Jason T. L. Wang

93 papers A* 1A 1B 5C 9Misc 5Journal 55Unranked 14
YearRankTypeTitle / Venue / Authors
2025 J jnl
An Interpretable Machine Learning Approach to Understanding the Relationships between Solar Flares and Source Active Regions.
CoRR
Huseyin Cavus, Jason T. L. Wang, Teja P. S. Singampalli, Gani Caglar Coban, Hongyang Zhang, Abd-ur Raheem, Haimin Wang
2025 J jnl
Explainable AI in Deep Learning-Based Prediction of Solar Storms.
CoRR
Adam Rawashdeh, Jason T. L. Wang, Katherine G. Herbert
2025 Misc conf
Explainable Artificial Intelligence in Deep Learning-Based Solar Storm Predictions.
FLAIRS
Adam Rawashdeh, Jason T. L. Wang, Katherine G. Herbert
2025 J jnl
Improving the Temporal Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using a Deep Generative Model.
CoRR
Jialiang Li, Vasyl Yurchyshyn, Jason T. L. Wang, Haimin Wang, Yasser Abduallah, Khalid A. Alobaid, Chunhui Xu, Ruizhu Chen, Yan Xu
2025 — conf
Out-of-Sample Validation of MagNet.
ICDM (Workshops)
Aryiadna Yesmanchyk, Yan Xu, Jason T. L. Wang, Haodi Jiang, Chunhui Xu, Haimin Wang
2025 J jnl
Prediction of Geoeffective CMEs Using SOHO Images and Deep Learning.
CoRR
Khalid A. Alobaid, Jason T. L. Wang, Haimin Wang, Ju Jing, Yasser Abduallah, Zhenduo Wang, Hameedullah Farooki, Huseyin Cavus, Vasyl Yurchyshyn
2025 J jnl
Prediction of Halo Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and a Transformer Model.
CoRR
Hongyang Zhang, Ju Jing, Jason T. L. Wang, Haimin Wang, Yasser Abduallah, Yan Xu, Khalid A. Alobaid, Hameedullah Farooki, Vasyl Yurchyshyn
2025 J jnl
Reconstruction of Solar EUV Irradiance Using CaII K Images and SOHO/SEM Data with Bayesian Deep Learning and Uncertainty Quantification.
CoRR
Haodi Jiang, Qin Li, Jason T. L. Wang, Haimin Wang, Serena Criscuoli
2024 J jnl
A transformer-based framework for predicting geomagnetic indices with uncertainty quantification.
J. Intell. Inf. Syst.
Yasser Abduallah, Jason T. L. Wang, Haimin Wang, Ju Jing
2024 Misc conf
An Interpretable Transformer Model for Operational Flare Forecasting.
FLAIRS
Yasser Abduallah, Vinay Ram Gazula, Jason T. L. Wang
2024 J jnl
Downscaling daily wind speed with Bayesian deep learning for climate monitoring.
Int. J. Data Sci. Anal.
Firas Gerges, Michel C. Boufadel, Elie Bou-Zeid, Hani Nassif, Jason T. L. Wang
2024 B conf
Interpretable Deep Learning for Solar Flare Prediction.
ICTAI
Vinay Ram Gazula, Katherine G. Herbert, Yasser Abduallah, Jason T. L. Wang
2024 J jnl
Long-term prediction of daily solar irradiance using Bayesian deep learning and climate simulation data.
Knowl. Inf. Syst.
Firas Gerges, Michel C. Boufadel, Elie Bou-Zeid, Hani Nassif, Jason T. L. Wang
2024 Misc conf
Multiclass Classification of Solar Flares in Imbalanced Data Using Ensemble Learning and Sampling Methods.
FLAIRS
Haodi Jiang, Ryoma Matsuura, Jason T. L. Wang
2024 J jnl
Prediction of the SYM-H Index Using a Bayesian Deep Learning Method with Uncertainty Quantification.
CoRR
Yasser Abduallah, Khalid A. Alobaid, Jason T. L. Wang, Haimin Wang, Vania K. Jordanova, Vasyl Yurchyshyn, Huseyin Cavus, Ju Jing
2024 C conf
Solar Image Synthesis with Generative Adversarial Networks.
ICMLA
Haodi Jiang, Jason T. L. Wang
2024 J jnl
Super-Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using SDO/HMI Data and an Attention-Aided Convolutional Neural Network.
