Publications

bold = PI    ^† = corresponding author    underline = students whom I supervised

Under Review

[U3] J. Kang, S. Jung, K. Kim, C. Gardner, J.-S. Yeom, T.-H. Ahn^†, and J. Kim^†, “HPC-CARLA: Closed-Loop Evaluation of Autonomous Driving Agents as a Resilient, Schedulable HPC Workload”, Under Review (SC’26 WORKS Workshop), 2026.

[U2] V. D Nguyen, C. Gao, C. Gardner, Z. Wang, A. J Margenot, L. Huang^†, T.-H. Ahn^†, “First Metagenome-Assembled Genomes from the Historic Morrow Plots Reveal Management-Associated Dominance of Archaeal Ammonia Oxidizers”, Under Review (Scientific Data (IF=8.7) 1st round), 2026. [bioRxiv]

[U1] K.-S. Kim, C. Gardner, A. Cullen, J. A. Stelzer, K. Cho, A. Sharma, M. T. Nemera, T. Law, H. Naz, G. Zhao, H. W. Gabel, G. J. Patti, E. S. Musiek, T.-H. Ahn, J. J. Yi^†, “Persistent neuronal stress signaling underlies phenotypes in a mouse model of Angelman syndrome”, Under Review (Nature (IF=55) 2nd round), 2026.

Journal Articles and Peer-Reviewed Conference Proceedings

2026

[J37] P. Kang^†, T.-H. Ahn, “Interaction as Interference: A Quantum-Inspired Aggregation Approach for Classification”, Mathematics, 14(16), 3002, 2026. [DOI]

[J36] C. Gardner, A. Dhiren, B. Min^†, T.-H. Ahn^†, “Wavelet-Enhanced PaDiM for Industrial Anomaly Detection”, IEEE Access (IF=4.2), vol. 14, pp. 37702-37718, 2026. [DOI]

[J35] G. Jung, T.-H. Ahn, and B. Min^†, “Wildfire Smoke Detection with a Multi-Resolution Framework and Two-Stage Classification Pipeline”, Fire (IF=3.2), 9(2), 92, 2026. [DOI]

2025

[C16] C. Gardner, S. Jeong, O. Khatavkar, A. Moon, Q. Cao, T.-H. Ahn^†, “Evaluating Accuracy and Performance Tradeoffs in GPU Accelerated Single Cell RNA-seq Analysis”, in Proceedings of the SC Workshops ‘25 (SC’25), pp. 349–358, 2025. [DOI] (Best Paper Runner-Up Award)

[J34] S. Park, E. Ahn, T.-H. Ahn, S. N. Ahn, S. Park, E. Kwon, S. Ahn, Y. Yang, “Artificial Intelligence and Aging in Place: A Scoping Review of Current Applications and Future Directions”, The Gerontologist (IF=5.3), 65, 6, gnaf130, 2025. [DOI]

[C15] S. Maharjan, M. Xia, T.-H. Ahn, M. Song, “Intelligent Code Completion by a Unified Multi-task Learning with a Large Language Model”, in Proceedings of the 2025 IEEE/ACIS 23rd SERA, Las Vegas, NV, pp. 134–142, 2025. [DOI]

[J33] J. P. Sirasani, C. Gardner, G. Jung, H. Lee, T.-H. Ahn^†, “Bioinformatics approaches of blood and tissue microbiome analyses: challenges and perspectives”, Briefings in Bioinformatics (IF=7.7), 26, 2, bbaf176, 2025. [DOI]

2024

[J32] C. Gardner, J. Chen, C. Hadfield, Z. Lu, D. Debruin, Y. Zhan, M. Donlin, T.-H. Ahn^†, Z. Lin^†, “Chromosome-level subgenome-aware de novo assembly of Saccharomyces bayanus provides insight into genome divergence after hybridization”, Genome Research (IF=6.2), 34, 11, 2133–2146, 2024. [DOI]

[J31] T. Si, Y. Wang, L. Zhang, E. Richmond, T.-H. Ahn, H. Gong, “Multivariate Time Series Change-Point Detection with a Novel Pearson-like Scaled Bregman Divergence”, Stats (IF=1.3), 7, 2, 462-480, 2024. [DOI]

2023

[J30] K. S. Cheng, P.-C. Huang, T.-H. Ahn, M. Song, “Tool Support for Improving Software Quality in Machine Learning Programs”, Information (IF=3.38), 14, 1, 53, 2023. [DOI]

