Plenary Papers
Alshin Alexander
MPEG standardization: new directions
Biography: Ph.D.in mathematical physics 1998.
Works as assistant vice president in LG Electronics, St. Peterburg R&D Lab.
The main research interests are video and image compression, standardization, numerical calculus. Published 4 monographs, 100+ papers, 150+ international patents. Has many company awards.
Abstract:
The Moving Picture Experts Group (MPEG) has been a cornerstone of global media technology for over three decades, delivering standards that enable interoperable, high quality audio visual experiences across industries. As media consumption shifts toward immersive, interactive, and AI enhanced formats, MPEG’s role is evolving to address new technical and market demands. MPEG’s recent work includes advanced video codecs (VVC, EVC), immersive media frameworks (MPEG I, MIV), and next generation audio (LC3). These standards underpin streaming, broadcasting, XR, and cloud based media services worldwide. MPEG emerging directions are: AI‑assisted compression and enhancement for video and images, Immersive media formats: volumetric video, light‑field, holographic content, Point cloud compression and Gaussian splats for 3D scene representation, Neural network‑based codecs, Low‑latency streaming and real‑time rendering.
Boldyrev Alexander
Developing SDR-based test setups for modern 5G communication network devices
Biography:
Head of Radio Electronics Department, Software-Defined Radio (SDR) Expert.
Education: Bauman Moscow State Technical University, Financial University under the Government of the Russian Federation.
Over 10 years of experience developing test and measurement systems in the aerospace and telecommunications industries.
Abstract:
Modern SDR solutions have come a long way from being a tool for amateur radio enthusiasts to a key element of complex test systems for telecommunication developments. Over many years of using SDR equipment, we have encountered various challenges in applying current SDR solutions to measuring and testing broadband communication systems. Often, the performance of commercial devices is insufficient to address the challenges of advanced communications research, forcing us add additional tools such as FPGAs, high-precision interchannel synchronization, additional digital signal processing, etc.
The report will analyze the development of SDR technologies from a simple ADCs to RFSoC platforms on a chip, as well as their applications for satellite communication systems and fifth-generation (5G) communication systems.
Son Thai Le
High-capacity, high density optical interface for AI/ML
Biography:
Son Thai Le is Director of Systems Design Architecture Engineering at Ciena, NJ, USA. Prior to the current role at Ciena, he was a director at Nubis Communications (acquired by Ciena in Oct 2025) from 2022-2025. Son Thai Le was a Member of Technical Staff at Nokia Bell Labs from 2016 – 2022 where he conducted research in high-speed optical transmission systems, including direct-detection for data center applications and coherent detection for metro and long-haul transmissions. Son Thai Le is a frequent speaker at top conferences in fiber optical communications such as OFC and ECOC. He has published more than 120 research papers and holds more than 10 patents in the field of fiber optical communications and 5G/6G mobile fronthaul. Son Thai Le has been awarded as “Innovator of the Year Germany 2018” and “Innovator Under 35 Europe” by MIT Technology Review in 2028. He is also the recipient of the “Best Paper Award” prize from the German Information Technology Association (ITG) in 2018. Son Thai Le is a Senior Member of IEEE and he was elevated to Optical Fellow in 2025. Son Thai Le was included in the list of Photonics100 2026.
Abstract:
Advanced Machine Learning and Artificial Intelligence (ML/AI) engines ask for hundreds of Tbps of full-duplex interconnect (input/output, I/O) across multi-row and multi-bay clusters at edge I/O densities in the Tbps/mm range. This emerging requirement substantially exceeds the I/O needs of the latest generation of Ethernet switches. As a result, a new class of high-speed, low-latency, low-power, linear-drive high-density optical interface (HDI/O) has been actively developed over the last few years. The stringent requirements in performance and flexibility in deployments, however, have imposed many challenges which ask for further innovations and also significant standardization efforts.
Klimakov Andrey
AI in next generation Wireless Networks: new challenges and opportunities
Biography:
Lomonosov Research Institute, Mathematical Modeling and Algorithms Laboratory.
Wireless RRM Team Leader
Abstract:
The report will discuss the main areas of research in the field of machine learning and artificial intelligence for the next generation 6G wireless communication technologies. Current approaches to the problem of wireless radio resource allocation will be reviewed, including AI/ML approaches and classical optimization, as well as new challenges associated with wireless multi-cell network architectures and improving the quality of AI/ML models by changing the training procedure and analyzing the available data for quality, diversity and scalability.