CoRR
Chunhui Xu, Jason T. L. Wang, Haimin Wang, Haodi Jiang, Qin Li, Yasser Abduallah, Yan Xu
2023 B conf
An Interpretable LSTM Network for Solar Flare Prediction.
ICTAI
Gautam Varma Datla, Haodi Jiang, Jason T. L. Wang
2023 J jnl
Deep Learning-Based Downscaling of Temperatures for Monitoring Local Climate Change Using Global Climate Simulation Data.
World Sci. Annu. Rev. Artif. Intell.
Firas Gerges, Michel C. Boufadel, Elie Bou-Zeid, Hani Nassif, Jason T. L. Wang
2023 — conf
Deep Learning-Enabled Prediction of Daily Solar Irradiance from Simulated Climate Data.
ICMLSC
Firas Gerges, Michel C. Boufadel, Elie Bou-Zeid, Hani Nassif, Jason T. L. Wang
2023 J jnl
Ensemble Learning for CME Arrival Time Prediction.
CoRR
Khalid A. Alobaid, Jason T. L. Wang
2023 J jnl
Estimating Coronal Mass Ejection Mass and Kinetic Energy by Fusion of Multiple Deep-learning Models.
CoRR
Khalid A. Alobaid, Yasser Abduallah, Jason T. L. Wang, Haimin Wang, Shen Fan, Jialiang Li, Huseyin Cavus, Vasyl Yurchyshyn
2022 J jnl
A Deep Learning Approach to Dst Index Prediction.
CoRR
Yasser Abduallah, Jason T. L. Wang, Prianka Bose, Genwei Zhang, Firas Gerges, Haimin Wang
2022 J jnl
A Deep Learning Approach to Generating Photospheric Vector Magnetograms of Solar Active Regions for SOHO/MDI Using SDO/HMI and BBSO Data.
CoRR
Haodi Jiang, Qin Li, Zhihang Hu, Nian Liu, Yasser Abduallah, Ju Jing, Genwei Zhang, Yan Xu, Wynne Hsu, Jason T. L. Wang, Haimin Wang
2022 — conf
A Novel Bayesian Deep Learning Approach to the Downscaling of Wind Speed with Uncertainty Quantification.
PAKDD (3)
Firas Gerges, Michel C. Boufadel, Elie Bou-Zeid, Hani Nassif, Jason T. L. Wang
2022 — conf
A Novel Deep Learning Approach to the Statistical Downscaling of Temperatures for Monitoring Climate Change.
ICMLSC
Firas Gerges, Michel C. Boufadel, Elie Bou-Zeid, Hani Nassif, Jason T. L. Wang
2022 C conf
A Transformer-Based Framework for Geomagnetic Activity Prediction.
ISMIS
Yasser Abduallah, Jason T. L. Wang, Chunhui Xu, Haimin Wang
2022 — conf
Bayesian Multi-head Convolutional Neural Networks with Bahdanau Attention for Forecasting Daily Precipitation in Climate Change Monitoring.
ECML/PKDD (5)
Firas Gerges, Michel C. Boufadel, Elie Bou-Zeid, Ankit Darekar, Hani Nassif, Jason T. L. Wang
2022 — conf
Early Prediction of Movie Success Using Machine Learning and Evolutionary Computation.
ISCIT
Firas Gerges, Danielle Azar, Joseph Vybihal, Jason T. L. Wang
2022 Misc conf
Forecasting the Disturbance Storm Time Index with Bayesian Deep Learning.
FLAIRS
Yasser Abduallah, Jason T. L. Wang, Prianka Bose, Genwei Zhang, Firas Gerges, Haimin Wang
2022 J jnl
Inferring Line-of-Sight Velocities and Doppler Widths from Stokes Profiles of GST/NIRIS Using Stacked Deep Neural Networks.
CoRR
Haodi Jiang, Qin Li, Yan Xu, Wynne Hsu, Kwangsu Ahn, Wenda Cao, Jason T. L. Wang, Haimin Wang
2022 J jnl
Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network.
CoRR
Yasser Abduallah, Vania K. Jordanova, Hao Liu, Qin Li, Jason T. L. Wang, Haimin Wang
2021 J jnl
Deep Learning Based Reconstruction of Total Solar Irradiance.
CoRR
Yasser Abduallah, Jason T. L. Wang, Yucong Shen, Khalid A. Alobaid, Serena Criscuoli, Haimin Wang
2021 Misc conf
Reconstruction of Total Solar Irradiance by Deep Learning.