2022

[C14] P. Basia, T.-H. Ahn, M. Song, “An IDE Support for Validating Machine Learning Applications in Bioengineering Text Corpora”, in IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022. [DOI]

[C13] K. S. Cheng, T.-H. Ahn, and M. Song, “Debugging Support for Machine Learning Applications in Bioengineering Text Corpora”, in IEEE 46th Annual COMPSAC, 2022. [DOI]

[J29] Y. Mreyoud, M. Song, J. Lim, and T.-H. Ahn^†, “MegaD: Deep Learning for Rapid and Accurate Disease Status Prediction of Metagenomic Samples”, Life (IF=3.96), 12, 5, 669, 2022. [DOI]

2021

[J28] Z. Lu, K. Berry, Z. Hu, Y. Zhan, T.-H. Ahn^†, and Z. Lin^†, “TSSr: an R Package for Comprehensive Analyses of TSS Sequencing Data”, NAR Genomics and Bioinformatics, 3, 4, 2021. [DOI]

[J27] Y. Yang, C. Gardner, P. Gupta, Y. Peng, C. Piasecki, R. J. Millwood, T.-H. Ahn, and C. N. Stewart Jr., “Novel Candidate Genes Differentially Expressed in Glyphosate-Treated Horseweed (Conyza canadensis)”, Genes (IF=3.96), 12, 10, 2021. [DOI]

[J26] S. Lewis, A. Nash, Q. Li, and T.-H. Ahn^†, “Comparison of 16S and Whole Genome Dog Microbiomes using Machine Learning”, BioData Mining (IF=4.078), 14, 41, 2021. [DOI]

[J25] A. Rajeh, K. Wolf, C. Schiebout, N. Sait, T. Kosfeld, R. J. DiPaolo^† and T.-H. Ahn^†, “iCAT: Diagnostic Assessment Tool of Immunological History using High-throughput T-cell Receptor Sequencing”, F1000Research (IF=2.297), 2021. [DOI]

[J24] E. Dhungel, Y. Mreyoud, H.-J. Gwak, A. Rajeh, M. Rho, and T.-H. Ahn^†, “MegaR: an Interactive R package for Rapid Sample Classification and Phenotype Prediction using Metagenome Profiles and Machine Learning”, BMC Bioinformatics (IF=3.169), 22, 25, 2021. [DOI]

2020

[J23] M. Hassert, K. J. Wolf, A. Rajeh, C. Schiebout, S. G. Hoft, T.-H. Ahn, R. J. DiPaolo, J. D. Brien, A. K. Pinto, “Diagnostic Differentiation of Zika and Dengue Virus Exposure by Analyzing T Cell Receptor Sequences from Peripheral Blood of Infected HLA-A2 Transgenic Mice”, PLOS Neglected Tropical Diseases (IF=4.781), 2020. [DOI]

[C12] Y. Mreyoud and T.-H. Ahn^†, “Deep Neural Network Modeling for Phenotypic Prediction of Metagenomic Samples”, in Proceedings of the 11th ACM-BCB ‘20, 2020. [DOI]

[C11] T. Kosfeld, J. McMillan, R. J. DiPaolo, J. Hou^†, and T.-H. Ahn^†, “Performance Evaluation of Viral Infection Diagnosis using T-Cell Receptor Sequence and Artificial Intelligence”, in Proceedings of the 11th ACM-BCB ‘20 (Acceptance Rate=30%), 2020. [DOI]

[J22] K. Bockerstett, S. Lewis, C. Noto, E. Ford, J. Saenz, N. Jackson, T.-H. Ahn, J. Mills, R. DiPaolo, “Single Cell Transcriptional Analyses Identify Lineage-Specific Epithelial Responses to Inflammation and Metaplastic Development in the Gastric Corpus”, Gastroenterology (IF=22.682), 159, 6, 2020. [DOI]

[J21] K. Bockerstett, S. Lewis, K. Wolf, C. Noto, N. Jackson, E. Ford, T.-H. Ahn, R. DiPaolo, “Single-cell Transcriptional Analyses of Spasmolytic Polypeptide-expressing Metaplasia Arising from Acute Drug Injury and Chronic Inflammation in the Stomach”, Gut (IF=17.943), 69(6), 1027-1038, 2020. [DOI]

