CV

Education

Ph.D in Version Control Theory, GitHub University, 2018 (expected)
M.S. in Jekyll, GitHub University, 2014
B.S. in GitHub, GitHub University, 2012

Work experience

Spring 2024: Academic Pages Collaborator
- GitHub University
- Duties includes: Updates and improvements to template
- Supervisor: The Users
Fall 2015: Research Assistant
- GitHub University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
Summer 2015: Research Assistant
- GitHub University
- Duties included: Tagging issues
- Supervisor: Professor Git

Skills

Skill 1
Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
Skill 3

Publications

Ordinal Encoding as a Regularizer in Binary Loss for Solar Flare Prediction

C. Pandey, J. Hong, A. Ji, R.A. Angryk, B. Aydin, "Ordinal Encoding as a Regularizer in Binary Loss for Solar Flare Prediction," Proc. IEEE ICDMW, Washington DC, November 2025, pp. 1-6.

EdgeAttNet: Towards Barb-Aware Filament Segmentation

V. Solomon, P. Martens, J. Liu, R. Angryk, "EdgeAttNet: Towards Barb-Aware Filament Segmentation," Proc. IEEE ICDMW, Washington DC, November 2025, pp. 1-9.

Autoregressive Surrogate Modeling of the Solar Wind with Spherical Fourier Neural Operator

R. Mansouri, D. Kempton, P. Riley, R. Angryk, "Autoregressive Surrogate Modeling of the Solar Wind with Spherical Fourier Neural Operator," Proc. IEEE ICDMW, Washington DC, November 2025, pp. 1-7.

Outlier Detection and Removal in Multivariate Time Series for a More Robust Machine Learning-Based Solar Flare Prediction

J. Wen, A. Ahmadzadeh, M.K. Georgoulis, V.M. Sadykov, R.A. Angryk, "Outlier Detection and Removal in Multivariate Time Series for a More Robust Machine Learning-Based Solar Flare Prediction," The Astrophysical Journal Supplement Series, Vol. 277(2), 2025, IOP Publishing, pp. 1-16.

Embedding Ordinality to Binary Loss Function for Improving Solar Flare Forecasting

C. Pandey, A. Ji, J. Hong, R.A. Angryk, B. Aydin, "Embedding Ordinality to Binary Loss Function for Improving Solar Flare Forecasting," Proc. IEEE DSAA 2024, San Diego, CA, October 2024, pp. 1-10.

Advancing Solar Flare Prediction Using Deep Learning with Active Region Patches

C. Pandey, T. Adeyeha, J. Hong, R.A. Angryk, B. Aydin, "Advancing Solar Flare Prediction Using Deep Learning with Active Region Patches," Proc. ECML PKDD 2024, LNCS Vol. 14950, Springer, 2024, pp. 50-60.

Class-Based Time Series Data Augmentation to Mitigate Extreme Class Imbalance for Solar Flare Prediction

J. Wen, R.A. Angryk, "Class-Based Time Series Data Augmentation to Mitigate Extreme Class Imbalance for Solar Flare Prediction," Proc. ICAISC 2024, LNCS, Springer, 2024, pp. 362-375.

Prediction of solar energetic events impacting space weather conditions

M. Georgoulis et al., "Prediction of solar energetic events impacting space weather conditions," Advances in Space Research, Elsevier, 2024, pp. 1-57.

Unveiling the Potential of Deep Learning Models for Solar Flare Prediction in Near-Limb Regions

C. Pandey, R.A. Angryk, B. Aydin, "Unveiling the Potential of Deep Learning Models for Solar Flare Prediction in Near-Limb Regions," Proc. ICMLA 2023, Jacksonville, FL, December 2023, pp. 703-708.

Explainable Deep Learning-based Solar Flare Prediction with post hoc Attention for Operational Forecasting

C. Pandey, R.A. Angryk, M.K. Georgoulis, B. Aydin, "Explainable Deep Learning-based Solar Flare Prediction with post hoc Attention," Proc. DS2023, Porto, Portugal, October 2023, pp. 567-581.

