José Suárez-Varela

Associate Researcher @ Telefonica Research. My main research interests are at the intersection of AI/ML and Communication Networks. #GNN #DRL

[José Suárez-Varela @jsuarezvarela]

@victorianoi Que bueno!!

[ORIGAMI @sns_origami]

The second kick-off meeting of the ORIGAMI project funded by Horizon Europe took place on 13/14 May. Thanks to all participants for their collaboration.@imdea_networks;@NEC_EMEA;@Telefonica_En;@tudelft;@i2CAT;@uc3m;@GruppoTIM;@Fogus_gr;@EMnify;@cumucore;@is_wireless;@NetAiTech

[Virgin Media O2 News @VMO2News]

We’ve unveiled the next phase of our mobile network evolution as our #5G Standalone network is now switched on in 14 cities nationwide.

This will give our customers wider and more reliable 5G coverage 👇

[Ioannis Arapakis @iarapakis]

Telefonica Research seeks talented researchers in networks & measurements to work on innovative projects shaping the future of global communication. Apply now to join a dynamic team!

https://t.co/zhLNZBxbZV

@TelefonicaResearch #networks #measurements #algorithmicdesign #5g #6g

[BlogThinkBig @ThinkBig_open]

🗣️ "Conectividad para un mundo mejor: usando IA para reducir desigualdades en redes móviles", un artículo de @iarapakis, @souneil, @SolansDavid y @jsuarezvarela.

https://t.co/hzThwxVYf8

[Kiko Llaneras @kikollan]

¿Los datos te rodean?

🧵 Las ideas más útiles que conozco para exprimir tus datos:

[José Suárez-Varela @jsuarezvarela]

@MEXC_Global @NodleNetwork Merge is working!

[José Suárez-Varela @jsuarezvarela]

@MEXC_Global @NodleNetwork Rocket!

[José Suárez-Varela @jsuarezvarela]

Thank you very much to all the co-authors for their great contribution to this work:
@PaulAlmasan, Miquel Ferriol, Krzysztof Rusek, Fabien Geyer, Xiangle Cheng, Xiang Shi, Shihan Xiao, Franco Scarselli, Albert Cabellos-Aparicio, and Pere Barlet-Ros.

[José Suárez-Varela @jsuarezvarela]

I'm thrilled to announce that our position paper “Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities” has been accepted in the pretigious IEEE Network Magazine 🎉🎉

Pre-print in @ArXiv:
https://t.co/ctU6uu82rN

#IEEE @ComSoc; #machinelearning

[José Suárez-Varela @jsuarezvarela]

This is a joint work from:
Barcelona Neural Networking Center (@BNN_UPC), UPC (@la_UPC)
AGH University of Science and Technology (@AGH_Krakow)
Technical University of Munich (@TU_Muenchen)
@Huawei Technologies Co., Ltd.
Università degli Studi di Siena (@unisiena)

[José Suárez-Varela @jsuarezvarela]

This year we will also organize the 1st GNNet workshop, co-located with ACM CoNEXT (December 2022). Top teams of the challenge will be invited to present their solutions there. Please, find more details about this workshop below:
https://t.co/HaQaywZpV7

[José Suárez-Varela @jsuarezvarela]

It is my pleasure to announce the 3rd edition of the Graph Neural Networking challenge ‼️📢📢

Title: Improving Network Digital Twins through Data-centric AI

There are attractive prizes for winners 💰💰.

Challenge website 👇👇👇
https://t.co/ODvmEpGiPI

[José Suárez-Varela @jsuarezvarela]

The GNNet competition is hosted by the @BNN_UPC, and it is organized as part of the @ITU AI/ML in 5G Challenge (https://t.co/IJJgN6KpNr)

Top-3 teams will advance to the Grand Challenge Finale of the ITU Challenge. The competition attracted 1,600+ participants in the last edition

[Barcelona Neural Networking Center @BNN_UPC]

📢 Paper alert! We are delighted to announce that the latest work "Network Digital Twin: Context, Enabling Technologies and Opportunities" has been accepted for publication at #IEEE Communications Magazine. The paper is publicly available in https://t.co/tYlV5CYE0z

[José Suárez-Varela @jsuarezvarela]

@sergiabadal Congratulations Sergi! Very well deserved!! 😀😀

[Patrick Moelleken 🇺🇦 @PMoelleken]

.@ZelenskyyUa's tv address to the Russian (!) people might be the most moving speech that I've ever seen in my entire life. The whole world needs to see, understand and share this crucial Ukrainian message.
#StandWithUkraine #Ukraine #Україна #Russia #Россия

[Dominique Beaini @dom_beaini]

Last year, we saw the rise of gigantic "foundation" models, trained on billions of images/text samples. Meanwhile, a typical GNN dataset contains ~1000 graphs👶🍼

Are you ready for the next phase of large-scale GNNs? Then check out this talk by @nc_frey
https://t.co/NdLx5yijKj