[J20] G. Mason-Buck, A. Graf, E. Elhaik, …, E. Dhungel, T.-H. Ahn, …, P. Labaj, “DNA Based Methods in Intelligence — Moving Towards Metagenomics”, Preprints, 2020. [DOI]

[J19] Z. Siddiqui, J. Maldonado, J. Grojean, F. Ye, D. Zhang, J. Longtine, T.-H. Ahn^†, and H. Guo^†, “Rchimerism: An R-Package for Automated Chimerism Data Analysis”, The Journal of Molecular Diagnostics (IF=5.568), 22(1), 21-30, 2020. [DOI]

2019

[J18] A. Paul, D. Lawrence, M. Song, S.-H. Lim, C. Pan, and T.-H. Ahn^†, “Using Apache Spark on Genome Assembly for Scalable Overlap-graph Reduction”, Human Genomics (IF=5.88), Vol 13, Supplement 1, 2019. [DOI]

[J17] V. K. Epuri, S. Sakala, T.-H. Ahn, and M. Song, “Tool Support for Managing Repetitive Program Changes in Evolving Software”, IET Software (IF=1.070), 2019. [DOI]

[J16] Z. Harris, E. Dhungel, M. Mosior, and T.-H. Ahn^†, “Massive Metagenomic Data Analysis using Abundance-Based Machine Learning”, Biology Direct (IF=4.78), 14, 12, 2019. [DOI]

[J15] J. McMillan, Z. Lu, J. Rodriguez, T.-H. Ahn^†, and Z. Lin^†, “YeasTSS: An Integrative Web Database of Yeast Transcription Start Sites”, Database (Oxford) (IF=4.462), Volume 2019, baz048, 2019. [DOI]

[C10/B1] W. Feng, Z. Yu, M. Kang, H. Gong^†, and T.-H. Ahn^†, “Practical Evaluation of Different Omics Data Integration Methods”, in Precision Health and Medicine. W3PHAI 2019. Studies in Computational Intelligence, vol 843, Springer, 2019. [DOI]

2018

[C9] A. Paul, D. Lawrence, M. Song, S.-H. Lim, C. Pan, and T.-H. Ahn^†, “SORA: Scalable Overlap-graph Reduction Algorithms for Genome Assembly using Apache Spark in the Cloud”, in Proceedings of the 2018 IEEE BIBM, 2018. [DOI]

[J14] K. Wolf, T. Hether, P. Gilchuk, A. Kumar, A. Rajeh, C. Schiebout, J. Maybruck, R. M. Buller, T.-H. Ahn, S. Joyce, R. DiPaolo, “Identifying and Tracking Low Frequency Virus-Specific TCR Clonotypes Using High-Throughput Sequencing”, Cell Reports (IF=9.423), 25, 9, P2369-2378.E4, 2018. [DOI]

[C8/J13] M. McCoy, A. Paul, M. Victor, M. Richner, H. Gabel, H. Gong, A. Yoo^†, and T.-H. Ahn^†, “LONGO: An R Package for Interactive Gene Length Dependent Analysis for Neuronal Identity”, Bioinformatics (IF=6.937), vol. 34, issue 13, pp. i422-428, ISMB-2018, 2018. [DOI]

2017

[C7] A. Paul, D. Lawrence, and T.-H. Ahn^†, “Overlap Graph Reduction for Genome Assembly using Apache Spark”, in Proceedings of ACM-BCB 2017, poster, p. 613-613, 2017. [DOI]

2015

[J12] T.-H. Ahn, X. Han, and A. Sandu, “Implicit Simulation Methods for Stochastic Chemical Kinetics”, Journal of Applied Analysis and Computation (IF=1.116), 5(3), pp. 420-452, 2015. [DOI]

[J11] M. Land, L. Hauser, S. Jun, I. Nookaew, M. Leuze, T.-H. Ahn, T. Karpinets, O. Lund, G. Kora, T. Wassenaar, S. Poudel, and D. Ussery, “Insights from 20 Years of Bacterial Genome Sequencing”, Functional & Integrative Genomics (IF=3.889), 15(2), pp. 141-161, 2015. [DOI]

[J10] T.-H. Ahn, J. Chai, and C. Pan, “Sigma: Strain-level Inference of Genomes from Metagenomic Analysis for Biosurveillance”, Bioinformatics (IF=6.937), vol. 31, issue 2, pp. 170-177, 2015. [DOI]