A Systematic Magnetic Polarity Inversion Line Dataset from SDO/HMI Magnetograms

A. Ji, X. Cai, N. Khasayeva, M.K. Georgoulis, P.C. Martens, R.A. Angryk, B. Aydin, "A Systematic Magnetic Polarity Inversion Line Dataset from SDO/HMI Magnetograms," The Astrophysical Journal Supplement Series, Vol. 265(1), 2023, IOP Publishing, pp. 1-16.

Contingency Space: A Semimetric Space for Classification Evaluation

A. Ahmadzadeh, D.J. Kempton, P.C. Martens, R.A. Angryk, "Contingency Space: A Semimetric Space for Classification Evaluation," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 45(2), 2023, IEEE, pp. 1501-1513.

Measuring Class-Imbalance Sensitivity of Deterministic Performance Evaluation Metrics

A. Ahmadzadeh, R.A. Angryk, "Measuring Class-Imbalance Sensitivity of Deterministic Performance Evaluation Metrics," Proc. IEEE ICIP 2022, Bordeaux, France, October 2022, pp. 51-55.

TS-MIoU: A Time Series Similarity Metric Without Mapping

A. Ahmadzadeh, Y. Chen, K.R. Puthucode, R.A. Angryk, "TS-MIoU: A Time Series Similarity Metric Without Mapping," Proc. ECML PKDD 2022, Grenoble, France, September 2022, pp. 1-17.

Review of solar energetic particle models

K. Whitman et al., "Review of solar energetic particle models," Advances in Space Research, Elsevier, 2022, pp. 1-82.

Solar Flare Forecasting with Deep Learning-based Time Series Classifiers

A. Ji, J. Wen, R. Angryk, B. Aydin, "Solar Flare Forecasting with Deep Learning-based Time Series Classifiers," Proc. ICPR 2022, Montreal, January 2022, pp. 2907-2913.

Towards coupling full-disk and active region-based flare prediction for operational space weather forecasting

C. Pandey, A. Ji, R.A. Angryk, M.K. Georgoulis, B. Aydin, "Towards coupling full-disk and active region-based flare prediction for operational space weather forecasting," Frontiers in Astronomy and Space Sciences, Vol. 9, 2022, pp. 1-13.

CGAN-based Synthetic Multivariate Time Series Generation: A Solution to Data Scarcity in Solar Flare Forecasting

Y. Chen, D.J. Kempton, A. Ahmadzadeh, J. Wen, R.A. Angryk, "CGAN-based Synthetic Multivariate Time Series Generation: A Solution to Data Scarcity in Solar Flare Forecasting," Neural Computing and Applications, Vol. 34, Springer, 2022, pp. 13339-13353.

Multiscale IoU: A Metric for Evaluation of Salient Object Detection with Fine Structures

A. Ahmadzadeh, D.J. Kempton, Y. Chen, R.A. Angryk, "Multiscale IoU: A Metric for Evaluation of Salient Object Detection with Fine Structures," Proc. IEEE ICIP 2021, Anchorage, September 2021, pp. 684-688.

Spatiotemporal event sequence discovery without thresholds

B. Aydin, S. Filali Boubrahimi, A. Kucuk, B. Nezamdoust, R.A. Angryk, "Spatiotemporal event sequence discovery without thresholds," GeoInformatica, Vol. 25(1), Springer, 2021, pp. 149-177.

How to Train Your Flare Prediction Model: Revisiting Robust Sampling of Rare Events

A. Ahmadzadeh, B. Aydin, M.K. Georgoulis, D.J. Kempton, S.S. Mahajan, R.A. Angryk, "How to Train Your Flare Prediction Model: Revisiting Robust Sampling of Rare Events," The Astrophysical Journal Supplement Series, Vol. 254(2), 2021, IOP Publishing, pp. 1-23.