FLAIRS
Yasser Abduallah, Jason T. L. Wang, Yucong Shen, Khalid A. Alobaid, Serena Criscuoli, Haimin Wang
2021 J jnl
Tracing Halpha Fibrils through Bayesian Deep Learning.
CoRR
Haodi Jiang, Ju Jing, Jiasheng Wang, Chang Liu, Qin Li, Yan Xu, Jason T. L. Wang, Haimin Wang
2020 J jnl
DeepSun: Machine-Learning-as-a-Service for Solar Flare Prediction.
CoRR
Yasser Abduallah, Jason T. L. Wang, Yang Nie, Chang Liu, Haimin Wang
2020 J jnl
Generative Adversarial Networks for Stochastic Video Prediction With Action Control.
IEEE Access
Zhihang Hu, Turki Turki, Jason T. L. Wang
2020 J jnl
Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning.
CoRR
Haodi Jiang, Jiasheng Wang, Chang Liu, Ju Jing, Hao Liu, Jason T. L. Wang, Haimin Wang
2020 J jnl
Inferring Vector Magnetic Fields from Stokes Profiles of GST/NIRIS Using a Convolutional Neural Network.
CoRR
Hao Liu, Yan Xu, Jiasheng Wang, Ju Jing, Chang Liu, Jason T. L. Wang, Haimin Wang
2020 J jnl
Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations.
CoRR
Gelu Nita, Manolis K. Georgoulis, Irina Kitiashvili, Viacheslav Sadykov, Enrico Camporeale, Alexander Kosovichev, Haimin Wang, Vincent Oria, Jason T. L. Wang, Rafal A. Angryk, Berkay Aydin, Azim Ahmadzadeh, Xiaoli Bai, Timothy Bastian, Soukaina Filali Boubrahimi, Bin Chen, Alisdair Davey, Sheldon Fereira, Gregory Fleishman, Dale Gary, Andrew Gerrard, Gregory Hellbourg, Katherine G. Herbert, Jack Ireland, Egor Illarionov, Natsuha Kuroda, Qin Li, Chang Liu, Yuexin Liu, Hyomin Kim, Dustin Kempton, Ruizhe Ma, Petrus C. Martens, Ryan M. McGranaghan, Edward Semones, John T. Stefan, Andrey Stejko, Yaireska Collado-Vega, Meiqi Wang, Yan Xu, Sijie Yu
2020 J jnl
Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural Networks.
CoRR
Hao Liu, Chang Liu, Jason T. L. Wang, Haimin Wang
2019 J jnl
Clinical intelligence: New machine learning techniques for predicting clinical drug response.
Comput. Biol. Medicine
Turki Turki, Jason T. L. Wang
2019 A* conf
Generative Adversarial Networks for Video Prediction with Action Control.
IJCAI
Zhihang Hu, Jason T. L. Wang
2019 J jnl
New algorithms for inferring gene regulatory networks from time-series expression data on Apache Spark.
Int. J. Big Data Intell.
Yasser Abduallah, Jason T. L. Wang
2019 J jnl
Predicting Solar Flares Using a Long Short-Term Memory Network.
CoRR
Hao Liu, Chang Liu, Jason T. L. Wang, Haimin Wang
2018 J jnl
A 3D Atrous Convolutional Long Short-Term Memory Network for Background Subtraction.
IEEE Access
Zhihang Hu, Turki Turki, NhatHai Phan, Jason T. L. Wang
2018 J jnl
A comparative review of recent bioinformatics tools for inferring gene regulatory networks using time-series expression data.
Int. J. Data Min. Bioinform.
Kevin Byron, Jason T. L. Wang
2018 J jnl
A transfer learning approach via procrustes analysis and mean shift for cancer drug sensitivity prediction.
J. Bioinform. Comput. Biol.
Turki Turki, Zhi Wei, Jason T. L. Wang
2018 C conf
DLGraph: Malware Detection Using Deep Learning and Graph Embedding.
ICMLA
Haodi Jiang, Turki Turki, Jason T. L. Wang
2018 J jnl
Discovering frequent induced subgraphs from directed networks.
Intell. Data Anal.
Sen Zhang, Zhihui Du, Jason T. L. Wang, Haodi Jiang
2018 — conf
Reverse Engineering Gene Regulatory Networks Using Graph Mining.
