research articles

Publication Topics (See IEEE Xplore)

Artificial Neural Network, Artificial Neural Network Model, Convolutional Neural Network, Feature Space, Neural Network, Feature Learning, Grayscale Images, Ground Truth Labels, Low False Positives, Machine Learning Models, Machine Learning Techniques, Support Vector Machine, Training Set, Accuracy Loss, Artificial Neural Network Classifier, Artificial Neural Network Training, Background Subtraction, Ballistic Movements, Bayes Factor, Bayesian Model, Binary Image, Binary Segmentation, Brain Injury, Brain Magnetic Resonance Imaging, Brain Tumor Classification, Brain Tumor Detection, Bullet Points, Classification Techniques, Computational Environment, Concept Of Learning, Control Experiments, Convolutional Neural Network Classifier, Credible Interval, Data Normalization, Data Privacy, Deep Learning Techniques, Digital Video, Dimensionality Reduction, Dimensions Of Factors, Extract Relevant Features, Eye Motion, Eye Movements, Eye Velocity, F1 Score, Factor Analysis, Factor Loadings, Factor Model, Factorization, Feature Extraction Techniques, Feature Information

2025

Shan Suthaharan, "A Nature-Inspired Colony of Artificial Intelligence System with Fast, Detailed, and Organized Learner Agents for Enhancing Diversity and Quality," to be published at the Agentic AI for Science: Hypothesis Generation, Comprehension, Quantification, and Validation Symposium, as part of AAAI Spring Symposium Series, 2025 in San Francisco, CA (March 31–April 2, 2025).

2024

Ahmed Ben-Aissa, Shan Suthaharan, Yao Cai, Kate Grieve, and Pedro Mecê, "Learning-based clustering of multi-depth time-domain full-field OCT retinal images." In Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXVIII, p. PC128300S. SPIE, 2024.
Shan Suthaharan, "tIFFS: An approach to define a theoretically infinite family of feature space for an artificial intelligence framework." In Emerging Topics in Artificial Intelligence (ETAI) 2024, vol. 13118, pp. 54-58. SPIE, 2024.
Shan Suthaharan. "Colony of AI: Towards building families of AI-agents using theory of genetic algorithm and bias randomization." In Emerging Topics in Artificial Intelligence (ETAI) 2024, vol. 13118, pp. 59-62. SPIE, 2024.
Shan Suthaharan, "Detective AI: distinguishing AI generated and real images by leveraging the concept of cross-correlation of connected image components of bit-planes." In Emerging Topics in Artificial Intelligence (ETAI) 2024, vol. 13118, pp. 43-49. SPIE, 2024.
Shan Suthaharan, "Modeling and simulation of noise vectors for improving diversity and quality of a generative AI." In Applications of Machine Learning 2024, vol. 13138, pp. 143-148. SPIE, 2024.
Ayodeji Iwayemi, and Shan Suthaharan. "Detecting decision-makers of an AI system in the feature maps under uncertainty by leveraging Bayesian search theory." In Applications of Machine Learning 2024, vol. 13138, pp. 52-64. SPIE, 2024.
Adarsh Gadari, Sandeep Chandra Bollepalli, Mohammed Nasar Ibrahim, Jose Alain Sahel, Jay Chhablani, Shan Suthaharan, and Kiran Kumar Vupparaboina. "Retinal sublayer segmentation based on deep learning using optical coherence tomography B-Scans: Training multilayer masks vs boundary labels." Investigative Ophthalmology & Visual Science 65, no. 7 (2024): 2408-2408.