On the Mining of the Minimal Set of Time Series Data Shapelets

S. Filali Boubrahimi, S.M. Hamdi, R. Ma, R. Angryk, "On the Mining of the Minimal Set of Time Series Data Shapelets," Proc. IEEE BigData 2020, Atlanta, December 2020, pp. 493-502.

Multivariate Time Series Dataset for Space Weather Data Analytics

R. Angryk et al., "Multivariate Time Series Dataset for Space Weather Data Analytics," Scientific Data, Vol. 7(227), Springer Nature, 2020, pp. 1-13.

MVTS-Data Toolkit: A Python package for preprocessing multivariate time series data

A. Ahmadzadeh, K. Sinha, B. Aydin, R. Angryk, "MVTS-Data Toolkit: A Python package for preprocessing multivariate time series data," SoftwareX, Vol. 12, Elsevier, 2020, pp. 1-6.

Efficient Image Retrieval by Fuzzy Rules from Boosting and Metaheuristic

M. Korytkowski, R. Senkerik, M.M. Scherer, R.A. Angryk, M. Kordos, A. Siwocha, "Efficient Image Retrieval by Fuzzy Rules from Boosting and Metaheuristic," Journal of Artificial Intelligence and Soft Computing Research, Vol. 10(1), 2020, pp. 57-69.

Rare-Event Time Series Prediction: A Case Study of Solar Flare Forecasting

A. Ahmadzadeh et al., "Rare-Event Time Series Prediction: A Case Study of Solar Flare Forecasting," Proc. IEEE ICMLA 2019, Boca Raton, December 2019, pp. 1814-1820.

Tensor Decomposition-based Node Embedding

S.M. Hamdi, S. Filali Boubrahimi, R.A. Angryk, "Tensor Decomposition-based Node Embedding," Proc. ACM CIKM 2019, Beijing, November 2019, pp. 2105-2108.

Interpretable Feature Learning of Graphs using Tensor Decomposition

S.M. Hamdi, R.A. Angryk, "Interpretable Feature Learning of Graphs using Tensor Decomposition," Proc. IEEE ICDM 2019, Beijing, November 2019, pp. 270-279.

Segmented Dynamic Time Warping: A Comparative and Applicational Study

R. Ma, A. Ahmadzadeh, S. Filali Boubrahimi, R.A. Angryk, "Segmented Dynamic Time Warping: A Comparative and Applicational Study," in Zongmin Ma & Li Yan (Eds.), Emerging Technologies and Applications in Data Processing and Management, IGI Global, 2019, pp. 1-19.

Identification of Discriminative Subnetwork from fMRI-based Complete Functional Connectivity Networks

S.M. Hamdi, Y. Wu, R. Angryk, L.C. Krishnamurthy, R. Morris, "Identification of Discriminative Subnetwork from fMRI-based Complete Functional Connectivity Networks," International Journal of Semantic Computing, Vol. 13(1), 2019, World Scientific, pp. 25-44.

A Curated Image Parameter Data Set from the Solar Dynamics Observatory Mission

A. Ahmadzadeh, D.J. Kempton, R.A. Angryk, "A Curated Image Parameter Data Set from the Solar Dynamics Observatory Mission," The Astrophysical Journal Supplement Series, Vol. 243(1), 2019, IOP Publishing, pp. 1-23.

Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories

B. Aydin and R.A. Angryk, "Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories," Springer, October 2018, ISBN 978-3-319-99872-5, 106 p., DOI: 10.1007/978-3-319-99873-2.

Neuro-Ensemble for Time Series Data Classification

S. Filali Boubrahimi, R. Ma, R. Angryk, "Neuro-Ensemble for Time Series Data Classification," Proc. IEEE/ACM DSAA 2018, Italy, October 2018, pp. 1-10.

Tracking Solar Phenomena from the SDO

D.J. Kempton, M.A. Schuh, R.A. Angryk, "Tracking Solar Phenomena from the SDO," The Astrophysical Journal, Vol. 869(1), 2018, IOP Publishing, pp. 1-54.

