Sungsik Kong
Biochemistry, Genetics and Molecular Biology · The Ohio State University
Publications
40
Citations
421
Est. group size
~1
Recurring co-author estimate
Active years
19
Publishing since 2008
Sungsik Kong develops statistical and computational methods for reconstructing phylogenetic networks and trees, which are diagrams showing how species or populations are evolutionarily related, especially when their histories involve interbreeding or hybridization between lineages. This work includes building scalable software tools and likelihood-based statistical tests, alongside some earlier applied projects in amphibian disease genetics and insect species identification. The research combines mathematical biology, genomics, and software development to help other biologists infer complex evolutionary histories from DNA sequence data.
Publication output has grown from near zero in 2017 to a steady average of roughly 4-5 papers per year over the last five years, with some year-to-year variation.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Evaluating Phylogenetic Comparative Methods under Reticulate Evolutionary Scenarios
arXiv (Cornell University) · 2026
- Evaluating Phylogenetic Comparative Methods under Reticulate Evolutionary Scenarios
arXiv (Cornell University) · 2026
- Peer Review Report For: RAWR v1.0: a software suite for phylogenetic support estimation and other sequence-aware RAndom Walk Resampling tasks [version 1; peer review: 2 approved with reservations]
2026
- SNaQ.jl: Improved scalability for level-1 phylogenetic network inference
Bioinformatics · 2026
- Phylogenetic networks empower biodiversity research
Proceedings of the National Academy of Sciences · 2025
- The promise of composite likelihood for species-level phylogenomic inference
Evolutionary Journal of the Linnean Society · 2025
- A method for massively scalable inference of phylogenetic networks
bioRxiv (Cold Spring Harbor Laboratory) · 2025
- SNaQ.jl: Improved Scalability for Phylogenetic Network Inference
bioRxiv (Cold Spring Harbor Laboratory) · 2025
- Data from: SNaQ.jl: Improved scalability for phylogenetic network inference
Open MIND · 2025
- Inference of Phylogenetic Networks From Sequence Data Using Composite Likelihood
Systematic Biology · 2024
- A New Frontier of AI: On-Device AI Training and Personalization
2024
- A Likelihood Ratio Test for Hybridization Under the Multispecies Coalescent
Bulletin of the Society of Systematic Biologists · 2024
- Identification of major histocompatibility complex genotypes associated with resistance to an amphibian emerging infectious disease
Infection Genetics and Evolution · 2023
- Median-Joining Networks and Bayesian Phylogenies Often Do Not Tell the Same Story
Bulletin of the Society of Systematic Biologists · 2023
- A Likelihood Ratio Test for Hybridization Under the Multispecies Coalescent
bioRxiv (Cold Spring Harbor Laboratory) · 2023
- bioRxiv (Cold Spring Harbor Laboratory)×6
- arXiv (Cornell University)×3
- Systematic Biology×2
- Proceedings of the National Academy of Sciences×2
- Bulletin of the Society of Systematic Biologists×2
- Laura Kubatko
Biochemistry, Genetics and Molecular Biology · The Ohio State University
- Megan L. Smith
Biochemistry, Genetics and Molecular Biology · Indiana University
- Drew J. Duckett
Biochemistry, Genetics and Molecular Biology · The Ohio State University
- Jong Yoon Jeon
Biochemistry, Genetics and Molecular Biology · Purdue University West Lafayette
- Danielle J. Parsons
Biochemistry, Genetics and Molecular Biology · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
Claim or correct this profile