MLDM (1)
Haodi Jiang, Turki Turki, Sen Zhang, Jason T. L. Wang
2017 J jnl
A Computational Approach to Finding RNA Tertiary Motifs in Genomic Sequences.
CoRR
Kevin Byron, Jason T. L. Wang
2017 — conf
A Time-Delayed Information-Theoretic Approach to the Reverse Engineering of Gene Regulatory Networks Using Apache Spark.
DASC/PiCom/DataCom/CyberSciTech
Yasser Abduallah, Jason T. L. Wang
2017 J jnl
Guest Editorial: Special Section on Biological Data Mining and Its Applications in Healthcare.
IEEE ACM Trans. Comput. Biol. Bioinform.
Fei Wang, Xiaoli Li, Jason T. L. Wang, See-Kiong Ng
2017 J jnl
MapReduce Algorithms for Inferring Gene Regulatory Networks from Time-Series Microarray Data Using an Information-Theoretic Approach.
CoRR
Yasser Abduallah, Turki Turki, Kevin Byron, Zongxuan Du, Miguel Cervantes-Cervantes, Jason T. L. Wang
2017 C conf
Reverse Engineering Regulatory Networks in Cells Using a Dynamic Bayesian Network and Mutual Information Scoring Function.
ICMLA
Haodi Jiang, Turki Turki, Jason T. L. Wang
2017 J jnl
Transfer Learning Approaches to Improve Drug Sensitivity Prediction in Multiple Myeloma Patients.
IEEE Access
Turki Turki, Zhi Wei, Jason T. L. Wang
2016 — conf
A Learning Framework to Improve Unsupervised Gene Network Inference.
MLDM
Turki Turki, William Bassett, Jason T. L. Wang
2016 — book
Bioinformatics Database Systems.
Kevin Byron, Katherine G. Herbert, Jason T. L. Wang
2016 J jnl
CHSalign: A Web Server That Builds upon Junction-Explorer and RNAJAG for Pairwise Alignment of RNA Secondary Structures with Coaxial Helical Stacking.
CoRR
Lei Hua, Yang Song, Namhee Kim, Christian Laing, Jason T. L. Wang, Tamar Schlick
2016 J jnl
Effective Classification of MicroRNA Precursors Using Combinatorial Feature Mining and AdaBoost Algorithms.
CoRR
Ling Zhong, Jason T. L. Wang
2016 C conf
Inferring Gene Regulatory Networks by Combining Supervised and Unsupervised Methods.
ICMLA
Turki Turki, Jason T. L. Wang, Ibrahim Rajikhan
2016 J jnl
Semi-Supervised Prediction of Gene Regulatory Networks Using Machine Learning Algorithms.
CoRR
Nihir Patel, Jason T. L. Wang
2015 C conf
A New Approach to Link Prediction in Gene Regulatory Networks.
IDEAL
Turki Turki, Jason T. L. Wang
2014 J jnl
Genome-Wide Prediction of Coaxial Helical Stacking Using Random Forests and Covariance Models.
Int. J. Artif. Intell. Tools
Kevin Byron, Jason T. L. Wang, Dongrong Wen
2013 J jnl
Novel features for identifying A-minors in three-dimensional RNA molecules.
Comput. Biol. Chem.
Palak Sheth, Miguel Cervantes-Cervantes, Akhila Nagula, Christian Laing, Jason T. L. Wang
2012 J jnl
A Method for Discovering Common Patterns from Two RNA Secondary Structures and its Application to Structural Repeat Detection.
J. Bioinform. Comput. Biol.
Lei Hua, Jason T. L. Wang, Xiang Ji, Ankur Malhotra, Mugdha Khaladkar, Bruce A. Shapiro, Kaizhong Zhang
2012 J jnl
Fast Elastic Peak Detection for Mass Spectrometry Data Mining.
IEEE Trans. Knowl. Data Eng.
Xin Zhang, Dennis E. Shasha, Yang Song, Jason T. L. Wang
2012 C conf
Genome-wide search for coaxial helical stacking motifs.
BIBE
Kevin Byron, Jason T. L. Wang, Dongrong Wen
2012 — conf
Pre-miRNA classification via combinatorial feature mining and boosting.
BIBM
Ling Zhong, Jason T. L. Wang, Dongrong Wen, Bruce A. Shapiro
2012 J jnl
Searching for Non-coding RNAs in Genomic Sequences Using ncRNAscout.
Genom. Proteom. Bioinform.
