Research

Our research focuses on developing innovative computational tools to analyze big data in biological, health, and biomedical domains using Artificial Intelligence (AI) and High-Performance Computing (HPC).

Bioinformatics & Biomedical Informatics

We develop AI-driven methods for multi-modal and multi-omics data fusion, metagenomics, single-cell RNA-seq, immune cell analysis, and computer vision for biomedical and industrial applications.

Key Topics: Multi-modal/multi-omics data integration, metagenome-assembled genomes, microbiome-based ML diagnostics, T-cell receptor sequencing, scRNA-seq, spatial transcriptomics, next-generation sequencing

Software: MegaR | MegaD | iCAT | LONGO | Sigma | Omega

Selected Funding:

• NSF CRII — Accelerating Human Microbiome Analysis
• NSF S-STEM BITWISE — Bioinformatics Training
• NIH — TCR Sequence Analysis of Human Cohorts from Zika Infection
• FBI — Identifying and Tracking Virus-Specific TCR Clonotypes
• Purina - Deep Analysis of Dietary Effects on Dog Gut Microbiomes

Selected Publications:

• J. P. Sirasani, et al., “Bioinformatics approaches of blood and tissue microbiome analyses”, Briefings in Bioinformatics, 2025. [DOI]
• C. Gardner, et al., “Chromosome-level subgenome-aware de novo assembly of S. bayanus”, Genome Research, 2024. [DOI]
• E. Dhungel, et al., “MegaR”, BMC Bioinformatics, 2021. [DOI]
• A. Rajeh, et al., “iCAT”, F1000Research, 2021. [DOI]
• M. McCoy, A. Paul, et al., “LONGO”, Bioinformatics (ISMB-2018), 2018. [DOI]
• K. Wolf, et al., “Identifying and Tracking Low Frequency Virus-Specific TCR Clonotypes”, Cell Reports, 2018. [DOI]
• T.-H. Ahn, J. Chai, C. Pan, “Sigma”, Bioinformatics, 2015. [DOI]
• B. Haider, T.-H. Ahn, et al., “Omega”, Bioinformatics, 2014. [DOI]

High-Performance Computing & AI Infrastructure

We build GPU computing infrastructure, develop scalable bioinformatics tools using Apache Spark and cloud platforms, and explore cybersecurity applications including PUF-blockchain technology.

Key Topics: GPU cluster management, anomaly detection, cloud computing, parallel/distributed algorithms, Apache Spark for genomics, PUF-blockchain security

Software: SORA | ForStoch

Selected Funding:

• NSF EAGER - Unveiling Security Risks to Scientific Integrity in AI-Driven Biological Discovery
• NSF CC* ModernCARE — GPU cluster for AI research at SLU
• Korean Ministry of MSS — PUF-Blockchain security

Selected Publications:

• C. Gardner, et al., “Wavelet-Enhanced PaDiM for Industrial Anomaly Detection”, IEEE Access, 2026. [DOI]
• G. Jung, T.-H. Ahn, B. Min, “Wildfire Smoke Detection with a Multi-Resolution Framework”, Fire, 2026. [DOI]
• C. Gardner, et al., “Evaluating Accuracy and Performance Tradeoffs in GPU Accelerated Single Cell RNA-seq Analysis”, SC Workshops ‘25, 2025. [DOI] (Best Paper Runner-Up)
• A. Paul, et al., “Using Apache Spark on Genome Assembly for Scalable Overlap-graph Reduction”, Human Genomics, 2019. [DOI]
• A. Paul, et al., “SORA”, IEEE BIBM, 2018. [DOI]
• T.-H. Ahn, et al., “Implicit Simulation Methods for Stochastic Chemical Kinetics”, JAAC, 2015. [DOI]

For a complete list, see Publications or Google Scholar.