Dynamic rate adaptation. - Garrison W. Cottrell; Mai H. Nguyen; Fu-Sheng Tsung (Artif. Intell. Rev., 1993)

A Connectionist Approach to Rate Adaptation. - Mai H. Nguyen; Garrison W. Cottrell (SIGART Bull., 1994)

Tau Net A neural network for modeling temporal variability. - Mai H. Nguyen; Garrison W. Cottrell (Neurocomputing, 1997)

A Scalable Data Science Workflow Approach for Big Data Bayesian Network Learning. - Jianwu Wang 001; Yan Tang; Mai H. Nguyen; Ilkay Altintas (BDC, 2014)

Big data provenance: Challenges, state of the art and opportunities. - Jianwu Wang 001; Daniel Crawl; Shweta Purawat; Mai H. Nguyen; Ilkay Altintas (IEEE BigData, 2015)

Towards an Integrated Cyberinfrastructure for Scalable Data-driven Monitoring, Dynamic Prediction and Resilience of Wildfires. - Ilkay Altintas; Jessica Block; Raymond A. de Callafon; Daniel Crawl; Charles Cowart; Amarnath Gupta; Mai H. Nguyen; Hans-Werner Braun; Jürgen P. Schulze; Michael Gollner; Arnaud Trouve; Larry Smarr (ICCS, 2015)

Determining feature extractors for unsupervised learning on satellite images. - Behnam Hedayatnia; Mehrdad Yazdani; Mai H. Nguyen; Jessica Block; Ilkay Altintas (IEEE BigData, 2016)

A scalable approach for location-specific detection of Santa Ana conditions. - Mai H. Nguyen; Dylan Uys; Daniel Crawl; Charles Cowart; Ilkay Altintas (IEEE BigData, 2016)

Integrated Machine Learning in the Kepler Scientific Workflow System. - Mai H. Nguyen; Daniel Crawl; Tahereh Masoumi; Ilkay Altintas (ICCS, 2016)

Automated scalable detection of location-specific Santa Ana conditions from weather data using unsupervised learning. - Mai H. Nguyen; Daniel Crawl; Jiaxin Li; Dylan Uys; Ilkay Altintas (IEEE BigData, 2017)

An Unsupervised Deep Learning Approach for Satellite Image Analysis with Applications in Demographic Analysis. - Jessica Block; Mehrdad Yazdani; Mai H. Nguyen; Daniel Crawl; Marta Jankowska; John J. Graham; Thomas A. DeFanti; Ilkay Altintas (eScience, 2017)

Modular Resource Centric Learning for Workflow Performance Prediction. - Alok Singh 004; Mai H. Nguyen; Shweta Purawat; Daniel Crawl; Ilkay Altintas (CoRR, 2017)

Land Cover Classification at the Wildland Urban Interface using High-Resolution Satellite Imagery and Deep Learning. - Mai H. Nguyen; Jessica Block; Daniel Crawl; Vincent Siu; Akshit Bhatnagar; Federico Rodríguez; Alison Kwan; Namrita Baru; Ilkay Altintas (IEEE BigData, 2018)

Analytics Pipeline for Left Ventricle Segmentation and Volume Estimation on Cardiac MRI Using Deep Learning. - Mai H. Nguyen; Ehab Abdelmaguid; Jolene Huang; Sanjay Kenchareddy; Disha Singla; Laura Wilke; Marcus Bobar; Eric D. Carruth; Dylan Uys; Ilkay Altintas; Evan D. Muse; Giorgio Quer; et al. (eScience, 2018)

Scalable Detection of Rural Schools in Africa Using Convolutional Neural Networks and Satellite Imagery. - Mehrdad Yazdani; Mai H. Nguyen; Jessica Block; Daniel Crawl; Naroa Zurutuza; Dohyung Kim; Gordon Hanson; Ilkay Altintas (UCC Companion, 2018)

Left Ventricle Segmentation and Volume Estimation on Cardiac MRI using Deep Learning. - Ehab Abdelmaguid; Jolene Huang; Sanjay Kenchareddy; Disha Singla; Laura Wilke; Mai H. Nguyen; Ilkay Altintas (CoRR, 2018)

Ten Simple Rules for Reproducible Research in Jupyter Notebooks. - Adam Rule; Amanda Birmingham; Cristal Zuñiga; Ilkay Altintas; Shih-Cheng Huang; Rob Knight 001; Niema Moshiri; Mai H. Nguyen; Sara Brin Rosenthal; Fernando Pérez; Peter W. Rose (CoRR, 2018)

Scaling Deep Learning-Based Analysis of High-Resolution Satellite Imagery with Distributed Processing. - Mai H. Nguyen; Jiaxin Li; Daniel Crawl; Jessica Block; Ilkay Altintas (IEEE BigData, 2019)

Understanding a Rapidly Expanding Refugee Camp Using Convolutional Neural Networks and Satellite Imagery. - Susanne Benz; Hogeun Park; Jiaxin Li; Daniel Crawl; Jessica Block; Mai H. Nguyen; Ilkay Altintas (eScience, 2019)