2023

Shan Suthaharan, "Modeling and simulation of a Tamil language encoder for advanced encryption technologies." Patterns, Cell Press, 2023, DOI:https://doi.org/10.1016/j.patter.2023.100740. Published on May 03, 2023.
Shan Suthaharan, Daniel Lee, Min Zhang and Ethan A. Rossi, "Microsaccade Segmentation using Directional Variance Analysis and Artificial Neural Networks," in Proc. of the 2023 IEEE 24th International Conference on Information Reuse and Integration for Data Science (IRI), pp. 1-6, DOI: https://doi.org/10.1109/IRI58017.2023.00008.
Shan Suthaharan, "nEGXAI: A negation-based explainable AI through feature learning in Fourier domain." In Emerging Topics in Artificial Intelligence (ETAI), vol. 12655, pp. 82-94, SPIE 2023.
Shan Suthaharan, "A frequency-driven deep learning technique for bird segmentation and detection from RGB video." In Applications of Machine Learning, vol. 12675, pp. 269-274, SPIE 2023.
Adarsh Gadari, Sandeep C. Bollepalli, Mohemmed N. Ibrahim, Sahel J. Alian, J. Chhablani, Shan Suthaharan*, and Kiran K. Vupparaboina*, "Robust Retinal Layer Segmentation Using OCT B-Scans: A Novel Approach Based on Pix2Pix Generative Adversarial Network," In Proc. of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB '23), Article No.: 52, pp 1–6, https://doi.org/10.1145/3584371.3612979.
Shan Suthaharan, "Harnessing the feature vectors of VGG-16 for birds detection under geometric distortions and brightness," In Proc. of the IEEE TransAI' 2023, pp. 19-26.
Shan Suthaharan, "Fall Detection using Machine Learning Techniques and Frequency-Driven Riemannian Manifolds," In Proc. of the IEEE ICMLA'2023, pp. 194-201.
Amitabha Dey and Shan Suthaharan, "LDEB: Label digitization with emotion binarization and machine learning for emotion recognition in conversational dialogues." preprint, https://arxiv.org/abs/2306.02193. Published on June 06, 2023.

2022

Shan Suthaharan, "Quantum aliasing: a negative influence of data scarcity on quantum machine learning." In Quantum Technologies 2022, vol. 12133, pp. 96-102. SPIE, 2022.
Aishwarya Gouru and Shan Suthaharan, “Facial Emotion Characterization and Detection using Fourier Transform and Machine Learning.” in Proc. of the 37th International Conference on Computers and Applications (CATA 2022) - https://compsci.uncg.edu/best-paper-award-at-the-cata-2022-conference/. (Received a best paper award).
Shan Suthaharan, "Scientific Tamil Lexicon: The Revelation of Cryptographic Connection Between Tamil Language and Galois Field." Preprint, https://osf.io/vb843. Published on January 16, 2022 .
Raveena Arasikere Rakesh and Shan Suthaharan, "Frequency-based Hilbert emotional feature space for emotion detection using machine learning." preprint, https://doi.org/10.21203/rs.3.rs-2365434/v1. Published on December 16th, 2022.

2021

Gunjan Chhablani, Yash Bhartia, Abheesht Sharma, Harshit Pandey and Shan Suthaharan, "NLRG at SemEval-2021 Task 5: Toxic Spans Detection Leveraging BERT-based Token Classification and Span Prediction Techniques ” In: Proceedings of the 15th international workshop on semantic evaluation (SemEval-2021). Association for Computational Linguistics, online, pp 233–242.
Raphael Lejoyeux, Raphael Atia, Kiran Vupparaboina, Mohamed Ibrahim, Shan Suthaharan, Jose-Alain Sahel, Kunal Dansingani, and Jay Chhablani. "En-face analysis of short posterior ciliary arteries crossing the sclera to choroid using wide-field swept-source optical coherence tomography," Scientific Reports 11, 8732 (2021). pp. 1-10. https://doi.org/10.1038/s41598-021-88205-8.
Shan Suthaharan, Gunjan Chhablani, Kiran K. Vupparaboina, Jose-Alain Sahel, Kunal K. Dansingani, Jay Chhablani. "An automated choroid segmentation approach using transfer learning and encoder-decoder networks," Investigative Ophthalmology & Visual Science 62, no. 8 (2021): 2158-21.
Kiran K. Vupparaboina, Amrish Selvam, Shan Suthaharan, Mohammed N. Ibrahim, Soumya Jana, Jose-Alain Sahel, Kunal Dansingani, Jay Chhablani. "Automated Choroid Layer Segmentation based on Wide-field SS-OCT Images using Deep Residual Encoder-decoder Architecture," Investigative Ophthalmology & Visual Science 62, no. 8 (2021): 2162-2162.

