Recent Publications

Ghebrechristos, H., Alaghband, G. “Immunizing Image Classifiers Against Localized Adversary Attack,” International Journal of Artificial Intelligence & Applications (IJAIA), Vol. 15, No. 2,  pp. 77-99, March 2024. 

Linck, I., Gσmez, A.T. & Alaghband, G. "SVG-CNN: A shallow CNN based on VGGNet applied to intra prediction partition block in HEVC". Multimed Tools Appl (2024).

Ghebrechristos, H., Alaghband, G. “3D convolution for Proactive Defense Against Localized Adversary Attacks,” 12th International Conference on Soft Computing, Artificial Intelligence and Applications (SCAI 2023), December 23, Sydney, Australia,

McCarthy, S., Alaghband, G., “The Emotion Magnitude Effect: Navigating Market Dynamics Amidst Supply Chain Events,” J. Risk Financial Manag. 2023, 16(12), 490, (21 pages);  https://doi.org/10.3390/jrfm16120490

Manh Huynh, Alaghband, G.," Multi-modal Sensor Framework with Learnable Uncertainty Estimator for Pedestrian Trajectory Prediction,” 2023 IEEE Conference on Intelligent Transportation Systems (ITSC 2023).

Alghamdi, T.; Alaghband, G. SAFEPA: “An Expandable Multi-Pose Facial Expressions Pain Assessment Method,” Appl. Sci. 2023, 13, 7206.

McCarthy, S., Alaghband, G., “Enhancing Financial Market Analysis and Prediction with Emotion Corpora and News Co-Occurrence Network,” J. Risk Financial Manag. 2023, 16(4), 226.

Henok Ghebrechristos1*, Stence Nicholas2*, David Mirsky MD*, Manh Huynh, Zackary Kromer, Ligia Batista1, Gita Alaghband PhD1, Brent O’Neill MD2, Steven Moulton MD, Daniel M. Lindberg MD, “Deep Learning Mixture-of-Experts for Cytotoxic Edema Assessment in Infants and Children,” 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), Cartagena de Indias, Colombia

Ligia Batista*, Nicholas V. Stence, David M Mirsky, Terri Lewis, Sarah Graber, Henok Ghebechristos, Gita Alaghband, Brent O’Neil, Daniel M. Lindberg., “Cytotoxic Edema is Associated with Injury Severity but not Abusive Mechanism in Young Children with Severe Brain Injury,” Annual Meeting of the Helfer Society. April, 2023. Tucson, AZ.

Linck, I., Gomez, A. T., Alaghband, G. ," CNN Quadtree Depth Decision Prediction for Block Partitioning in HEVC Intra-Mode" 2023 Data Compression Conference (DCC 23), UT.

Manh Huynh, Alaghband, G.,"Online Adaptive Temporal Memory with Certainty Estimation for Human Trajectory Prediction," (WACV 23)


Alghamdi, T., Alaghband, G., “Facial Expressions Based Automatic Pain Assessment System,” Special Issue Recent Advances in Deep Learning for Image Analysis, Appl. Sci. 2022, 12(13), 6423; (16 pages)  https://doi.org/10.3390/app12136423


Manh Huynh, Alaghband, G., "GPRAR: Graph Convolutional Network based Pose Reconstruction and Action Recognition for Human Trajectory Prediction," (2021).

 

Takano, N.,  Alaghband, G., “Generator From Edges: Reconstruction of Facial Images,” 15th International Symposium on Visual Computing (ISVC'20)

 

Manh, H., Alaghband, G., “AOL: Adaptive Online Learning for Human Trajectory Prediction in Dynamic Video

Scenes,” The British Machine Vision Conference (BMVC ‘20)

 

Ghebrechristos, H., Alaghband, G. Deep curriculum learning optimization. SN COMPUT. SCI. 1, 245 (2020). https://doi.org/10.1007/s42979-020-00251-7

 

Alghamdi, T., Alaghband, G., “A Novel CC*CNN Model for Face Recognition using Edge,” 14th  International Conference on Information Technology and Applications (ICITA 2020), IRC Best Paper Award.

 

Ghebrechristos, H.E, Alaghband, G., “Information Theory-Based Curriculum Learning Factory to Optimize Training,”  ACPR 2019. Lecture Notes in Computer Science, vol. 12046. Springer,  https://doi.org/10.1007/978-3-030-41404-7_29,  Auckland, New Zealand.

 

Ghebrechristos, H.E, Alaghband, G., “Optimizing Training using Information Theory-Based Curriculum Learning Factory,” 31st  International Conference on Tools with Artificial Intelligence (ICTAI 2019).

 

Alghamdi, T., Alaghband, G., “High Performance Parallel Sort for Shared and Distributed Memory MIMD,”

16th International Conference in Applied Computing (AC’2019),  Cagliari, Italy.

