Dr. Evangelos Vlachos
Tenure-track Researcher · ATHENA RC
Dr. Evangelos Vlachos
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ISAC
Distributed MPC for Directional UAV Networks: Co-design of Motion and Hybrid Beam Alignment
This paper addresses the coupled control and communication problem in UAV networks operating at millimeter-wave (mmWave) frequencies. …
Hardware-Aware SE(3) Control Barrier Functions for Counter-UAS Interceptors with Directed Energy Payloads
Drone-mounted directed energy payloads — RF jammers and High Power Microwave (HPM) sources — offer a reusable Counter-UAS capability, …
Multi-Functional Diversity via Flexible Spatial Partitioning for Massive MIMO ISAC
In massive MIMO Integrated Sensing and Communications (ISAC), conventional contiguous sub-array partitioning limits spatial degrees of …
Paper Submitted to IEEE Transactions on Wireless Communications
We submitted a paper on multi-functional diversity via flexible spatial partitioning for massive MIMO ISAC to IEEE TWC.
Mar 5, 2026
1 min read
Paper
Workshop Proposal Submitted to EuCNC & 6G Summit 2026
We submitted a proposal to host a half-day workshop at EuCNC & 6G Summit 2026 (Malaga, Spain, June 2–5) on Integrated Sensing and Communications for the 6G Sky, bridging technology and regulation in U-Space.
Jan 22, 2026
1 min read
News
New Paper: ISAC for AAM: Integrated Sensing and Communication Technology for Advanced Air Mobility
Researchers develop an integrated sensing and communication technology to enhance safety and efficiency in advanced air mobility vehicles.
Oct 6, 2025
1 min read
Paper
New Paper: Flexible hybrid precoding for integrated sensing and communications
Researchers propose flexible hybrid precoding schemes to optimize joint sensing and communication performance in resource-constrained wireless systems.
Jul 1, 2025
1 min read
Paper
SPLASH: Signal Processing for Joint Sensing and Communications in U-Space
Co-design of sensing, communication and control protocols for next-generation U-Space services.
Jan 1, 2023
New Paper: Compressed sensing for efficient encoding of dense 3D meshes using model-based Bayesian learning
This research develops a model-based Bayesian learning approach to efficiently encode dense 3D meshes using compressed sensing, achieving higher compression ratios while preserving visual quality.
Jan 1, 2017
1 min read
Paper
New Paper: Compressed sensing techniques for decision feedback equalization of sparse wireless channels
A novel application of compressed sensing techniques significantly improves decision feedback equalization of sparse wireless channels by exploiting filter sparsity.
May 1, 2012
1 min read
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