2020

Ritu Joshi and Shan Suthaharan. "Pixel-Level Feature Space Modeling and Brain Tumor Detection Using Machine Learning." In 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 821-826. IEEE, 2020.
Naseeb Thapaliya, Lavanya Goluguri, Shan Suthaharan, Asymptotically Stable Privacy Protection Technique for fMRI Shared Data over Distributed Computer Networks, BCB '20: Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, September 2020, Article No.: 100, pp 1–8, https://doi.org/10.1145/3388440.3414863.
Shan Suthaharan, Ethan A. Rossi, Valerie Snyder, Jay Chhablani, Raphael Lejoyeux, José-Alain Sahel, Kunal K. Dansingani, Laplacian feature detection and feature alignment for multimodal ophthalmic image registration using phase correlation and Hessian affine feature space. Signal Process. 177: 107733 (2020).
Shan Suthaharan, A low-sensitivity quantitative measure for traffic safety data analytics. Int. J. Data Sci. Anal. 9(2): 241-256 (2020).
Shan Suthaharan, Ethan Rossi, Valerie Snyder, Raphael Lejoyeux, Jay Chhablani, Jose Sahel, Kunal Dansingani. 2020. Multimodal ophthalmic image registration using Hessian feature spaces, ARVO 2020. Abstract published in Investigative Ophthalmology & Visual Science 61, no. 7 (2020): 1149-1149.
E. Gofas, M. Zhang, Y. Rei, V. Snyder, K. Vienola, S. Suthaharan, E. Rossi. 2020. A refined detection scheme and image processing pipeline for multioffset adaptive optics scanning light ophthalmoscopy improves the contrast of retinal ganglion cell layer neurons in humans, ARVO 2020. Abstract published in Investigative Ophthalmology & Visual Science 61, no. 7 (2020): 205-205.

2019

Shan Suthaharan, Weining Shen, Elliptical modeling and pattern analysis for perturbation models and classification. Int. J. Data Sci. Anal. 7(2): 103-113 (2019).
Firoozeh Karimi, Selima Sultana, Ali Shirzadi Babakan, Shan Suthaharan, An enhanced support vector machine model for urban expansion prediction. Comput. Environ. Urban Syst. 75: 61-75 (2019).
Firoozeh Karimi, Selima Sultana, Ali Shirzadi Babakan, Shan Suthaharan. Urban expansion modeling using an enhanced decision tree algorithm. Geoinformatica. pp. 1-17 (2019). https://doi.org/10.1007/s10707-019-00377-8.
Shan Suthaharan, Big data analytics: Machine learning and Bayesian learning perspectives - What is done? What is not? Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 9(1) (2019).
Suprateek Kundu and Shan Suthaharan, Privacy-Preserving Predictive Model Using Factor Analysis for Neuroscience Applications, in Proceedings of the 5th IEEE International Conference on Big Data Security on Cloud (BigDataSecurity 2019), pp. 67-73 (2019).
Selvarajah Mohanarajah, Gregorry Ross, Shan Suthaharan, Towards Encapsulated Cyber Security Labs: A Container Based Approach. SIGCSE 2019: 1267 (Poster, published in the proceedings).

2018

Shan Suthaharan, A software engineering schema for data intensive applications. ACM Southeast Regional Conference 2018: 23:1-23:8.
Shan Suthaharan, Characterization of differentially private logistic regression. ACM Southeast Regional Conference 2018: 15:1-15:8.
Vishali Vadakattu, Shan Suthaharan, Feature Extraction Using Apparent Power and Real Power for Smart Home Data Classification. ICMLA 2018: 1290-1295.

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