Area of research
Computer Networks and Communications · Information Systems and Management
Research interest
Research interests include Scientific Computing and Data Management, Distributed and Parallel Computing Systems, Cloud Computing and Resource Management, and Advanced Data Storage Technologies.
What to Support When You’re Compressing
RuralAI in Tomato Farming: Integrated Sensor System, Distributed Computing, and Hierarchical Federated Learning for Crop Health Monitoring
QoS-aware edge AI placement and scheduling with multiple implementations in FaaS-based edge computing
An Empirical Study of Container Image Configurations and Their Impact on Start Times
Accelerating Communications in Federated Applications with Transparent Object Proxies
The Diminishing Returns of Masked Language Models to Science
Optimizing Scientific Data Transfer on Globus with Error-Bounded Lossy Compression
PSI/J: A Portable Interface for Submitting, Monitoring, and Managing Jobs
SECRE: Surrogate-Based Error-Controlled Lossy Compression Ratio Estimation Framework
FAIR principles for AI models with a practical application for accelerated high energy diffraction microscopy
Rural AI: Serverless-Powered Federated Learning for Remote Applications
<i>func</i>X: Federated Function as a Service for Science
Making Common Fund data more findable: catalyzing a data ecosystem
Hierarchical and Decentralised Federated Learning
FLoX: Federated Learning with FaaS at the Edge
Optimizing Error-Bounded Lossy Compression for Scientific Data With Diverse Constraints
High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor
Challenges and Advances in Information Extraction from Scientific Literature: a Review
Colmena: Scalable Machine-Learning-Based Steering of Ensemble Simulations for High Performance Computing
Coding the Computing Continuum: Fluid Function Execution in Heterogeneous Computing Environments
funcX: A Federated Function Serving Fabric for Science
Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types
A data ecosystem to support machine learning in materials science
Enabling real-time multi-messenger astrophysics discoveries with deep learning
Reproducible big data science: A case study in continuous FAIRness
Deconstructing the 2017 Changes to AWS Spot Market Pricing
Active Learning Yields Better Training Data for Scientific Named Entity Recognition
Matminer: An open source toolkit for materials data mining
Predicting Amazon Spot Prices with LSTM Networks
REU Site: AI and Science Summer Lab: advancing AI-enabled scientific discovery across the physical and biological sciences
Collaborative Research: Frameworks: Diamond: Democratizing Large Neural Network Model Training for Science
Collaborative Research: Sustainability: A Community-Centered Approach for Supporting and Sustaining Parsl
Collaborative Research: REU Site: BigDataX: From theory to practice in Big Data computing at eXtreme scales
Frameworks: Collaborative Research: ChronoLog: A High-Performance Storage Infrastructure for Activity and Log Workloads
Collaborative Research: OAC Core: Enabling Extremely Fine-grained Parallelism on Modern Many-core Architectures
CCRI: Planning: Collaborative Research: Infrastructure for Enabling Systematic Development and Research of Scientific Workflow Management Systems
CSR: Small: Cost-Aware Cloud Profiling, Prediction, and Provisioning as a Service
REU Site: Collaborative Research: BigDataX: From theory to practice in Big Data computing at eXtreme scales
Collaborative Research: SI2-SSI: Swift/E: Integrating Parallel Scripted Workflow into the Scientific Software Ecosystem