Publications

(* denotes CLS student author)

Book

K. Al-Jabery, T. Obafemi-Ajayi, G. Olbricht, D. Wunsch, “Computational Learning Approaches to Data Analytics in Biomedical Applications", Nov. 2019, Academic Press, Elsevier

Book Chapter

R. Kanawong, T. Obafemi-Ajayi, D. Liu, M. Zhang, D. Xu and Y. Duan, “Tongue Image Analysis and Its Mobile App Development for Health Diagnosis.” In Translational Informatics in Smart Healthcare (pp. 99-121). 2017 Springer.

Journals

Harder A, Olbricht GR, Ekuma G*, Hier DB, Obafemi-Ajayi T. "Multiple Imputation for Robust Cluster Analysis to address Missingness in Medical Data". IEEE Access. 12, pp.42974-42991. 2024.
Tony Astuhuaman D, Hier D, Obafemi-Ajayi T. "Towards Explainability of Dimension Reduction Plots of Unsupervised Learning Model Outcomes". 2024
Petrenko S, Hier D, Obafemi-Ajayi T, Bone M, Timpson E, Speight M. "Analyzing Biomedical Datasets with Symbolic Tree Adaptive Resonance Theory". Information, Special Edition on Adaptive Resonance Theory, 2024, 15(3), p.125.
Yelugam R, Hier D, Obafemi-Ajayi T, Carrithers M, Wunsch D. "A Formal Explanation Space for the Simultaneous Clustering of Neurology Phenotypes". Research Square pre-print server,2023
Foster L, Uribe-Zarain X, Obafemi-Ajayi T. "Microaggressions in the heartland “flyover” region: history, progress, lessons learned and challenges". Equality, Diversity and Inclusion. Dec 2023.
Matta J, Dobrino D, Yeboah D*, Howard S, EL-Manzalawy Y, Obafemi-Ajayi T. "Connecting Phenotype to Genotype: PheWAS-inspired Analysis of Autism Spectrum Disorder. Frontiers in Human Neuroscience-Brain Health and Clinical Neuroscience". 2022.
T. Obafemi-Ajayi, A. Perkins, B. Nanduri, B., D. Wunsch, J. Foster, J. Peckham, “No-boundary thinking: a viable solution to ethical data-driven AI in precision medicine”, AI Ethics (2021).
D. Hier, T. Obafemi-Ajayi, M. Thimgan, G. Olbricht, S. Azizi, B. Allen, B. Hadi, D. Wunsch, “Blood biomarkers for mild traumatic brain injury: a selective review of unresolved issues”, Biomarker Research, 9, 70, 2021.
L. Bui*, D. Yeboah*, L. Steinmeister, S. Azizi, D. Heir, D. Wunsch, G. Olbricht, T. Obafemi-Ajayi, "Heterogeneity in blood biomarker trajectories after mild TBI revealed by unsupervised learning." IEEE/ACM Transactions on Computational Biology and Bioinformatics (2021).
S. Azizi, D. Hier, B. Allen, T. Obafemi-Ajayi, G. Olbricht, M. Thimgan, D. Wunsch, “A Kinetic Model for Blood Biomarker Levels after mild Traumatic Brain Injury”, Frontiers in neurology, 12, p.1121, 2021.
E. Redd, S. Senger, T. Obafemi-Ajayi, “Noise optimizes super-Turing computation in recurrent neural networks”, Physical Review Research 2021; 3(1).
D. Yeboah*, L. Steinmeister, D. Hier, B. Hadi, D. Wunsch, G. Olbricht, T. Obafemi-Ajayi, “An Explainable and Statistically Validated Ensemble Clustering Model applied to the Identification of Traumatic Brain Injury Subgroup”, IEEE Access 2020 (8), p.180690-180705.
M. Abbas, J. Matta, T. Le, H. Bensmail, T. Obafemi-Ajayi, V. Honavar, Y. EL-Manzalawy, “Biomarker discovery in inflammatory bowel diseases using network-based feature selection”, PloS one. 2019; 14(11).
J. Matta, T. Obafemi-Ajayi, J. Borwey, K. Sinha, D. Wunsch, G. Ercal, “Node-Based Resilience Measure Clustering with Applications to Noisy and Overlapping Communities in Complex Networks”, Applied Sciences, 8(8), p.1307, 2018.
J. Matta, J. Zhao*, G. Ercal, T. Obafemi-Ajayi, “Applications of Node-Based Resilience Graph Theoretic Framework to Clustering Autism Spectrum Disorders Phenotypes”, Applied Network Science, 3(1), p.38, 2018.
T. Obafemi-Ajayi, J. H. Miles, T. N. Takahashi, W. Qi, K. Aldridge, M. Zhang, S. Xin, Y. He, Y. Duan, “Facial Structure Analysis separates Autism Spectrum Disorders into Meaningful Clinical Subgroups”, Journal of Autism and Developmental Disorders, pp. 1-16, 2014.