Michael Bao, Miguel Cervantes-Cervantes, Ling Zhong, Jason T. L. Wang
2011 J jnl
In silico prediction of noncoding RNAs using supervised learning and feature ranking methods.
Int. J. Bioinform. Res. Appl.
Stephen J. Griesmer, Miguel Cervantes-Cervantes, Yang Song, Jason T. L. Wang
2010 J jnl
Bioinformatics Methods for Studying MicroRNA and ARE-Mediated Regulation of Post-Transcriptional Gene Expression.
Int. J. Knowl. Discov. Bioinform.
Richipal Singh Bindra, Jason T. L. Wang, Paramjeet Singh Bagga
2010 J jnl
On Comparing Two Structured RNA Multiple alignments.
J. Bioinform. Comput. Biol.
Vandanaben Patel, Jason T. L. Wang, Shefali Setia, Anurag Verma, Charles D. Warden, Kaizhong Zhang
2007 — conf
A New Algorithm for RNA Secondary Structure Prediction.
BIOCOMP
Junilda Spirollari, Jason T. L. Wang, Yongkyu Park
2007 B conf
A study of phylogenetic tools for genomic nomenclature data cleaning.
ITiCSE
Jonathan D. Marra, Katherine G. Herbert, Jason T. L. Wang
2007 J jnl
Biological data cleaning: a case study.
Int. J. Inf. Qual.
Katherine G. Herbert, Jason T. L. Wang
2007 — ch.
Classification of RNA Sequences with Support Vector Machines.
Analysis of Biological Data: A Soft Computing Approach
Jason T. L. Wang, Xiaoming Wu
2007 — conf
Detecting Conserved RNA Secondary Structures in Viral Genomes: The RADAR Approach.
BioSurveillance
Mugdha Khaladkar, Jason T. L. Wang
2006 J jnl
Kernel design for RNA classification using Support Vector Machines.
Int. J. Data Min. Bioinform.
Jason T. L. Wang, Xiaoming Wu
2006 B conf
PhyloMiner: A Tool for Evolutionary Data Analysis.
SSDBM
Sen Zhang, Katherine G. Herbert, Jason T. L. Wang, William H. Piel, David R. B. Stockwell
2006 C conf
RADAR: An InteractiveWeb-Based Toolkit for RNA Data Analysis and Research.
BIBE
Mugdha Khaladkar, Vivian Bellofatto, Jason T. L. Wang, Bin Tian, Kaizhong Zhang
2005 C conf
Biomonitoring, Phylogenetics and Anomaly Aggregation Systems.
ISI
David R. B. Stockwell, Jason T. L. Wang
2005 J jnl
Xml Clustering And Retrieval Through Principal Component Analysis.
Int. J. Artif. Intell. Tools
Jason T. L. Wang, Jianghui Liu, Junhan Wang
2004 B conf
XML Clustering by Principal Component Analysis.
ICTAI
Jianghui Liu, Jason T. L. Wang, Wynne Hsu, Katherine G. Herbert
2000 — conf
Application of hidden Markov models to biological data mining: a case study.
Data Mining and Knowledge Discovery: Theory, Tools, and Technology
Michael M. Yin, Jason T. L. Wang
1994 J jnl
A formal approach to modeling office information systems.
J. Syst. Integr.
Zhijian Zhu, James A. McHugh, Jason T. L. Wang, Peter A. Ng
1994 J jnl
Heuristic Classification of Office Documents.
Int. J. Artif. Intell. Tools
Xiaolong Hao, Jason T. L. Wang, Michael P. Bieber, Peter A. Ng
1994 — ch.
Texpros: an Intelligent Document Processing System.
The Impact of Case Technology on Software Processes
Jason T. L. Wang, Peter A. Ng
1994 — conf
The approximate graph matching problem.
ICPR (2)
Jason T. L. Wang, Kaizhong Zhang, Gung-Wei Chirn
1993 A conf
Nested segmentation: an approach for layout analysis in document classification.
ICDAR
Xiaolong Hao, Jason T. L. Wang, Peter A. Ng
1993 J jnl
On research issues regarding uncertain query processing in an office document retrieval system.
J. Syst. Integr.
Qianhong Liu, Jason T. L. Wang, Peter A. Ng
1992 J jnl
Texpros: an Intelligent Document Processing System.
Int. J. Softw. Eng. Knowl. Eng.
Jason T. L. Wang, Peter A. Ng