Spatiotemporal Interpolation Methods for Solar Event Trajectories

S. Filali Boubrahimi, B. Aydin, M.A. Schuh, D. Kempton, R.A. Angryk, R. Ma, "Spatiotemporal Interpolation Methods for Solar Event Trajectories," The Astrophysical Journal Supplement Series, Vol. 236(1), 2018, IOP Publishing, pp. 1-23.

Beyond Accuracy - A SMART Approach to Site-Based Spatio-Temporal Data Quality Assessment

D. Galarus, R. Angryk, "Beyond Accuracy - A SMART Approach to Site-Based Spatio-Temporal Data Quality Assessment," International Journal of Intelligent Data Analysis, Vol. 22(1), IOS Press, 2018, pp. 21-43.

Prediction of Solar Eruptions using Filament Metadata

A. Aggarwal, N. Schanche, K.K. Reeves, D. Kempton, R. Angryk, "Prediction of Solar Eruptions using Filament Metadata," The Astrophysical Journal Supplement Series, Vol. 236(1), 2018, IOP Publishing, pp. 1-15.

Coronal Mass Ejection Data Clustering and Visualization of Decision Trees

R. Ma, R.A. Angryk, P. Riley, S. Filali Boubrahimi, "Coronal Mass Ejection Data Clustering and Visualization of Decision Trees," The Astrophysical Journal Supplement Series, Vol. 236(1), 2018, IOP Publishing, pp. 1-14.

Solar Flare Prediction using Multivariate Time Series Decision Trees

R. Ma, S. Filali, S.M. Hamdi, R. Angryk, "Solar Flare Prediction using Multivariate Time Series Decision Trees," Proc. IEEE BigData 2017, Boston, December 2017, pp. 2487-2496.

Multi-wavelength Solar Event Detection using Faster R-CNN

A. Kucuk, B. Aydin, R. Angryk, "Multi-wavelength Solar Event Detection using Faster R-CNN," Proc. IEEE BigData 2017, Boston, December 2017, pp. 2470-2476.

A large-scale solar dynamics observatory image dataset for computer vision applications

A. Kucuk, J.M. Banda, R.A. Angryk, "A large-scale solar dynamics observatory image dataset for computer vision applications," Scientific Data, Vol. 4, Springer Nature, 2017, pp. 1-9. DOI: 10.1038/sdata.2017.96.

An Integrated Solar Database (ISD) with Extended Spatiotemporal Querying Capabilities

A. Kucuk et al., "An Integrated Solar Database (ISD) with Extended Spatiotemporal Querying Capabilities," Proc. SSTD 2017, LNCS Vol. 10411, Springer, 2017, pp. 405-411.

Measuring the Significance of Spatiotemporal Co-occurrences

B. Aydin, A. Kucuk, R.A. Angryk, P. Martens, "Measuring the Significance of Spatiotemporal Co-occurrences," ACM Transactions on Spatial Algorithms and Systems, Vol. 3(3), 2017, ACM, pp. 9:1-9:35.

Describing Solar Images with Sparse Coding for Similarity Search

D.J. Kempton, M.A. Schuh, R.A. Angryk, "Describing Solar Images with Sparse Coding for Similarity Search," Proc. IEEE BigData 2016, Washington DC, December 2016, pp. 3168-3176.

The SMART Approach to Comprehensive Quality Assessment of Site-Based Spatial-Temporal Data

D.E. Galarus, R.A. Angryk, "The SMART Approach to Comprehensive Quality Assessment of Site-Based Spatial-Temporal Data," Proc. IEEE BigData 2016, Washington DC, December 2016, pp. 2636-2645.

A Graph-based Approach to Spatiotemporal Event Sequence Mining

B. Aydin, R.A. Angryk, "A Graph-based Approach to Spatiotemporal Event Sequence Mining," Proc. IEEE ICDMW 2016, Barcelona, December 2016, pp. 1090-1097.

