Introduction to 5G from radio perspective

Ms. Thura Hatim Al-Juboori | Ericsson Poland | Friday December 3, 2021 | 10:00 (CET, 09:00 UTC) |

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5G is the fifth generation of cellular networks. Up to 100 times faster than 4G, 5G is creating never-before-seen opportunities for people and businesses. Faster connectivity speeds, ultra-low latency and greater bandwidth is advancing societies, transforming industries and dramatically enhancing day-to-day experiences. Services that we used to see as futuristic, such as e-health, connected vehicles and traffic systems and advanced mobile cloud gaming have arrived. With 5G technology, we can help create a smarter, safer and more sustainable future.


* Network performance and evolution lead for all Europe and Latin America, Ericsson Company (Poland office)

* Professional consultant for network performance and 5G evolution lead with more than 15 years of experience in different Telco topics

* Responsibilities covering all Europe and Latin America:

Spectrum & Regulatory Advisory (spectrum and bandwidth acquisition advisory to operators, also spectrum interference topics)

NSA to SA Evolutions (5G spectrum architecture and deployment strategy

5G Evolution Proof Points (NSA/SA coverage extension NR mid band link budget, ESS spectrum sharing system simulator and SA strategy)  

Performance Benchmarking (OOKLA speed test and crowdsourced data analytics)

Network Performance Assessment (app coverage, VoLTE, recommended actions)

LTE/NR Product Segmentation (capacity improvement with NR introduction, DC /NR CA coverage extension gain)

LTE Capacity Expansion & Planning (LTE densification, transport capacity, NR introduction new use cases eMBB, FWA)

MBB Coverage & Device Analysis (smart network investment, improve coverage and CA strategy based on UE cap)

NR TDD Build with Precision (360 analysis based on site build, EMF, capacity, app coverage and TCO)

Site Evolution (network inventory & dimensioning)

Hot Topics (Cloud RAN, Open RAN, private network, and NW sharing)

Planning Network Evolutions with 5G Predictions Future 3 Years


   – TOP 15 woman in 5G (perspektywy woman in tech Dec. 2020)

   – Speaker and Mentor for ‚IT FOR SHE‘ Woman Tech Camp 2021

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Applied Data Science – Use Cases and Challenges in the Semiconductor Industry

Dr. Anja Zernig | KAI Kompetenzzentrum Automobil- und Industrieelektronik GmbH Villach |
Friday, November 26, 2021 | 10:00 (CET, 09:00 UTC) | Online:

Abstract: AI has infected the world. Today, there is a huge hype around Data Science activities all over the world, where one of the biggest challenges for the industry is to deliver financial value quickly but also sustainably. In her talk, she will show some examples on latest Use Cases in the area of Data Science within the semiconductor industry, including technical approaches and practical challenges. Further, she will give some personal insights on important enabling factors that make a Data Science project successful.

Bio: Anja Zernig coordinates Data Science projects at KAI Kompetenzzentrum Automobil- und Industrieelektronik GmbH in Villach, which is a 100% subsidiary of Infineon Technologies Austria AG. Dr. Zernig studied Technical Mathematics at the University of Klagenfurt and received her PhD in 2016. Afterwards, she has been applied as a researcher at KAI, focusing on topics like outlier and anomaly detection, pattern recognition, applied statistical methods and Machine Learning techniques. Since 2019 she is coordinating a team of Data Scientists, involved in various national and international funding projects and acts as a link between the industry and academic collaboration partners. She is supervising researchers and students, dealing with innovative data-analytical concepts within the semiconductor production, testing and optimization and publishes latest scientific insights in different conference and Journal papers. Beside this, Dr. Zernig participates in and supports local Data Science activities, e.g. she is part of the organizing team of the Women in Data Science Villach. In recent times, she is focusing on deployment strategies to guarantee sustainable Machine Learning lifecycles.

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RL-Cache: Learning-Based Cache Admission for Content Delivery

Sergey Gorinsky | IMDEA Networks Institute, Madrid |
Friday, November 12, 2021 | 14:00 (CET, 13:00 UTC) | S.0.05

Content delivery networks (CDNs) distribute much of the Internet content by caching and serving the objects requested by users. A major goal of a CDN is to maximize the hit rates of its caches, thereby enabling faster content downloads to the users. Content caching involves two components: an admission algorithm to decide whether to cache an object and an eviction algorithm to decide which object to evict from the cache when it is full. In this paper, we focus on cache admission and propose an algorithm called RL-Cache that uses model-free reinforcement learning (RL) to decide whether or not to admit a requested object into the CDN’s cache. Unlike prior approaches that use a small set of criteria for decision making, RL-Cache weights a large set of features that include the object size, recency, and frequency of access. We develop a publicly available implementation of RL-Cache and perform an evaluation using production traces for the image, video, and web traffic classes from Akamai’s CDN. The evaluation shows that RL-Cache improves the hit rate in comparison with the state of the art and imposes only a modest resource overhead on the CDN servers. Further, RL-Cache is robust enough that it can be trained in one location and executed on request traces of the same or different traffic classes in other locations of the same geographic region.

