1 citations · 2 across the 7 of their papers we have counts for
9 papers
From Sensors to Insight: Rapid, Edge-to-Core Application Development for Sensor-Driven Applications
Komal Thareja, Anirban Mandal, Ewa Deelman
Scientists increasingly rely on sensor-based data, yet transforming raw streams into insights across the edge-to-cloud continuum remains difficult. Provisioning heterogeneous infra…
(POSTER) From Sensors to Insight: Rapid, Edge-to-Core Application Development for Sensor-Driven Applications
Komal Thareja, Anirban Mandal, Ewa Deelman
Scientists increasingly rely on sensor-based data; however transforming raw streams into insights across the edge-to-cloud continuum remains difficult due to the breadth of experti…
SWARM+: Scalable and Resilient Multi-Agent Consensus for Decentralized Data-Aware Workload Management
Komal Thareja, Krishnan Raghavan, Hamza Safri +2
Distributed scientific workflows are increasingly executed across heterogeneous and geo-distributed computing environments, where centralized workload orchestration becomes a scala…
AeroResQ: Edge-Accelerated UAV Framework for Scalable, Resilient and Collaborative Escape Route Planning in Wildfire Scenarios
Suman Raj, Radhika Mittal, Rajiv Mayani +5
Drone fleets equipped with onboard cameras, computer vision, and Deep Neural Network (DNN) models present a powerful paradigm for real-time spatio-temporal decision-making. In wild…
Evaluating the Efficacy of LLM-Based Reasoning for Multiobjective HPC Job Scheduling
Prachi Jadhav, Hongwei Jin, Ewa Deelman +1
High-Performance Computing (HPC) job scheduling involves balancing conflicting objectives such as minimizing makespan, reducing wait times, optimizing resource use, and ensuring fa…
Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context Learning
Hongwei Jin, George Papadimitriou, Krishnan Raghavan +5
Anomaly detection in computational workflows is critical for ensuring system reliability and security. However, traditional rule-based methods struggle to detect novel anomalies. T…
Advancing Anomaly Detection in Computational Workflows with Active Learning
Krishnan Raghavan, George Papadimitriou, Hongwei Jin +4
A computational workflow, also known as workflow, consists of tasks that are executed in a certain order to attain a specific computational campaign. Computational workflows are co…
Self-supervised Learning for Anomaly Detection in Computational Workflows
Hongwei Jin, Krishnan Raghavan, George Papadimitriou +4
Anomaly detection is the task of identifying abnormal behavior of a system. Anomaly detection in computational workflows is of special interest because of its wide implications in…
Reproducing the results for NICER observation of PSR J0030+0451
Chaitanya Afle, Patrick R. Miles, Silvina Caino-Lores +6
NASA's Neutron Star Interior Composition Explorer (NICER) observed X-ray emission from the pulsar PSR J0030+0451 in 2018. Riley et al. reported Bayesian parameter measurements of t…