Enabling high-dimensional range queries using kNN indexing techniques: approaches and empirical results

T. Wylie, M.A. Schuh, R.A. Angryk, "Enabling high-dimensional range queries using kNN indexing techniques: approaches and empirical results," Journal of Combinatorial Optimization, Vol. 32(4), Springer, 2016, pp. 1107-1132.

Mining At Most Top-K% Spatiotemporal Co-occurrence Patterns in Data Sets with Extended Spatial Representations

K. Ganesan Pillai, R.A. Angryk, J.M. Banda, D. Kempton, B. Aydin, P. Martens, "Mining At Most Top-K% Spatiotemporal Co-occurrence Patterns in Data Sets with Extended Spatial Representations," ACM Transactions on Spatial Algorithms and Systems, Vol. 2(3), 2016, ACM, pp. 1-27.

Modeling and Indexing Spatiotemporal Trajectory Data in Non-Relational Databases

B. Aydin, V. Akkineni, R. Angryk, "Modeling and Indexing Spatiotemporal Trajectory Data in Non-Relational Databases," in Zongmin Ma (Ed.), Managing Big Data in Cloud Computing Environments, IGI Global, 2016, pp. 133-162.

Mining Spatiotemporal Co-occurrence Patterns in Non-Relational Databases

B. Aydin, V. Akkineni, R. Angryk, "Mining Spatiotemporal Co-occurrence Patterns in Non-Relational Databases," GeoInformatica, Vol. 20(4), Springer, 2016, pp. 801-828.

Spatio-Temporal Quality Control: Implications and Applications for Data Consumers and Aggregators

D. Galarus, R. Angryk, "Spatio-Temporal Quality Control: Implications and Applications for Data Consumers and Aggregators," Open Geospatial Data, Software and Standards, Vol. 1(2), Springer, 2016, pp. 1-23.

SPARQL Queries on RDF with Fuzzy Constraints and Preferences

R. Ma, X. Jia, J. Cheng, R.A. Angryk, "SPARQL Queries on RDF with Fuzzy Constraints and Preferences," Journal of Intelligent and Fuzzy Systems, Vol. 30(1), IOS Press, 2016, pp. 183-195.

Large-scale Dataset of Solar Event Reports from Automated Feature Recognition Modules

M.A. Schuh, R.A. Angryk, P.C. Martens, "Large-scale Dataset of Solar Event Reports from Automated Feature Recognition Modules," Journal of Space Weather and Space Climate, Vol. 6(A22), EDP Sciences, 2016, pp. 1-18.

Unsupervised Learning Techniques for Detection of Regions of Interest in Solar Images

J.M. Banda, R.A. Angryk, "Unsupervised Learning Techniques for Detection of Regions of Interest in Solar Images," Proc. IEEE ICDMW 2015, Atlantic City, November 2015, pp. 582-588.

Tracking Solar Events through Iterative Refinement

D.J. Kempton, R.A. Angryk, "Tracking Solar Events through Iterative Refinement," Astronomy and Computing, Vol. 13(1), Elsevier, 2015, pp. 124-135.

Mining spatiotemporal co-occurrence patterns in solar datasets

B. Aydin, D. Kempton, V. Akkineni, R. Angryk, K.G. Pillai, "Mining spatiotemporal co-occurrence patterns in solar datasets," Astronomy and Computing, Vol. 13(1), Elsevier, 2015, pp. 136-144.

Solar Image Parameter Data from the SDO: Long-term Curation and Data Mining

M.A. Schuh, R.A. Angryk, P.C. Martens, "Solar Image Parameter Data from the SDO: Long-term Curation and Data Mining," Astronomy and Computing, Vol. 13(1), Elsevier, 2015, pp. 86-98.

Regional content-based image retrieval for solar images: Traditional versus modern methods

J.M. Banda, R.A. Angryk, "Regional content-based image retrieval for solar images: Traditional versus modern methods," Astronomy and Computing, Vol. 13(1), Elsevier, 2015, pp. 108-116.

