOCOM, MobiHoc, ICDCS, IWQoS, and SEC) and as a reviewer for top journals (e.g., ToN, JSAC, TMC, and TPDS). He has received several awards, including a Google Research Scholar Award, an Outstanding Paper Award of IEEE RTSS 2022, Best Paper Awards of IEEE IPCCC 2023 and of IEEE HotPNS 2016, and an Athene Young Investigator Award of TU Darmstadt. He is currently a Senior Member of IEEE.

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Publications

Latest Publications

X-Stream: A Flexible, Adaptive Video Transformer for Privacy-Preserving Video Stream Analytics
F. Dou, L. Wang, S. Chen, F. Liu, in: Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), IEEE, n.d.
Train Once Apply Anywhere: Effective Scheduling for Network Function Chains Running on FUMES
M. Blöcher, N. Nedderhut, P. Chuprikov, R. Khalili, P. Eugster, L. Wang, in: Proceedings of the IEEE International Conference on Computer Communications (INFOCOM), IEEE, n.d.
𝜆Grapher: A Resource-Efficient Serverless System for GNN Serving through Graph Sharing
H. Hu, F. Liu, Q. Pei, Y. Yuan, Z. Xu, L. Wang, in: Proceedings of the ACM Web Conference (WWW), ACM, 2024.
Sponge: Inference Serving with Dynamic SLOs Using In-Place Vertical Scaling
K. Razavi, S. Ghafouri, M. Mühlhäuser, P. Jamshidi, L. Wang, in: Proceedings of the 4th Workshop on Machine Learning and Systems (EuroMLSys), Colocated with EuroSys 2024, ACM, 2024.
IPA: Inference Pipeline Adaptation to Achieve High Accuracy and Cost-Efficiency
S. Ghafouri, K. Razavi, M. Salmani, A. Sanaee, T. Lorido Botran, L. Wang, J. Doyle, P. Jamshidi, Journal of Systems Research (JSys) (n.d.).
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