Sergey Gorinsky is a tenured Research Associate Professor at IMDEA Networks Institute in Madrid, Spain. He joined the institute in 2009 and leads the NetEcon (Network Economics) research group there. Dr. Gorinsky received his Ph.D. and M.S. degrees from the University of Texas at Austin, USA in 2003 and 1999 respectively and Engineer degree from Moscow Institute of Electronic Technology, Zelenograd, Russia in 1994. From 2003 to 2009, he served on the tenure-track faculty at Washington University in St. Louis, USA. In 2010-2014, Dr. Gorinsky was a Ramón y Cajal Fellow funded by the Spanish Government. Sergey Gorinsky graduated four Ph.D. students. The areas of his primary research interests are computer networking, distributed systems, and network economics. His work appeared at top conferences and journals such as SIGCOMM, CoNEXT, INFOCOM, Transactions on Networking, and Journal on Selected Areas in Communications. He served as a TPC chair of ICNP 2017 and other conferences, as well as a TPC member for a much broader conference population. Sergey Gorinsky contributed to conference organization in many roles, such as a general chair of SIGCOMM 2018 and ICNP 2020. He also served as an evaluator of research proposals and projects for the European Research Council (ERC StG), European Commission (Horizon 2020, FP7), COST Association, and numerous other funding agencies.

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Software Developer mit Teamleader Perspektive (M/W)

IoT40 Systems GmbH baut stabile zukunftssichere IoT und AI Lösungen und führt seine
Kunden durch die digitale Transformation zum Erfolg!

„We don’t predict the future – we build it“

Im Zuge unserer Tätigkeiten im Industrie 4.0 Umfeld, haben wir uns auch auf individuelle
Softwareentwicklung spezialisiert und Lösungen ausgearbeitet, die in bestehende ITStrukturen
unserer Kunden nahtlos integriert werden können. Wir beschäftigen uns mit künstlicher Intelligenz
und setzen diese in Produktionsbereich bei Kunden ein. Wir leben unsere Leidenschaft für das Internet
der Dinge voll und ganz aus.

Weitere Informationen zur Stellenausschreibung / Bewerbung finden Sie hier:

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Betreuung ACCESS

Dieses Bild hat ein leeres Alt-Attribut. Der Dateiname ist Fehringer-e1626943117681.jpg

Wir, das Ingenieurbüro Fehringer (IBF) GmbH, sind ein seit über 25 Jahren in Deutschland ansässiges internationales Ingenieurbüro für Elektrotechnik, das in Klagenfurt seit Kurzem eine Dependance hat. Diese möchten wir gemeinsam mit Ihnen auf- und ausbauen.

Unser Schwerpunkt liegt in der Automatisierungstechnik, hier sind wir in klassischen Projekten genauso unterwegs wie in innovativen Pilotprojekten.

Zur Unterstützung suchen wir einen Studenten (m/w/d)

zum Einpflegen von Daten und Programmen in eine Datenbank auf ACCESS-Basis sowie Schaffung einer visuellen Benutzeroberfläche.

Ihre Qualifikationen:

  • Laufendes Studium der Informations- und Kommunikationstechnologie (auch Absolventen sind willkommen)
  • Datenbankkenntnisse
  • Teamfähigkeit
  • Deutsch und Englisch in Wort und Schrift

Was wir bieten:

  • ein kleines Team mit flachen Hierarchien
  • einen modernen Arbeitsplatz in Klagenfurt
  • Platz für eigene Ideen
  • leistungsgerechte Vergütung

Arbeitsausmaß: ca. 5-10 Stunden / Woche

Arbeitsbeginn: So bald als möglich

Ihr Kontakt zu uns:

Schicken Sie Ihre Bewerbungsunterlagen asap per Email an:

Weitere Informationen zu unserem Unternehmen finden Sie unter

Mobil-Tel.: +49 / 171 / 7719096

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Information Security Engineer (m/f/d)

As a leading global supplier of wafer fabrication equipment and services to the semiconductor industry, Lam Research develops innovative solutions that help our customers build smaller, faster, and more power-efficient devices.

We are a company comprised of people who work hard, deliver outstanding results and maintain a sense of humor during even the most challenging times. Our success results from our employees‘ diverse technical and business expertise, which fuels close collaboration and ongoing innovation. We know that our dynamic, global team of exceptional employees is essential to our continued growth.

Join the Lam Research team, where you can play a vital role in the future of electronics and write your own success story.

More information here:

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Standardising the compressed representation of neural networks

Werner Bailer | Joanneum Research, Graz | Friday, June 25, 2021 | 10:00 (CET, 08:00 UTC) | online


Artificial neural networks have been adopted for a broad range of tasks in multimedia analysis and processing, such as visual and acoustic classification, extraction of multimedia descriptors or image and video coding. The trained neural networks for these applications contain a large number of parameters (weights), resulting in a considerable size. Thus, transferring them to a number of clients using them in applications (e.g., mobile phones, smart cameras) benefits from a compressed representation of neural networks.

