CCI xG Testbed Team

Aloizio Da Silva

DaSilva's primary area of research is in wireless networking communication, focusing on NFV, SDN, and SDR on large-scale testbed experimentation, as well as radio access networks and core networks. DaSilva is also research faculty at the Bradley Department of Electrical and Computer Engineering at Virginia Tech.

Read more about Aloizio Da Silva

• Sayanta Seth
• Focuses on NextG/6G wireless communications, hardware-in-the-loop testbed development, and dynamic spectrum sharing. His work emphasizes FR3/mmWave systems, O-RAN, cognitive radio networks, and beamsteering optimization for next-generation wireless networks.
• Read more about Sayanta Seth

• Harshit Sai Teja Doddi
• Network Administrator for CCI xG Testbed

• Asheesh Tripathi
• Research interests include O-RAN-based NextG wireless networks, software-defined radio-based citizens broadband radio service networks, and machine learning.

• Md. Habibur Rahman
• Research Focus: Advanced AI/ML for O-RAN-enabled 5G and emerging 6G networks, focusing on intelligent radio resource management, network-slice QoS optimization, energy-efficient RAN orchestration, AI/ML pipeline development, service automation, and AI-RAN. Research involves developing and experimentally validating AI-driven solutions using SDR-based 5G testbeds and open-source O-RAN platforms.
• Contributed Research Projects:
  • Commonwealth Cyber Initiative (CCI): AI/ML-driven O-RAN research on intelligent resource management, Near-RT RIC orchestration, and AI/ML services automation.
  • Transformer-Based Inter-Cell Coordination on OCUDU (SoftBank Corp.): AI-driven multi-cell coordination and interference-aware Resource allocation on CUDA-accelerated OCUDU platform development.

• Mahesha Viduranga
• Research Focus: O-RAN security, interoperability, and trustworthy automation for 5G and emerging 6G networks, focusing on security challenges across O-RAN open interfaces, cross-plane threat analysis, Zero Trust mechanisms, and AI/ML-assisted adaptive network management. Research involves experimentally identifying security gaps, evaluating their system-level impact, and developing practical mitigation and automation mechanisms using commercial and open-source O-RAN platforms. This work has resulted in publications and demonstrations at ACM WiSec and IEEE MILCOM.
• Contributed Research Projects:
  • NTIA ACCoRD Project - Open Fronthaul Security Testing: Conducts security testing of the O-RAN Open Fronthaul across different multi-vendor O-RU and O-DU pairings, evaluating security configurations, protocol behavior, and interoperability in realistic deployment environments.
  • SoloRAN - Self-Service O-RAN Experimentation for xApp Development and Evaluation (ACM MobiCom 2026, Demo): Developing a self-service experimentation platform for the CCI xG Testbed that simplifies O-RAN xApp development, deployment, testing, and evaluation through reproducible wireless-network experiments.

• Ishtiaque Ahmed Toke
• Research Focus: Trustworthy AI for O-RAN-enabled 5G and emerging 6G networks, focusing on LLM- and agent-assisted network management, AI-driven lifecycle automation, standards-grounded verification, AI-assisted RAN test analysis, and the safe integration of AI into network operations. Research involves developing model-agnostic frameworks that let AI support network decisions while keeping them accountable to 3GPP and O-RAN standards and operator policy, validated on open-source O-RAN platforms.
  
• Contributed Research Projects:
  • NTIA ACCoRD Project - Open Fronthaul Interoperability Testing: Conducts interoperability testing of the O-RAN Open Fronthaul across different multi-vendor O-RU and O-DU pairings, evaluating how control, user, synchronization, and management plane functions interwork between vendors in realistic deployment environments.
  • rApp Verify: A Pre-Deployment Trust Gate for O-RAN rApps (ACM MobiCom 2026, Demo): Checks O-RAN rApps against 3GPP and O-RAN standards before deployment, with LLM assistance whose claims are independently verified.
  • GLASS: Gated Link-Aware SGP4 State Correction for GNSS-Degraded Tactical LEO-NTN (IEEE MILCOM 2026): Uses a safety-gated learned model to improve satellite link predictions when GNSS or fresh orbital data is unavailable.
  • AMORA (AI-driven Metrics Optimization for RAN Analysis): Self-contained web app that turns large RAN test data files into KPI summaries, charts, and engineering reports, with a private local LLM that answers questions about each run so engineers can troubleshoot faster without data leaving the system.
  • Self-hosted LLM based on Gemma 4, deployed on the lab's own GPU stack so research data stays on-premises.