 

Manh, H., Alaghband, G., “Trajectory Prediction by Coupling Scene-LSTM with Human Movement LSTM,” In: Bebis G. et al. (eds) Advances in Visual Computing. ISVC 2019. Lecture Notes in Computer Science, vol 11844, Springer. https://doi.org/10.1007/978-3-030-33720-9_19, Lake Tahoe, Nevada

 

Manh, H., Alaghband, G., “Scene-LSTM: A Model for Human Trajectory Prediction,” arXiv:1808.04018 [cs.CV], April 2019.

 

Takano, N.,  Alaghband, G., “SRGAN: What the neural network learns,” The 23rd International Conference on Image Processing, Computer Vision,& Pattern Recognition (IPCV'19) .

 

Ghebrechristos, H.E, Alaghband, G., “Expediting Training Using Information Theory-Based Patch Ordering Algorithm,” International Conference on Computational Science and Computational Intelligence (CSCI'18).

 

Linck, I., Alaghband, G., “Test Zonal Search based on Region Label (TZSR) for Motion Estimation in HEVC,” (MMSP 2018) 2018 IEEE 20th International Workshop on Multimedia Signal Processing, Vancouver, BC, 2018, pp. 1-6, doi: 10.1109/MMSP.2018.8547127.

 

Manh, H., Alaghband, G., “Spatiotemporal KSVD Dictionary Learning for Online Multi-target Tracking,” Proceedings of the 15th Computer and Robot Vision (CRV 2018), Toronto, Ontario, CA. doi: 10.1109/CRV.2018.00030

 

Gnabasik, D., Alaghband, G., “A Data-driven Biomarker Computational Model for Lung Disease Classification,” Proceedings of the 10th International Conference on Bioinformatics and Computational Biology (BICOB 2018),  Las Vegas, USA.

 

Ghebrechristos, H.E, Alaghband, G., “RetiNet - Feature Extractor for Learning Patterns of Diabetic Retinopathy and Age-Related Macular Degeneration from Publicly Available Datasets,” Health Informatics and Medical Systems (CSCI-ISHI) in International Conference on Computational Science and Computational Intelligence (CSCI'17),  Las Vegas, USA.

 

Simonton, T., Alaghband, G., “Efficient and Accurate Word2Vec Implementations in GPU and Shared-Memory Multicore Architectures,” 2017 IEEE High Performance Extreme Computing Conference (HPEC ‘17), Waltham, MA USA, 12 - 14 September 2017, pp. 1-7.  http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8091076

 

Alaghband, G., Fardi, H. Z., “Parallel Programming Multi-core Computers,” Proceedings of the 2016 STEM Education Hawaii University International Conferences on Science, http://www.huichawaii.org/steam2016.html , Honolulu, Hawaii, June 10-12, 2016 pp.1-11. http://www.huichawaii.org/assets/alaghband%2c-gita---2016-steam-huic.pdf

 

Vu, L., Alaghband, G., “A Load Balancing Parallel Method for Frequent Pattern Mining on Multi-core Cluster,” Proceedings of HPC Symposium, 2015 Spring Simulation Multi-Conference (SpringSim’15), Simulation Series, pp. 49-59,  in Vol. 47, No. 4, April 12-15, 2015, Alexandria, Virginia, USA.

 

Vu, L., Alaghband, G., “A Self-Adaptive Method for Frequent Pattern Mining using a CPU-GPU Hybrid Model,” Proceedings of HPC Symposium, 2015 Spring Simulation Multi-Conference (SpringSim’15), Simulation Series, pp. 192-202 in Vol. 47, No. 4, April 12-15, 2015, Alexandria, Virginia, USA.

 

Vu, L., Alaghband, G., “Novel parallel method for association rule mining on multi-core shared memory systems,” Parallel Computing, Volume 40, Issue 10, December 2014, Pages 768–785. (Special Section on 2013 Workshop on Data Intensive Scalable Computing Systems (DISCS-2013) edited by Dr. Philip C. Roth and Dr. Yong Chen, doi:10.1016/j.parco.2014.08.003, http://www.sciencedirect.com/science/article/pii/S0167819114001124 

 

Vu, L., Alaghband, G., “Efficient Algorithms for Mining Frequent Patterns from Sparse and Dense Databases,” Journal of Intelligent Systems, ISSN (Online ahead of print) 2191-026X, ISSN (Print) 0334-1860, DOI: 10.1515/jisys-2014-0040, September 2014, pp.181-197 in Vol. 24, Issue 2, March/April 2015.