On Visualization Techniques for Solar Data Mining

M.A. Schuh, J.M. Banda, T. Wylie, P. McInerney, K. Ganesan Pillai, R.A. Angryk, "On Visualization Techniques for Solar Data Mining," Astronomy and Computing, Vol. 10(2), Elsevier, 2015, pp. 32-42.

Iterative Refinement of Multiple Targets Tracking of Solar Events

D. Kempton, K. Ganesan Pillai, R. Angryk, "Iterative Refinement of Multiple Targets Tracking of Solar Events," Proc. IEEE BigData 2014, Washington DC, October 2014, pp. 36-44.

Massive Labeled Solar Image Data Benchmarks for Automated Feature Recognition

M. Schuh, R. Angryk, "Massive Labeled Solar Image Data Benchmarks for Automated Feature Recognition," Proc. IEEE BigData 2014, Washington DC, October 2014, pp. 53-60.

A Comparative Evaluation of Automated Solar Filament Detection

M.A. Schuh, J.M. Banda, P.N. Bernasconi, R.A. Angryk, P.C.H. Martens, "A Comparative Evaluation of Automated Solar Filament Detection," Solar Physics, Vol. 289(7), Springer-Verlag, 2014, pp. 2503-2524.

A Filter-and-Refine Approach to Mine Spatiotemporal Co-occurrences

K. Ganesan Pillai, R. Angryk, B. Aydin, "A Filter-and-Refine Approach to Mine Spatiotemporal Co-occurrences," Proc. ACM SIGSPATIAL 2013, Orlando, November 2013, pp. 114-123.

imageFARMER: Introducing a Data Mining Framework for the Creation of Large-scale Content-based Image Retrieval Systems

J.M. Banda, R.A. Angryk, P.C.H. Martens, "imageFARMER: Introducing a Data Mining Framework for the Creation of Large-scale Content-based Image Retrieval Systems," International Journal of Computer Applications, Vol. 79(13), FCS, 2013, pp. 8-13.

A Large-Scale Solar Image Dataset with Labeled Event Regions

M.A. Schuh, R.A. Angryk, K. Ganesan Pillai, J.M. Banda, P.C.H. Martens, "A Large-Scale Solar Image Dataset with Labeled Event Regions," Proc. IEEE ICIP 2013, Melbourne, September 2013, pp. 4349-4353.

Comparison of two kinds of fuzzy arithmetic, LR and OFN, applied to fuzzy observation of the cofferdam water level

J.M. Czerniak, W.T. Dobrosielski, R.A. Angryk, "Comparison of two kinds of fuzzy arithmetic, LR and OFN, applied to fuzzy observation of the cofferdam water level," Computer Science, Vol. 14(3), AGH University, 2013, pp. 443-457.

An IEEE Standards-based Visualization Tool for Knowledge Discovery in Maintenance Event Sequences

M. Schuh, J. Sheppard, S. Strasser, R. Angryk, C. Izurieta, "An IEEE Standards-based Visualization Tool for Knowledge Discovery in Maintenance Event Sequences," IEEE Aerospace and Electronic Systems Magazine, Vol. 28(7), IEEE, 2013, pp. 30-39.

Steps toward Large-Scale Solar Image Data Analysis to Differentiate Solar Phenomena

J.M. Banda, R.A. Angryk, P.C.H. Martens, "Steps toward Large-Scale Solar Image Data Analysis to Differentiate Solar Phenomena," Solar Physics, Vol. 288(1), Springer-Verlag, 2013, pp. 435-462.

Abstracting for Dimensionality Reduction in Text Classification

R.A. McAllister, R.A. Angryk, "Abstracting for Dimensionality Reduction in Text Classification," International Journal of Intelligent Systems, Vol. 28(2), Wiley, 2013, pp. 115-138.

On Dimensionality Reduction for Indexing and Retrieval of Large-scale Solar Image Data

J. Banda, R. Angryk, P. Martens, "On Dimensionality Reduction for Indexing and Retrieval of Large-scale Solar Image Data," Solar Physics, Vol. 283(1), Springer-Verlag, 2013, pp. 113-141.