MPEG Neural Network Coding and Representation is the first international standard for efficient compression of neural networks (NNs). The standard is designed as a toolbox of compression methods, which can be used to create coding pipelines. It can be either used as an independent coding framework (with its own bitstream format) or together with external neural network formats and frameworks. For providing the highest degree of flexibility, the network compression methods operate per parameter tensor in order to always ensure proper decoding, even if no structure information is provided. The standard contains compression-efficient quantization and an arithmetic coding scheme (DeepCABAC) as core encoding and decoding technologies, as well as neural network parameter pre-processing methods like sparsification, pruning, low-rank decomposition, unification, local scaling and batch norm folding. NNR achieves a compression efficiency of more than 97% for transparent coding cases, i.e. without degrading classification quality, such as top-1 or top-5 accuracies.

This talk presents an overview of the context, technical features and characteristics of NN coding standard, and discusses ongoing topics such as incremental neural network representation.


Werner Bailer is a Key Researcher at DIGITAL – Institute for Information and Communication Technologies at JOANNEUM RESEARCH in Graz, Austria. He received a degree in Media Technology and Design in 2002 for his diploma thesis on motion estimation and segmentation for film/video standards conversion. His research interests include audiovisual content analysis, multimedia retrieval and machine learning. He regularly contributes to standardization, among others in MPEG, where he co-chairs the ad-hoc group on neural network compression.

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Internship: Information Technology (f/m/d)

As a leading global supplier of wafer fabrication equipment and services to the semiconductor industry, Lam Research develops innovative solutions that help our customers build smaller, faster, and more power-efficient devices.

This success is the result of our employees‘ diverse technical and business expertise, which fuels close collaboration and ongoing innovation. Join the Lam Research team, where you can write your own success story. Help us solve our customers‘ toughest problems and be part of a company that plays a vital role in the future of electronics.

More information here:

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Edge computing in 5G networks

Benedek Kovács PhD | Senior Specialist, Ericsson R&D at Hungary | Friday, May 28, 2021 |

10:30 (CET, 08:30 UTC) |

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Abstract: We overview the edge computing status from a telecommunication networks perspective, give a definition, introduce an example. We discuss the different driving forces in the telecommunication and cloud industry and go thorugh the different solution proposals. We cover the networking, cloud and management aspects and show the different options using the example.

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Navigation in 360-Degree Video Content: Challenges, Solutions and Opportunities

Klara Nahrstedt | University of Illinois | Thursday, December 17, 2020 | 15:00 (CET, 14:00 UTC) | online

Abstract: With the emergence of  360-degree cameras, VR/AR display devices, ambisonics auditory devices, more diverse 360-degree multi-modal content has become available and with it the challenging demands for the capability of navigating within the 360-degree multi-modal content to enhance users’ multi-modal experience.  In this talk, we will discuss the challenges of navigating through the 360-degree multi-modal content in a HMD-Cloud-based distributed environment, and discuss the concept of the navigation graph to organize the 360-video content for successful delivery and viewing. We will dive into more details of the navigation graph’ concept as one possible direction of potential solutions to represent views-objects-tiles navigation. We will show how navigation graphs are serving as models for viewing behaviors in the temporal and spatial domains to perform a better rate adaptation of tiled media associated with view and object predictions. The experimental results are encouraging and support the claim that the navigation graph modeling provides a strong representation of navigation and viewing patterns of users, and its usage enhances the streaming and viewing quality in 360-degree video applications. We conclude the talk with research opportunities that this area is offering.

Joint work with UIUC collaborators: Dr. Jounsup Park, Mingyuan Wu, Eric Lee, Bo Chen, and UMass collaborators: Ariel Rosenthal, Yash Shah, John Murray, Kevin Spiteri, Dr. Michael Zink, Dr. Ramesh Sitaraman.

Bio: Klara Nahrstedt is the Ralph and Catherine Fisher Professor in the Computer Science Department, and Director of Coordinated Science Laboratory in the College of Engineering at the University of Illinois at Urbana-Champaign. Her research interests are directed toward Internet-of-Things systems, tele-immersive systems, end-to-end Quality of Service (QoS) and resource management in large scale distributed systems and networks, and real-time security and privacy in cyber-physical systems such as power grid. She is the co-author of multimedia books `Multimedia: Computing, Communications and Applications‘ published by Prentice Hall, and ‘Multimedia Systems’ published by Springer Verlag.

She is the recipient of the IEEE Communication Society Leonard Abraham Award for Research Achievements, University Scholar, Humboldt Research Award, IEEE Computer Society Technical Achievement Award, ACM SIGMM Technical Achievement Award, TU Darmstadt Piloty Prize, the Grainger College of Engineering Drucker Award, and the former chair of the ACM Special Interest Group in Multimedia. She was the general co-chair and TPC co-chair of many international conferences including ACM Multimedia, IEEE Percom, IEEE IOTDI and others. Klara Nahrstedt received her Diploma in Mathematics from Humboldt University, Berlin, Germany in 1985. In 1995 she received her PhD from the University of Pennsylvania in the Department of Computer and Information Science. She is ACM Fellow, IEEE Fellow, AAAS Fellow, and Member of the German National Academy of Sciences (Leopoldina Society).

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