Conference Proceedings

Orlenko A, Freda PJ, Ghosh A, Choi H, Matsumoto N, Bright TJ, Walker CT, Obafemi-Ajayi T, Moore JH. "Cluster Analysis reveals Socioeconomic Disparities among Elective Spine Surgery Patients". in Pacific Symposium on Biocomputing. Jan 2024.
Ekuma G*, Hier DB, Obafemi-Ajayi T. "An Explainable Deep Learning Model for Prediction of Severity of Alzheimer’s Disease". in IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology 2023.
Lamikanra K, Obafemi-Ajayi T. "Leveraging the Power of Artificial Intelligence and Blockchain in Recruitment using Beetle Platform". in IEEE Conference on Artificial Intelligence (CAI) 2023.
Perkins A, Peckham J, Obafemi-Ajayi T, Huang X. "Team Building without Boundaries". in Proc. 13th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) 2022.
Peckham J, Perkins A, Obafemi-Ajayi T, Huang X. NBT (No-Boundary Thinking): "Need to Attend to Ethical Implications of Data and AI". in 13th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics 2022.
Addison A*, Obafemi-Ajayi T. "Comparative Single-cell RNA-sequencing Cluster Analysis for Traumatic Brain Injury Marker Genes Detection". in International Conference on Bioinformatics and Computational Biology (BICOB) 2022.
J. Matta, D. Dobrino, S. Howard, D. Yeboah*, J. Kopel, Y. EL-Manzalawy, T. Obafemi-Ajayi, “A PheWAS Model of Autism Spectrum Disorder”, to appear in Proc. 43rd International Conference of the IEEE Engineering in Medicine and Biology Society 2021.
D. Yeboah*, H. Nguyen*, D. Heir, G. Olbricht, T. Obafemi-Ajayi, “A deep learning model to predict traumatic brain injury severity and outcome from MR images”, to appear in Proc. IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Oct 2021.
E. Redd, T. Obafemi-Ajayi, "Noise Quality and Super-Turing Computation in Recurrent Neural Networks", to appear in Proc. 30th International Conference on Artificial Neural Networks, ICANN2021.
S. Subhash, T. Obafemi-Ajayi, D. Goodman, D. Wunsch, G. Olbricht, “Predictive Modeling of Sports-Related Concussions using Clinical Assessment Metrics”, in Proc. IEEE Symposium Series on Computational Intelligence (SSCI) Dec. 2020.
T. Nguyen*, J. Viehman, D. Yeboah*, G. Olbricht, T. Obafemi-Ajayi, “Statistical Comparative Analysis and Evaluation of Validation Indices for Clustering Optimization”, in Proc. IEEE Symposium Series on Computational Intelligence (SSCI) Dec. 2020.
Z. Roy*, S. Subhash, L. Bui*, B. Hadi, D. Hier, D. Wunsch, G. Olbricht, T. Obafemi-Ajayi, “Exploratory Analysis of Concussion Recovery Trajectories using Multi-modal Assessments and Serum Biomarkers", in Proc. IEEE Engineering in Medicine and Biology Conference (EMBC) July, 2020.
M. Chaplin, J. Grubb, T. Clifford, J. Bruce, T. Obafemi-Ajayi, J. Matta, "Improved Classification of Medical Data Using Meta-Best Feature Selection", in Proc. IEEE Engineering in Medicine and Biology Conference (EMBC) July 2020.
T. Nguyen*, T. Obafemi-Ajayi, “Structured Iterative Hard Thresholding for Categorical and Mixed Data Types” in Proc. IEEE Symposium Series on Computational Intelligence (SSCI) Dec. 2019.
J. Dale*, J. Zhao*, T. Obafemi-Ajayi, “Multi-objective Optimization Approach to find Biclusters in Gene Expression Data”, in Proc. IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), July 2019.
J. Zhao*, T. Nguyen*, D. Adjeroh, P. Koob, J. Kopel, T. Obafemi-Ajayi, “Genotype Combinations Linked to Phenotype Subgroups in Autism Spectrum Disorders”, in Proc. IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), July 2019.
