Artificial Intelligence (AI) will be the dominant technology of the future and will impact every corner of society. In particular, AI / ML (machine learning) will shape how communication networks, a lifeline of our society, will be run. Many companies in the ICT sector are exploring how to make best use of AI/ML. ITU has been at the forefront of this endeavour exploring how to best apply AI/ML in future networks including 5G networks. The time is therefore right to bring together the technical community and stakeholders to brainstorm, innovate and solve relevant problems in 5G using AI/ML. Building on its standards work, ITU is conducting a global ITU AI/ML 5G Challenge on the theme “How to apply ITU’s ML architecture in 5G networks”.
Participants will be able to solve real world problems, based on standardized technologies developed for ML in 5G networks. Teams will be required to enable, create, train and deploy ML models (such that participants will acquire hands-on experience in AI/ML in areas relevant to 5G). Participation is open to ITU Member States, Sector Members, Associates and Academic Institutions and to any individual from a country that is a member of ITU.
Interested in further information about the ITU AI/ML in 5G Challenge?
or selecting a problem statement?
fill out the ITU AI/ML in 5G Challenge Participants Survey
Cash Prizes: The ITU AI/ML in 5G Challenge has set up prize pools of different sizes to reward outstanding teams totalling to around 20, 000 CHF.
ITU AI/ML 5G Challenge Timeline
- Test dataset release: 15-30 September 2020
- Score-based evaluation phase: 1-15 October 2020
- Submission Deadline: 15 October 2020
- Provisional ranking of all the teams: 16 October 2020
- Top 5 solutions submit their code and documentation:
31 October – 6 November 2020
- Winners (top 3) official announcement: 20 November 2020
- Awards and presentation: 15-17 December 2020
Challenge Related Information
- Invitation Letter
- ITU AI/ML 5G Challenge: Participation Guidelines
(1st June, 2020)
- ITU AI/ML 5G Challenge: Summary Slides
(14th September, 2020)
- ITU AI/ML 5G Challenge: Challenge Management Guidelines
(5th August, 2020)
- Problem statements and data resources
(25th August, 2020)
- Sponsorship Inquiries
(13th April, 2020)
- Challenge Management Board
ITU AI/ML 5G Challenge Management Board
Mostafa RAN AI and Data Analytics Vodafone distinguished engineer is a globally recognized authority in Digital Transformation and RAN strategy, design and optimization, applying AI/ML to new tools via using new innovative AI concept. He is also Chairman for ITU Network 2030, co-chairman in ITU FGML5G WG1, ETSI POC rapporteur chair and Board Member advisor for The AUC. Distinguished Engineers community consists of 15 world class members (Professors and Highest standard Engineering experts worldwide), shaping the future of the technology worldwide by researches and technical consultancies. Mostafa holds a BSc in Electronics & Telecommunication and is undertaking MSc in Nano-technologies & Artificial Intelligence. He holds 3 patents, the 4th in progress and has authored/contributed to numerous publications and participation regarding AI, Cognitive Networks in ITU-ETSI-GSMA.
Dr. Jun Liao is an Artificial Intelligence (AI) Director (Senior Engineer of professor level) of China Unicom Network Technology Research Institute. Dr. Liao received his Ph.D. Degree in Computer Application Technology from University of Electronic Science and Technology of China, and conducted his postdoctoral study in Communication and Information System from Beijing University of Posts and Telecommunications. He serves as the Head of AI Planning of China Unicom, Deputy-head of Standardization Group of China Artificial Intelligence Industry Development Alliance (AIIA). Dr. Liao has been working in areas of Computer, Communications and Internet for more than two decades, including communication network and terminal intelligence so that he has a wide knowledge of the telecommunication network, big data of terminal and terminal intelligence. He led an AI team not only to carry out research in the fields of network intelligence, consumer Internet intelligence and industrial Internet intelligence but also to commit to promoting in-depth cooperation with Tencent, Baidu, Alibaba and other Internet companies in the field of AI. He has published more than 40 papers, many of which are indexed by SCI and EI, and has also won many patents and software copyrights and published a monograph. Many research outcomes are adopted by standardization organizations such as ITU-T, ETSI, CCSA, AIIA, etc.
Paul Patras is a Lecturer (Assistant Professor) and Chancellor’s Fellow in the School of Informatics at the University of Edinburgh, where he leads the Internet of Things Research Programme. He received his Ph.D. from University Carlos III of Madrid, along with an outstanding dissertation award. He was a Research Fellow at the Hamilton Institute in Ireland and held visiting research positions at the University of Brescia, Northeastern University, TU Darmstadt, and Rice University. He has co-authored 35 peer-reviewed publications, some of which appeared in top-tier venues including IEEE InfoCom, ACM MobiHoc, and IEEE Transactions on Mobile Computing. He has served on the technical program committee of 40+ international conference, including IEEE MASS, IEEE GLOBECOM, and TMA. He sits on the steering committee of ACM WiNTECH, serves as an associate editor of IEEE Communications Letters, and is a senior member of the IEEE. His research interests include mobile intelligence, performance optimisation in mobile networks, security and privacy.
Dr. Aki Nakao is a professor in Applied Computer Science at the University of Tokyo. He received Ph.D. degree in Computer Science from Princeton University. He has been teaching at the University of Tokyo since 2005, leading research group at Nakao Research Laboratory pursuing networked systems. His main study areas include, but are not limited to, SDN, NFV, Network Virtualization, In-Network Processing for Smartphones, Wearables and Cloud interactions, etc.
Liya Yuan is an open source & standardization engineer in ZTE, focusing on the field of AI for telecommunication network. She is currently the Technical Steering Committee (TSC) chair of AI project Adlik, which is incubated in Linux Foundation AI Foundation. She also takes an active part in ITU-T standardization activities and is the main editor of ITU-T FG ML5G specifications on ”Serving framework for ML models in future networks including IMT-2020″.
Dr Salih Ergut has more than 15 years of experience in the telecommunication domain in academia and industry. He has worked for vendor and operator companies in the sector including Ericsson Wireless (San Diego, CA), Ericsson Silicon Valley, Aware (Boston, MA), Nextwave (San Diego, CA), Turk Telekom Group (Istanbul, Turkey) and is currently working at Turkcell 5G R&D team in Istanbul, Turkey. He received his BS in Electrical Engineering from Bilkent University (Ankara, Turkey), MS in Electrical & Computer Engineering from Northeastern University (Boston, MA), and PhD in Electrical & Computer Engineering from University of California San Diego (La Jolla, CA). His research interests include wireless communications, machine learning, big data technologies, 5G technologies, SDN, NFV, and IoT.
Cheng Qiang, he is senior engineer of China Academy of Information and Communications Technology. He serves as Vice Chairman of ITU-T FG-ML5G from 2019-2020 and the Chairman of Telecom Project Group of Artificial Intelligence Industry Alliance of China from 2016. He engaged in broadband network technology and artificial intelligent research, presided over the drafting of more than 20 communications industry standards and China national standards. He will give a welcome speech from ITU and AIIA, and a brief introduction of AI/ML challenge.
José Suárez-Varela received his B.Sc. and M.Sc. degrees in Telecommunication engineering from the University of Granada (UGR), in 2014 and 2017 respectively. He is currently pursuing a Ph.D. at the Barcelona Neural Networking Center (BNN-UPC). During 2019, he was a visiting researcher at the University of Siena, where he was investigating about Graph Neural Networks with some pioneering researchers of the Artificial Intelligence (AI) field. His main research interests are in the field of network AI, particularly in the application of Graph Neural Networks for network control and management. He is also interested in traffic measurement and classification, and their application in Software-Defined Networking.
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