Frolov Alexey
New error-correcting codes and decoding algorithms for 6G wireless networks
Biography:
Dr. Alexey Frolov received the M.Sc. degree in computer science from Bauman Moscow State Technical University (BMSTU) in 2010, the Ph.D. degree in mathematics from the Institute for Information Transmission Problems (IITP), Russian Academy of Sciences (RAS), in 2012 and the D.Sc. degree in mathematics from Moscow Institute of Physics and Technology (MIPT) in 2021. He is currently a Full Professor at the Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia. His research interests include information theory and its applications in telecommunications, storage systems, and other areas. He was a recipient of the IEEE GLOBECOM Communication Theory Symposium Best Paper Award in 2020, the Russian Government Award in Science and Technology for Young Scientists in 2016 and the Moscow Government Award for Young Scientists in 2013. He was the chairman of the IEEE Russia Information Theory Society Chapter from 2021 to 2022. He serves as an Editor for IEEE Transactions on Communications.
Abstract:
Typically, the decoding algorithm governs the choice of the particular error-correcting code. For example, the 3GPP New radio standard (5G) utilizes low-density parity check (LDPC) codes as error-correcting codes for the data channel and polar codes for the control channel. Belief-propagation decoding algorithm drives the choice of the LDPC codes, and successive cancellation list decoder dictates the design of the polar code. As a result, standards adopt not the best codes but the best codes under particular decoding methods. It is believed that LDPC and polar codes have almost reached their performance limits making further improvements problematic. In this talk we consider new decoding approaches and corresponding coding schemes, namely 1) decoding algorithms based on mathematical programming (linear and quadratic) methods; 2) deep neural networks for code design and decoding; 3) sparse regression codes and approximate message passing decoding.
Pozhar Vitold, Machikhin Alexander
Acousto-optical techniques and instruments for spectral analysis and imaging spectroscopy
Scientific Technological Center of Unique Instrumentation, Russian Academy of Sciences (STC UI RAS)
Biography:
Pozhar Vitold, Head of Department of Acousto-optical information systems, Professor at Moscow Bauman State Technical University,
Professor at National Research Nuclear University “MEPhI” (Moscow)
born in 1958, graduated from Moscow Institute of Physics and Technology (MIPT, Dolgoprudny, Moscow Region), Candidate of Science (PhD) since 1987, Doctor of Physics and Mathematics since 2005
Machikhin Alexander, Head of Acousto-optical spectroscopy Laboratory in STC UI RAS (Moscow), graduated from Moscow Bauman State Technical University (2007), Associated professor at National Research University “MPEI” (Moscow), Candidate of Science (PhD) since 2011, Doctor of Technology since 2019
Basic fields of activity: acousto-optics, optics, acoustics, radiophysics, spectrometry, optical gas analysis, environment monitoring, spectral imaging, differential spectroscopy, metrology.
Abstract:
Nowadays, instruments and technologies detecting and processing spatial-spectral data form the basis for various industrial, biomedical, agricultural and other specialized systems capable of solving many urgent problems. Among the different technical platforms implementing hyperspectral technologies, acousto-optical devices occupy a unique place due to the combination of exceptional features. The report presents a family of original (STC UI RAS) acousto-optical instruments and techniques for spectral and hyperspectral analysis as well as for spectral imaging. Some examples of their practical applications are discussed.
Özgür Gürbüz
Resource alloction for THZ drone communications with realistic antennas and mobility patterns
Biography:
Özgür Gürbüz received her B.S. and M.S degrees in Electrical and Electronics Engineering at Middle East Technical University, in 1992 and 1995, respectively. She received her Ph.D. degree in Electrical and Computer Engineering from Georgia Institute of Technology in 2000. From 2000 until 2002 she worked as a researcher and systems/algorithms engineer for Cisco Systems, in Wireless Access and Wireless Networking Business Units. As of September 2002, Dr. Gurbuz joined the Faculty of Engineering and Natural Sciences at Sabanci University, where she is now a Professor. Her research interests are in the field of wireless communications and networks, specifically design of link and higher layer network algorithms/protocols for emerging physical layer techniques including full-duplex communication, cooperative communication, MIMO, smart antennas. Recently, she has been working on full-duplex communication, digital self-interference cancellation and applications of machine learning in wireless communications/networks and THz communications. She is a member of IEEE and IEEE Communications Society.
Abstract:
This work considers Terahertz (THz) drone communications by applying various resource allocation schemes with practical THz antennas within the frequency range of 0.75-4.4 THz under realistic mobility and misalignment scenarios, ensuring a more accurate representation of real-world conditions. Through numerical simulations, we unveil the real capacity achievable within the realm of Tbps up to 100 meters range, when drones are in motion and subject to alignment and moderate misalignment. However, when exposed to actual mobility traces, the performance of all resource allocation schemes experiences a significant drop, sometimes up to six orders of magnitude, due to occasional reverse orientations of antennas. Consequently, the need arises for active beam control solutions to maintain the performance of THz drone networks. These findings highlight both the significant strides made in THz technology and the remaining challenges for the integration of THz band drones into the fabric of 6G networks.