Fellows

Name: Mohammad Rehan

DC Number: DC-10

Institution: EURECOM

Supervisor: Professor Adlen Ksentini

Brief CV:

Mohammad Rehan is a Doctoral Researcher at EURECOM, France, under the 6G-TERRAIN Marie Sklodowska-Curie Actions Doctoral Network (MSCA-DN)project. His PhD topic, “On sensing capabilities of gNB FR2 towards optimized beamforming in an end-to-end system,”
aims to design sensing-based mechanisms for autonomous and efficient beam tracking that minimize scanning overhead while maximizing the SNR at both the UEs and the gNB. His work explores the integration of sensing capabilities into mmWave gNBs, leveraging transversal technologies such as computer vision to reduce beam tracking overhead. The research employs DL, RNNs, and DRL to fuse visual and radio-based sensing for adaptive beam management in both LoS and NLoS conditions. The developed algorithms will be further validated in an end-to-end testbed using OpenAirInterface (OAI).
Before joining EURECOM, he worked on the project “Active RIS-Assisted Satellite Communication Systems” at Indian Institute of Science (IISc) Bengaluru, where he contributed to the design of joint transmit and reflect beamforming to maximize sum-rate performance for multiuser MISO systems under power constraints at the satellite and active RIS. He earned his M.Tech in Communication & Information Systems from Aligarh Muslim University (AMU), Aligarh, India, where he graduated first in his class. His M.Tech thesis, titled “Spectral and Energy Efficiency Performance of Massive MIMO-OFDM Systems,” focused on investigating methodologies to enhance spectral and energy efficiency in massive MIMO systems His main research interests include 6G FR2 beamforming with multi-sensing integration, AI and vision-assisted beam management, RIS, Massive MIMO systems and ML for wireless communications

Name: Mehdi Hassani

DC Number: DC-05

Institution: EURECOM

Supervisor: Professor Adlen Ksentini

Brief CV:

“Mehdi Hassani is a Doctoral Candidate at EURECOM  within the 6G-TERRAIN Marie Skłodowska-Curie Doctoral Network. His PhD research focuses on enhancing semantic understanding and feasibility assessment in intent-based management systems, aiming to develop intelligent mechanisms for autonomous network management in 6G. His work leverages Large Language Models (LLMs), Semantic Role Labeling (SRL), and Knowledge Graphs (KGs) to improve semantic validation and conflict detection, combined with time-series prediction and reinforcement learning for feasibility assessment and resource optimization in AI-native networks.
Mehdi holds a State Engineering Degree in Computer Science, specializing in Computer Systems, from the Higher National School of Computer Science (ESI Algiers), Algeria’s leading ICT engineering institution. Prior to joining the 6G-TERRAIN network, he worked as an IT Solutions and Network Specialist at Sonatrach, contributing to large-scale system and network infrastructure management. He also completed a research internship at EURECOM, where he explored Explainable AI (XAI) and Machine Reasoning for intelligent resource management in 6G networks.
His main research interests include AI-driven network automation, semantic reasoning, cybersecurity, and machine learning for network intelligence.

Name: Martino Chiarani

DC Number: DC-01

Institution: Iquadrat Informatica S.L

Supervisor: Dr. Kostas Ramantas

Brief CV:

Martino Chiarani earned his Master’s Degree in Information and Communications Engineering from the University of Trento, Italy, in 2025. As part of his academic journey, he conducted a research internship at Iquadrat Informatica S.L. (IQU) in Barcelona, Spain, where he worked for his thesis on the design of a scalable, eXplainable AI (XAI)-driven client selection strategy for federated learning, applied to 6G network slicing and resource allocation scenarios. During the internship, he developed and evaluated AI algorithms for optimizing network performance, managing resources, and improving connectivity, focusing on federated learning frameworks and the integration of XAI techniques to ensure transparency in decision-making processes.

Martino is currently pursuing his PhD as a Marie Curie Doctoral Candidate at Iquadrat within the 6G-TERRAIN project (DC01/IQU-1). where he investigates native AI decision automation in telecommunication networks, aiming to support real-time, conflict-free adaptation of system intents. His work includes the development and validation of conflict resolution schemes using the IQU Beyond 5G (B5G) testbed, grounded in measurement-based and real-world experimentation. Through this research, Martino contributes to advancing self-adaptive and intelligent management solutions for future 6G network infrastructures.

Name: Dimitrios Tsoukalas

DC Number: DC-06

Institution: Iquadrat Informatica S.L.

Supervisor: Prof. Christos Verikoukis, Dr. Kostas Ramantas

Brief CV:

Dimitrios Tsoukalas holds an Integrated Master’s Degree in Information and Communications Systems Engineering from the University of Aegean, Greece, completed in 2023. His Master’s thesis investigated Orthogonal Time Frequency Space (OTFS) Modulation for high-speed telecommunications applications, with a focus on signal processing using MATLAB to compare OTFS and Orthogonal Frequency Division Multiplexing (OFDM) technologies. In 2025, he graduated from a Postgraduate Program in AI & ML: Business Applications at The University of Texas at Austin, where he developed expertise in machine learning techniques, including neural networks, large language models (LLMs), and reinforcement learning.
Dimitrios has gained industry experience as a Full Stack Developer at Itec GmbH in Austria, where he developed internal web applications. As a Machine Learning Engineer Intern at Desion GmbH in Germany, he designed a 3D simulation leveraging reinforcement learning and the Deep Deterministic Policy Gradient (DDPG) algorithm to train robotic systems for real-world tasks, such as catching a moving cloth using a robotic hand and 3D camera.
Currently, Dimitrios is a Marie Curie Doctoral Candidate at Iquadrat in Barcelona, Spain, as part of the 6GTERRAIN project (DC6: IQU-2). His research focuses on intent translation and actuation, exploring LLM-based systems to translate human language into Infrastructure Level Intent (ILI) and implementing self-managed control loops for intent actuation in next-generation 6G networks. His work aims to advance intelligent and autonomous network management for future telecommunications systems.