Cardiac MRI Image Segmentation for Left Ventricle and Right Ventricle using Deep Learning. - Bosung Seo; Daniel Mariano; John Beckfield; Vinay Madenur; Yuming Hu; Tony Reina; Marcus Bobar; Mai H. Nguyen; Ilkay Altintas (CoRR, 2019)

Ten simple rules for writing and sharing computational analyses in Jupyter Notebooks. - Adam Rule; Amanda Birmingham; Cristal Zuñiga; Ilkay Altintas; Shih-Cheng Huang; Rob Knight 001; Niema Moshiri; Mai H. Nguyen; Sara Brin Rosenthal; Fernando Pérez; Peter W. Rose (PLoS Comput. Biol., 2019)

PEnBayes: A Multi-Layered Ensemble Approach for Learning Bayesian Network Structure from Big Data. - Yan Tang; Jianwu Wang 001; Mai H. Nguyen; Ilkay Altintas (Sensors, 2019)

Generalization in Cardiac Image Segmentation. - Zhengjie Xu; Zixiang Zhou; Garrison W. Cottrell; Mai H. Nguyen (IEEE BigData, 2021)

Multimodal Wildland Fire Smoke Detection. - Siddhant Baldota; Shreyas Anantha Ramaprasad; Jaspreet Kaur Bhamra; Shane Luna; Ravi Ramachandra; Eugene Zen; Harrison Kim; Daniel Crawl; Ismael Pérez; Ilkay Altintas; Garrison W. Cottrell; Mai H. Nguyen (CoRR, 2022)

Effects of data and entity ablation on multitask learning models for biomedical entity recognition. - Nicholas E. Rodriguez; Mai H. Nguyen; Bridget T. McInnes (J. Biomed. Informatics, 2022)

FIgLib & SmokeyNet: Dataset and Deep Learning Model for Real-Time Wildland Fire Smoke Detection. - Anshuman Dewangan; Yash Pande; Hans-Werner Braun; Frank Vernon; Ismael Pérez; Ilkay Altintas; Garrison W. Cottrell; Mai H. Nguyen (Remote. Sens., 2022)

Visualization and Labeling of Terrestrial LiDAR Data for Three-Dimensional Fuel Classification. - Ivannia Gomez Moreno; Isaac Nealey; Daniel Roten; Mai H. Nguyen; Daniel Crawl; Kate O'Laughlin; Melissa Floca; Scott Pokswinski; Ilkay Altintas (e-Science, 2023)

Ensemble Based Learning for Automated Safety Labeling of Prescribed Fires. - Li Tan; Raymond A. de Callafon; Mai H. Nguyen; Ilkay Altintas (ICCS (1), 2023)

Voyager - An Innovative Computational Resource for Artificial Intelligence & Machine Learning Applications in Science and Engineering. - Rommie E. Amaro; Jiunn-Yeu Chen; Javier M. Duarte; Thomas E. Hutton; Christopher Irving; Martin C. Kandes; Amit Majumdar 001; Dmitry Y. Mishin; Mai H. Nguyen; Paul Rodríguez; Fernando Silva; Robert S. Sinkovits; et al. (PEARC, 2023)

Developing a Best Practices Training Program in Cyberinfrastructure-Enabled Machine Learning Research. - Mary P. Thomas; Andreas W. Götz; Martin C. Kandes; Mai H. Nguyen; Paul Rodríguez; Peter W. Rose; Robert S. Sinkovits (PEARC, 2023)

Multimodal Wildland Fire Smoke Detection. - Jaspreet Kaur Bhamra; Shreyas Anantha Ramaprasad; Siddhant Baldota; Shane Luna; Eugene Zen; Ravi Ramachandra; Harrison Kim; Chris Schmidt; Chris Arends; Jessica Block; Ismael Pérez; Daniel Crawl; et al. (Remote. Sens., 2023)

Near Real-Time Wildfire Damage Assessment using Aerial Thermal Imagery and Machine Learning. - Saqib Azim; Mai H. Nguyen; Daniel Crawl; Jessica Block; Rawaf Al Rawaf; Francesca Hart; Mark Campbell; Robert Scott; Ilkay Altintas (IEEE Big Data, 2024)

Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management. - Somya Sharma Chatterjee; Kelly Lindsay; Neel Chatterjee; Rohan Patil; Ilkay Altintas De Callafon; Michael S. Steinbach; Daniel Giron; Mai H. Nguyen; Vipin Kumar 001 (SDM, 2024)

BioBERT-based Deep Learning and Merged ChemProt-DrugProt for Enhanced Biomedical Relation Extraction. - Bridget T. McInnes; Jiawei Tang; Darshini Mahendran; Mai H. Nguyen (CoRR, 2024)

Editorial: Big scientific data analytics on HPC and cloud. - Jianwu Wang; Junqi Yin; Mai H. Nguyen; Jingbo Wang; Weijia Xu (Frontiers Big Data, 2024)