• Manikantha Rayudu
• Focusing on federated learning to enhance reliability and privacy in IoT, extending to O-RAN systems.

• Abdullah Al Safi 
• Research Focus: AI-RAN, Cuda accelerated OCUDU, Agentic AI in Next Gen Wireless Network, TN-NTN Coexistence, dApp/E3 Interface
• Contributed Research Projects:
  • Commonwealth Cyber Initiative (CCI): Deploy and validation of open-source 5G RAN stacks with multiple O-RUs, SDRs, COTS UE. Full private 5G testbed developed - NVIDIA GH200, NI X410, SONY Xperia phones, Open 5GS, Cuda Accelerated OCUDU
  • Softbank Project on Multi-Site Scheduling (MSS) for Inter Cell Coordination & MU-MIMO: Full operation indoor and outdoor 5G testbed deployment utilizing open-source software stack. Train and implementation of native ML model into O-DU to coordinate between multi-cells. Extensive modification of RAN stack to fit ML inference into per TTI UL scheduler. Enable and deploy MU-MIMO in OCUDU.

• Junkai Lu
• Research Focus:  AI/ML for O-RAN-enabled 5G and emerging 6G networks, focusing on AI-native real-time radio resource management, multi-cell and multi-site coordination with interference-aware scheduling, uplink multi-user and distributed MIMO, GPU-accelerated RAN (AI-RAN), and end-to-end AI/ML pipelines from over-the-air data logging to model deployment. Research involves developing and experimentally validating AI-driven solutions on an SDR-based 5G testbed with commercial UEs and the open-source O-RAN platform OCUDU.
• Contributed Research Projects:
  • Commonwealth Cyber Initiative (CCI) xG Testbed - AI-RAN on OCUDU: GPU-accelerated 5G RAN with an in-slot AI scheduler running TensorRT models inside the DU.
  • Multi-Site Scheduling and Uplink Multi-User MIMO on OCUDU (SoftBank Corp.): a multi-cell uplink scheduler that plans co-channel cells jointly at every slot from learned inter-user collision costs, and an uplink MU-MIMO joint receiver in the O-DU-low that pairs co-channel users across cells, both on the CUDA-accelerated OCUDU platform.
  • Distributed MIMO (D-MIMO) Uplink Joint Reception: cell-free uplink reception across multiple USRP X410 sites on a shared 10 MHz/PPS reference, channel-aware user pairing and MMSE joint detection with commercial phones, evaluated against multi-cell scheduling as coordination versus cooperation.

• Shuyan(Apple) Zhou
• Research Focus: Open Radio Access Networks (O-RAN) for 5G/6G, focusing on fronthaul delay management, interoperability testing (IOT), network performance optimization, and cybersecurity. Research involves real-time communication, latency analysis, and experimental validation using SDR-based testbeds and open-source RAN platforms.
• Contributed Research Projects:
  • O-RAN Delay Management: Fronthaul latency analysis, interoperability testing, and performance evaluation using OCUDU.
  • Network Security and Validation: Cyberattack detection, system behavior analysis, and security evaluation of IoT and cyber-physical systems.
  • Real-Time System Testing: Experimental validation, fault detection, and performance monitoring of distributed systems, with applications to reliable O-RAN operations.

• Jacek Kibilda
• Modeling and technology design for next-generation mobile networks using stochastic geometry, AI, and optimization.

• Joao Santos
• Focuses on 5G testbed and AI assurance; integrating SDR with SDN for programmable networks

• Gustavo Zanatta Bruno

• Role: Visiting PhD Scholar

   

•  Abhishek Kumar
• Role: Visiting PhD Scholar

• Zeeshan Shah
• Role: Principal Engineer, Verizon- 5G ORAN Lab

• Focus: 5G O-RAN- ACCoRD Testing and Integration Engineer- Support Day to Day ORAN ACCoRD testing activities