Computer Vision for the Solar Dynamics Observatory (SDO)

P.C.H. Martens et al., "Computer Vision for the Solar Dynamics Observatory (SDO)," Solar Physics, Vol. 275(1), Springer-Verlag, 2012, pp. 79-113.

On the Surprisingly Accurate Transfer of Image Parameters between Medical and Solar Images

J.M. Banda, R.A. Angryk, P. Martens, "On the Surprisingly Accurate Transfer of Image Parameters between Medical and Solar Images," Proc. IEEE ICIP 2011, Brussels, September 2011, pp. 3669-3672.

Semantically-Guided Clustering of Text Documents via Frequent Subgraphs Discovery

R. Angryk, M.S. Hossain, B. Norick, "Semantically-Guided Clustering of Text Documents via Frequent Subgraphs Discovery," Foundations of Intelligent Systems, LNCS Vol. 6804, Springer-Verlag, 2011, pp. 407-417.

Heuristic Algorithm for Interpretation of Multi-Valued Attributes in Similarity-based Fuzzy Relational Databases

R. Angryk, J. Czerniak, "Heuristic Algorithm for Interpretation of Multi-Valued Attributes in Similarity-based Fuzzy Relational Databases," International Journal of Approximate Reasoning, Vol. 51(8), Elsevier, 2010, pp. 895-911.

On the Effectiveness of Fuzzy Clustering as a Data Discretization Technique for Large-scale Classification of Solar Images

J.M. Banda, R. Angryk, "On the Effectiveness of Fuzzy Clustering as a Data Discretization Technique for Large-scale Classification of Solar Images," Proc. FUZZ-IEEE 2009, Jeju Island, Korea, August 2009, pp. 2019-2024.

Attribute-Oriented Defuzzification of Fuzzy Database Tuples with Conjunctive Interpretation of Categorical Entries

R. Angryk, "Attribute-Oriented Defuzzification of Fuzzy Database Tuples with Conjunctive Interpretation of Categorical Entries," Control and Cybernetics, Vol. 38(2), Polish Academy of Sciences, 2009, pp. 419-453.

An Efficient Abstraction-Based Data Model for Information Retrieval

R. McAllister, R. Angryk, "An Efficient Abstraction-Based Data Model for Information Retrieval," Advances in Artificial Intelligence, LNCS Vol. 5866, Springer-Verlag, 2009, pp. 567-576.

An Example-based Image Retrieval System for the TRACE Repository

R. Lamb, R. Angryk, P. Martens, "An Example-based Image Retrieval System for the TRACE Repository," Proc. ICPR 2008, Tampa, FL, December 2008, pp. 1-4.

Generating Concept Hierarchies from User Queries

B. Wall, N. Richter, R. Angryk, "Generating Concept Hierarchies from User Queries," in T.Y. Lin et al. (Eds.), Data Mining: Foundations and Practice, SCI Vol. 118, Springer-Verlag, 2008, pp. 423-442.

GDClust: A Graph-Based Clustering Technique for Text Documents

M.S. Hossain, R. Angryk, "GDClust: A Graph-Based Clustering Technique for Text Documents," Proc. IEEE ICDM 2007 Workshop, Omaha, October 2007, pp. 417-422.

Attribute-Oriented Fuzzy Generalization in Proximity- and Similarity-Based Relational Database Systems

R. Angryk, F. Petry, "Attribute-Oriented Fuzzy Generalization in Proximity- and Similarity-Based Relational Database Systems," International Journal of Intelligent Systems, Vol. 22(7), Wiley, 2007, pp. 763-779.

Algorithm for Defuzzification of Multi-Valued Taxonomic Attributes in Similarity-Based Fuzzy Relational Databases

M.S. Hossain, R. Angryk, "Algorithm for Defuzzification of Multi-Valued Taxonomic Attributes in Similarity-Based Fuzzy Relational Databases," Theoretical Advances and Applications of Fuzzy Logic, ASC Vol. 42, Springer-Verlag, 2007, pp. 23-35.

