Research

My research develops intelligent, secure, and experimentally validated wireless systems. I combine communication and signal-processing theory, machine learning, software implementation, and experimental evaluation to address the reliability, security, and adaptability of next-generation wireless networks.

A defining feature of my research is the translation of theoretical and algorithmic advances into reproducible implementations using software-defined radios, Open RAN platforms, cellular systems, national wireless testbeds, and field-deployable experimental platforms. My current research program is organized around the following four interconnected areas.

Wireless Security and Automated Network Testing

The growing programmability and complexity of cellular systems create attack surfaces that cannot be evaluated adequately through static analysis alone. My research develops automated and experimentally grounded methods for identifying, reproducing, measuring, and mitigating security vulnerabilities across wireless physical, protocol, and network-control layers.

This direction includes adversarial testing of cellular and Open RAN systems, physical-layer attacks and defenses, behavioral monitoring, security evaluation of intelligent network applications, and low-latency detection mechanisms. A central goal is to transform wireless security testing from isolated manual experiments into systematic and reproducible evaluation frameworks.

Representative topics: cellular security testing; O-RAN threat analysis; jamming and spoofing; anomaly detection; physical-layer security; resilient protocol operation.

[Gallery picture]

Soft-T UE Architecture

[Gallery picture]

UAV-assisted physical layer security.

Trustworthy and AI-Native Open RAN:

Open RAN introduces programmability, intelligence, virtualization, and open interfaces into cellular networks, but these capabilities also create new challenges involving reliability, security, interoperability, and trustworthy automation. My research develops learning-based control, optimization, testing, and security mechanisms for Open RAN systems, with particular emphasis on near-real-time applications, network slicing, spectrum management, anomaly detection, and experimentally validated network intelligence.

This work combines algorithm development with implementation and evaluation using software-defined radios, cellular protocol stacks, RAN Intelligent Controller platforms, and wireless testbeds. The objective is to enable Open RAN systems that remain adaptive and dependable under changing traffic, interference, mobility, and adversarial conditions.

Representative topics: AI-enabled RAN control; xApp and rApp security; network slicing; spectrum sharing; RAN experimentation; trustworthy wireless intelligence.

[Gallery picture]

Next-Generation O-RAN Architecture.

[Gallery picture]

O-RAN-based LSTM anomaly detection and secure slicing xApps

UAVS WITH RECONFIGURABLE INTELLIGENT SURFACES: APPLICATIONS, CHALLENGES, AND OPPORTUNITIES

The reconfigurable intelligent surface (RIS) is a candidate 6G technology that enables new wireless transmission patterns by controlling the signal propagation and the communications channel. TheRIS facilitates reflection of the incident radio waves, which can be controlled in real-time to shape the electromagnetic signal and steer it in the desired direction. Therefore, to further expand my previous UAV research at the physical layer, I have proposed the joint integration of UAV and RIS under a novel framework called aerial RIS (ARIS). With such direction, my research has focused on improving the achievable data rates of ground users in different scenarios by employing the ARIS to support terrestrial wireless networks. Optimization of the transmission data rates in such cases are NP-hard under the constraints of UAV trajectory, power, and phaseshifts. Therefore, I have proposed an iterative mathematical tool and RL algorithm to solve these optimization problems by jointly designing the reflection coefficients of the RIS passive elements, active beamforming of the transmitter, and UAV trajectory. The obtained results from this research open many research directions to be investigated in the future, such as applying this solution for improving the secrecy rate of ground users while trying to disrupt the performance of attackers by arbitrarily controlling the attacker’s channel. Other future directions for both ground and aerial RIS include as the interaction between various RISs, doppler resilience of phase-shifts, direct/indirect path analysis, and signal processing. In addition to expanding the scope of my research to enable cutting-edge contributions to emerging RIS for integrated sensing, computing, and localization in different resource-restricted wireless communication networks such as IoT, internet-of-everything (IoE), UAV, and vehicle-to-everything (V2X).

[Picture]

Aerial RIS Usecases for Advanced Wireless Networks.

Integrated Sensing and Communication (ISAC):

Integrated sensing and communication enables wireless infrastructure to support environmental perception while continuing to deliver communication services. My research investigates signal-processing, waveform, estimation, and learning methods that improve target detection, localization, scene understanding, and sensing reliability under communication and hardware constraints.

Current work explores sensing observability, sparse recovery, high-mobility waveform processing, and physics-grounded learning for wireless sensing. I am particularly interested in moving beyond simulation-only evaluation by implementing and validating sensing algorithms using software-defined radios and configurable wireless platforms.

Representative topics: ISAC observability; target detection; OFDM and AFDM sensing; sparse delay-Doppler recovery; physics-guided learning; SDR-based sensing experiments.

[Gallery picture]

Movable antenna and reconfigurable intelligent surfaces (MARIS)-aided ISAC.