Mission
This blog highlights the contributions made by a group of faculty, researchers, and doctoral students working on Networked Systems aspects. For open positions, please consult our Projects.
This blog highlights the contributions made by a group of faculty, researchers, and doctoral students working on Networked Systems aspects. For open positions, please consult our Projects.
We are happy to announce that Massimo Girondi successfully defended his licentiate thesis (licentiate is a degree at KTH half-way to a PhD)! Marco Chiesa has done an excellent job as a co-advisor and as is customary we are very grateful to Prof. Gerald Q. Maguire Jr. for his key insights. Giuseppe Siracusano was a superb opponent at the licentiate seminar, with Amir Payberah as the examiner. Massimo’s thesis is available online:
“Toward Highly-efficient GPU-centric Networking”
A few shots from the celebration are below.
Group shot of Networked Systems Laboratory members (Massimo is beneath the KTH logo). Image taken by Voravit Tanyingyong
Dejan is deeply honored to become a Wallenberg Scholar! This grant comes with 18 MSEK in funding over five years. More information is available at the KAW website.
We are hugely honored that our “Millions of Low-Latency Insertions on ASIC switches” paper received the Best Paper Award at ACM CoNEXT 2023! More details are available in our earlier post.
From left to right: Tommaso Caiazzi, Mariano Scazzariello, Marco Chiesa, Olivier Bonaventure (TPC co-chair)
We were once again at the ceremony at which KTH is officially awarding doctoral degrees. This time it was Alireza Farshin’s time, and we used the beautiful Stockholm City Hall to recreate our favorite hallway shot!
Our “SEMLA: Securing Enterprises via Machine-Learning-based Automation” project proposal has been selected for funding by Vinnova. The project cost is 12MSEK with Prof. Marco Chiesa as the PI. Other project partners include members from the Computer Security group from KTH, the Connected Intelligence unit at RISE, RedHat, and Saab.
The SEMLA project seeks to make the development of software systems more resilient, secure, and cost-effective. SEMLA leverages recent advancements in machine learning (ML) and artificial intelligence (AI) to automate critical yet common & time-consuming tasks in software development that often lead to catastrophic security vulnerabilities.