Similarity-driven Defuzzification of Fuzzy Tuples for Entropy-based Data Classification Purposes

R. Angryk, "Similarity-driven Defuzzification of Fuzzy Tuples for Entropy-based Data Classification Purposes," Proc. FUZZ-IEEE 2006, Vancouver, July 2006, pp. 1490-1498.

Development of Ontologies by the Lowest Common Abstraction of Terms Using Fuzzy Hypernym Chains

R. Angryk, J. Dolan, F. Petry, "Development of Ontologies by the Lowest Common Abstraction of Terms Using Fuzzy Hypernym Chains," in Zongmin Ma (Ed.), Soft Computing in Ontologies and Semantic Web, SCI Vol. 204, Springer-Verlag, 2006, pp. 123-148.

On Interpretation of Non-Atomic Values and Induction of Decision Rules in Fuzzy Relational Databases

R. Angryk, "On Interpretation of Non-Atomic Values and Induction of Decision Rules in Fuzzy Relational Databases," in L. Rutkowski et al. (Eds.), Artificial Intelligence and Soft Computing, LNAI Vol. 4029, Springer-Verlag, 2006, pp. 170-181.

Knowledge Discovery in Fuzzy Databases Using Attribute-Oriented Induction

R. Angryk, F. Petry, "Knowledge Discovery in Fuzzy Databases Using Attribute-Oriented Induction," in T.Y. Lin et al. (Eds.), Foundations and Novel Approaches in Data Mining, SCI Vol. 9, Springer-Verlag, 2006, pp. 169-196.

Discovery of Abstract Knowledge from Non-Atomic Attribute Values in Fuzzy Relational Databases

R. Angryk, F. Petry, "Discovery of Abstract Knowledge from Non-Atomic Attribute Values in Fuzzy Relational Databases," in B. Bouchon-Meunier et al. (Eds.), Modern Information Processing, Elsevier, 2006, pp. 171-182.

Creating Concept Hierarchies in an Information Retrieval System

B. Wall, N. Richter, R. Angryk, "Creating Concept Hierarchies in an Information Retrieval System," Proc. IEEE ICDM 2005 Workshop, Houston, November 2005, pp. 99-105.

Mining Multi-Level Associations with Fuzzy Hierarchies

R. Angryk, F. Petry, "Mining Multi-Level Associations with Fuzzy Hierarchies," Proc. FUZZ-IEEE 2005, Reno, NV, May 2005, pp. 785-790.

Fuzzy Induction in Dynamic User Profiling for Information Filtering

R. Angryk, C. Barbu, "Fuzzy Induction in Dynamic User Profiling for Information Filtering," Proc. AAAI 2004, San Jose, CA, July 2004, pp. 946-947.

Generalization Data Mining of Fuzzy Object-Oriented Databases

R. Angryk, R. Ladner, F. Petry, "Generalization Data Mining of Fuzzy Object-Oriented Databases," in Zongmin Ma (Ed.), Advances in Fuzzy Object-Oriented Databases, Idea Group Publishing, 2004, pp. 85-112.

Data Mining Fuzzy Databases Using Attribute-Oriented Generalization

R. Angryk, F. Petry, "Data Mining Fuzzy Databases Using Attribute-Oriented Generalization," Proc. IEEE ICDM 2003 Workshop, Melbourne, FL, November 2003, pp. 8-15.

Fuzzy Spatial Relationships and Mobile Agent Technology in Geospatial Information Systems

F. Petry, M. Cobb, D. Ali, R. Angryk et al., "Fuzzy Spatial Relationships and Mobile Agent Technology in Geospatial Information Systems," in P. Matsakis & L.M. Sztandera (Eds.), Applying Soft Computing in Defining Spatial Relations, Physica-Verlag, 2002, pp. 123-155.

Rafal Angryk, Ph.D.

CV

Education

Work experience

Skills

Publications

Talks

Teaching

Service and leadership