[J9] T.-H. Ahn, A. Sandu, L.T. Watson, C.A. Shaffer, Y. Cao, and W.T. Baumann, “A Framework to Analyze the Performance of Load Balancing Schemes for Ensembles of Stochastic Simulations”, International Journal of Parallel Programming (IF=1.258), Vol. 43, Issue 4, pp. 597-630, 2015. [DOI]

2014

[J8] J. Chai, G. Kora, T.-H. Ahn, D. Hyatt, and C. Pan, “Functional Phylogenomics Analysis of Bacteria and Archaea using Consistent Genome Annotation with UniFam”, BMC Evolutionary Biology (IF=3.559), 14(1):207, 2014. [DOI]

[J7] B. Haider, T.-H. Ahn, B. Bushnell, J. Chai, A. Copeland, and C. Pan, “Omega: an Overlap-graph de novo Assembler for Metagenomics”, Bioinformatics (IF=6.937), vol. 30, issue 19, pp. 2717-2722, 2014. [DOI]

[J6] Z. Li, Y. Wang, Q. Yao, N.B. Justice, T.-H. Ahn, D. Xu, R.L. Hettich, J.F. Banfield, and C. Pan, “Diverse and Divergent Post-translational Modification of Proteins of Closely Related Bacteria in Two Growth Stages of a Natural Microbial Community”, Nature Communications (IF=13.811), 5, article 4405, 2014. [DOI]

2013

[J5] D. Dechev and T.-H. Ahn, “Using SST/macro for Effective Analysis of MPI-based Applications: Evaluating Large-Scale Genomic Sequence Search”, IEEE Access (IF=3.745), vol. 1, pp. 428-435, 2013. [DOI]

[J4] Y. Wang, T.-H. Ahn, Z. Li, and C. Pan, “Sipros/ProRata: a Versatile Informatics System for Quantitative Community Proteomics”, Bioinformatics (IF=6.937), vol. 29, no. 16, pp. 2064-2065, 2013. [DOI]

2011

[C6/J3] T.-H. Ahn and A. Sandu, “Implicit Second Order Weak Taylor Tau-Leaping Methods for the Stochastic Simulations of Chemical Kinetics”, Procedia Computer Science, Volume 4, pp. 2297-2306, ICCS (Acceptance Rate=24%), 2011. [DOI]

[J2] D.A. Ball, T.-H. Ahn, P. Wang, K.C. Chen, Y. Cao, J.J. Tyson, J. Peccoud, and W.T. Baumann, “Stochastic Exit from Mitosis in Budding Yeast: Model Predictions and Experimental Observations”, Cell Cycle (IF=3.304), vol. 10, issue 6, pp. 1-11, 2011. [DOI]

[C5] T.-H. Ahn, D. Dechev, H. Lin, H. Adalsteinsson, and C. Janssen, “Evaluating Performance Optimizations of Large-Scale Genomic Sequence Search Applications Using SST/macro”, in Proceedings of SIMULTECH 2011 (Acceptance Rate=17.7%), 2011. [DOI]

[C4] T.-H. Ahn and A. Sandu, “Fully Implicit Tau-Leaping Methods for the Stochastic Simulation of Chemical Kinetics”, in Proceedings of HPC 2011, SpringSim ‘11, Boston, MA, 2011. [DOI]

2010

[C3] T.-H. Ahn and A. Sandu, “Parallel Stochastic Simulations of Budding Yeast Cell Cycle: Load Balancing Strategies and Theoretical Analysis”, in Proceedings of ACM-BCB ‘10, pp. 237-246 (Acceptance Rate=25%), 2010. [DOI]

2009

[J1] T.-H. Ahn, L.T. Watson, Y. Cao, C.A. Shaffer, and W.T. Baumann, “Cell Cycle Modeling for Budding Yeast with Stochastic Simulation Algorithms”, Computer Modeling in Engineering and Sciences (IF=0.75), vol. 51, no. 1, pp. 27-52, 2009. [DOI]

[C2] T.-H. Ahn, P. Wang, L.T. Watson, Y. Cao, C.A. Shaffer, and W.T. Baumann, “Stochastic Cell Cycle Modeling for Budding Yeast”, in Proceedings of SpringSim ‘09, San Diego, CA, pp. 113:1-113:6, 2009. [DOI]

2008

[C1] T.-H. Ahn, Y. Cao, and L.T. Watson, “Stochastic Simulation Algorithms for Chemical Reactions”, in Proceedings of BIOCOMP ‘08, Las Vegas, NV, pp. 431-436, 2008.