 

Kern, D., and Alaghband, G., “Parallel Processing of Irregular Workloads on the GPGPU: Adaptive Quadrature,” Proceedings of the PDPTA'14: The 2014 International Conference on Parallel and Distributed Processing Techniques and Applications, Vol. 2, pp. 423-429,   July 21-24, 2014, Las Vegas, Nevada, USA, http://worldcomp-proceedings.com/proc/proc2014/pdpta.html, http://worldcomp-proceedings.com/proc/p2014/PDP.htmlpp.

 

Fardi, H., Pace, S., Alaghband, G., “A Semiconductor Device Simulator Utilizing MATLAB,” Proceedings of the 2014 Hawaii University International Conferences on Science, Technology, Engineering, Math and Education, http://www.huichawaii.org/steam2014p.html , Honolulu, Hawaii, June 16-18, 2014 pp1-10. http://www.huichawaii.org/assets/fardi_hamid_-_et_al_stem_2014.pdf

 

Fardi, H., Alaghband, G., “Assessment Strategies for Student Recruitment and Retention in Engineering,” Global Science and Technology Forum (GSTF), Journal on Education (JED), Vol. 2, No. 1. pp. 74-80, June 2014. dl6.globalstf.org/index.php/jed/article/download/686/693

 

Gnabasik, D., Alaghband, G., “Discrete Time Evolution of Proteomic Biomarkers,” Proceedings of the CSCI 2014, International Conference on Computational Science and Computational Intelligence, Las Vegas, Nevada, USA, Vol. 2, pp. 11-16, March 10-13, 2014. http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6820887 , http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6822296

 

Vu, L., Alaghband, G. “An Efficient Approach for Mining Association Rules from Sparse and Dense Databases” Proceedings of the  International Conference on Information and Knowledge Management 2014  (ICIKM’2014), World Congress on Computer and Information Systems 2014 (WCCAIS’2014), January 17-19, pp. 1-8, Hammamet, Tunisia. 10.1109/WCCAIS.2014.6916550, http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&tp=&arnumber=6916550

 

Vu, L.; Alaghband, G., "Novel Parallel Method for Mining Frequent Patterns on Multi-core Shared Memory Systems," in Proc. of the ACM 2013 Int. Workshop on Data-Intensive Scalable Computing Systems, Supercomputing 2013, Nov 2013, pp. 49-54, Denver, Colorado. http://dl.acm.org/citation.cfm?id=2534653

 

Aydin, A. A.; Alaghband, G., “Sequential & Parallel Hybrid Approach for Non-Recursive Most Significant Digit Radix Sort,” Proceedings of the IADIS Applied Computing 2013, October 23-25, 2013, pp. 51-59, Fort Worth, Texas.

 

Mohammed, M.; Alaghband, G., “An Improved Parallel Eight Direction Prewitt Edge Detection Algorithm,” Proceedings of the 17th International Conference on Image Processing, Computer Vision, & Pattern Recognition, WorldComp’ 13, pp. 852-860, July 22-25, 2013, Las Vegas, Nevada.

 

Vu, L.; Alaghband, G., “Mining Frequent Patterns Based on Data Characteristics,” Proceedings of the 2012 International Conference on Information & Knowledge Engineering, in-print, WorldComp’ 12, July 16-19, 2012, pp. 369-376, Las Vegas, Nevada.

 

Gnabasik, D.; Alaghband, G., “Proteomic Data Analysis: a Topological Approach,” Proceedings of the 2012 International Conference on Bioinformatics and Computational Biology BIOCOMP, in-print, WorldComp’ 12, July 16-19, 2012, Las Vegas, Nevada.

 

Vu, L.; Alaghband, G., “High Performance Frequent Pattern Mining on Multi-core Cluster,” IEEE Proceedings of the 2012 International Conference on Collaboration Technologies and Systems (CTS 2012), pp. 630- 633, May 21-25, 2012, Denver, Colorado.

 

Gnabasik, D.; Alaghband, G., “Topological Analysis of Proteomic Data,”  IEEE Proceedings of the 2012 International Conference on Collaboration Technologies and Systems (CTS 2012), pp. 634- 635, May 21-25, 2012, Denver, Colorado.

 

Vu, L.; Alaghband, G., “A Fast Algorithm Combining FP-Tree and TID-List for Frequent Pattern Mining,” Proceedings of the 2011 International Conference on Information & Knowledge Engineering, pp. 472-477, WorldComp’ 11, July 18-21, 2011, Las Vegas, Nevada.

 

Alaghband, G. , “Relationship model: a network model for integrating human expertise with systematic distributed processes,” Journal of Software Maintenance and Evolution: Research and Practice, Volume 23, Issue 2, March 2011, Pages: 109–135, Article first published online : 4 MAY 2010, DOI: 10.1002/smr.471 http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1532-0618/earlyview.