T. Clifford, J. Bruce, T. Obafemi-Ajayi, J. Matta, “Comparative Analysis of Feature Selection Methods to Identify Biomarkers in a Stroke-Related Dataset”, in Proc. IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), July 2019.
E. Redd, A. S. Younger, T. Obafemi-Ajayi, “Stochastic Resonance Enables BPP/log* Complexity and Universal Approximation in Analog Recurrent Neural Networks”, in Proc. IEEE International Joint Conference on Neural Networks (IJCNN), July 2019.
T. Nguyen*, T. Obafemi-Ajayi, “Recurrent Network and Multi-arm Bandit Methods for Multi-task Learning without Task Specification”, in Proc. IEEE International Joint Conference on Neural Networks (IJCNN), July 2019.
T. Nguyen*, A. S. Younger, E. Redd, T. Obafemi-Ajayi, “Meta-Learning Related Tasks with Recurrent Networks: Optimization and Generalization”, in Proc. IEEE International Joint Conference on Neural Networks (IJCNN), June 2018
J. Dale*, J. Matta, S. Howard, G. Ercal, W. Qiu, T. Obafemi-Ajayi, “Analysis of Grapevine Gene Expression Data using Node-Based Resilience Clustering”, in Proc. IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), May 2018.
T. Nguyen*, K. Nowell, K. E. Bodner, T. Obafemi-Ajayi, “Ensemble Validation Paradigm for Intelligent Data Analysis in Autism Spectrum Disorders”, in Proc. IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), May 2018.
J. Dale*, A. Nishimoto*, T. Obafemi-Ajayi, “Performance Evaluation and Enhancement of Biclustering Algorithms”, in Proc. International Conference on Pattern Recognition Applications and Methods (ICPRAM), Jan 2018.
T. Obafemi-Ajayi, G. Olbricht, C. Germeroth, L. Settles, T. N. Takahashi, J. H. Miles, D. Wunsch, “Genetic Variant Analysis of Boys with Autism: a Pilot Study on Linking Facial Phenotype to Genotype”, in Proc. IEEE International Conference on Bioinformatics and Biomedicine, Nov. 2017.
T. Obafemi-Ajayi, K. Al-Jabery, L. Salminen, D. Laidlaw, R. Cabeen, D. Wunsch and R. Paul, “Neuroimaging Biomarkers of Cognitive Decline in Healthy Older Adults via Unified Learning”, in Proc. IEEE Symposium Series on Computational Intelligence (SSCI) Nov. 2017.
T. Odun-Ayo and T. Obafemi-Ajayi, “Building the K-12 Engineering Pipeline: An assessment of where we stand”, in Proc. IEEE Frontiers in Education Conference FIE Oct. 2017.
J. Matta, T. Nguyen*, G. Ercal, T. Obafemi-Ajayi, “Applications of Novel Graph Theoretic Methods to Clustering Autism Spectrum Disorders Phenotypes”, International Conference on Bioinformatics and Computational Biology (BICOB) Mar 2017.
J. Matta, T. Obafemi-Ajayi, J. Borwey, D. Wunsch, G. Ercal, “Robust Graph-theoretic Clustering Approaches Using Node-Based Resilience Measures”, IEEE International Conference on Data Mining, Dec 2016.
K. Al-Jabery, T. Obafemi-Ajayi, G. R. Olbricht, T. N. Takahashi, S. Kanne, D. Wunsch, “Ensemble Statistical and Subspace Clustering Model for Analysis of Autism Spectrum Disorder Phenotypes”, IEEE Engineering in Medicine and Biology Conference August, 2016.

Abstract Proceedings

L. Steinmeister, D. Yeboah*, G. Olbricht, T. Obafemi-Ajayi, B. Hadi, D. Hier, D. Wunsch, “Handling missing data for unsupervised learning with an application on a FITBIR Traumatic Brain Injury (TBI) Dataset”, 2020 Military Health System Research Symposium (MHSRS)
E. Redd, A.S. Younger, T. Obafemi-Ajayi, “The Brain Likely Exploits ‘Defects’ for Super-Turing Computation—So Should All High-Performance Hardware”, Cognitive Computing Conference 2018.

Workshops/Symposiums Proceedings

T. Toma, T. Obafemi-Ajayi, J. Dawson, D. Adjeroh, "Random Subspace Projection for Predicting Biogeographical Ancestry", In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1719-1725).