Ph.D. Student
Major – Quantitative Biosciences (QBioS)
Expected graduation – May 2029
B.S., Georgia Institute of Technology, 2020
Center for the Study of Systems Biology
Engineered BioSystems Building
950 Atlantic Drive
Atlanta GA, 30332, Mail Code: 2000
Research Interests
- Concept representation, compositionality, and generalization in neural systems
- Computation and temporal signal encoding in biological brains
- Evolved plastic artificial neural networks
- Virtual cell simulation
- Modeling of cellular signaling systems & pathways
Publications
Edelman, B, Kim H, Skolnick J. Submitted. Trajectories matter: Discovery and validation of ordered EHR sequences that inform clinical risk predictions.
Zhou, H, Edelman B, Skolnick J. Submitted. MENDELSEEK: An algorithm that predicts Mendelian Genes and elucidates what makes them special.
Edelman, B, Skolnick J. 2025. Valsci: An Open-Source, Self-Hostable Literature Review Utility for Automated Large-Batch Scientific Claim Verification Using Large Language Models. BMC Bioinformatics: 26: 140. https://doi.org/10.1186/s12859-025-06159-4. PDF
Zhou, H, Edelman B, Skolnick J. 2025. A mode-of-action protein based approach that characterizes the relationships among most major diseases. Scientific Reports: 15, 9668. https://doi.org/10.1038/s41598-025-93377-8. PDF