collaborators

5 papers

eess.SY2025

A Vertical Approach to Designing and Managing Sustainable Heterogeneous Edge Data Centers

Aikaterini Maria Panteleaki, Varatheepan Paramanayakam, Vasileios Pentsos +3

The increasing demand for Artificial Intelligence (AI) computing poses significant environmental challenges, with both operational and embodied carbon emissions becoming major cont…

cs.PF2025

CarbonCall: Sustainability-Aware Function Calling for Large Language Models on Edge Devices

Varatheepan Paramanayakam, Andreas Karatzas, Iraklis Anagnostopoulos +1

Large Language Models (LLMs) enable real-time function calling in edge AI systems but introduce significant computational overhead, leading to high power consumption and carbon emi…

cs.LG2025

Ecomap: Sustainability-Driven Optimization of Multi-Tenant DNN Execution on Edge Servers

Varatheepan Paramanayakam, Andreas Karatzas, Dimitrios Stamoulis +1

Edge computing systems struggle to efficiently manage multiple concurrent deep neural network (DNN) workloads while meeting strict latency requirements, minimizing power consumptio…

cs.LG2025

Multi-Agent Geospatial Copilots for Remote Sensing Workflows

Chaehong Lee, Varatheepan Paramanayakam, Andreas Karatzas +7

We present GeoLLM-Squad, a geospatial Copilot that introduces the novel multi-agent paradigm to remote sensing (RS) workflows. Unlike existing single-agent approaches that rely on…

cs.LG2024

RankMap: Priority-Aware Multi-DNN Manager for Heterogeneous Embedded Devices

Andreas Karatzas, Dimitrios Stamoulis, Iraklis Anagnostopoulos

Modern edge data centers simultaneously handle multiple Deep Neural Networks (DNNs), leading to significant challenges in workload management. Thus, current management systems must…