Andrew Hornback

According to our database, Andrew Hornback authored at least 12 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

EMxDesign: A Genetic Algorithm for High Affinity Drug Design.

Neha Jain, Andrew Hornback, May Dongmei Wang

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Predicting Cardiovascular Disease Risk in Tobacco Users Using Machine Learning Algorithms.

Asma Khimani, Andrew Hornback, Neha Jain, Pavithra Avula, Anirudh Jaishankar, May D. Wang

Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024

Identifying Features for Keloid Scars Subtyping Using K-Modes Clustering.

Anirudh Jaishankar, Neha Jain, Andrew Hornback, Asma Khimani, Pavithra Avula, May D. Wang

Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024

Heterogeneous Treatment Effects of Spinal Fusion Surgery for Adolescent Idiopathic Scoliosis Patients.

J. Ben Tamo, Micky C. Nnamdi, Andrew Hornback, Matthew Chen, Wenqi Shi, Yuanda Zhu, Henry J. Iwinski, May D. Wang

Proceedings of the 15th ACM International Conference on Bioinformatics, 2024

Uncovering Key Features of Individuals Who Benefit from Polygenic Risk Scores in Prostate Cancer Prediction.

Andrew Hornback, Monica Isgut, Anirudh Jaishankar, Harinishree Sathu, Pavithra Avula, May D. Wang

Proceedings of the 15th ACM International Conference on Bioinformatics, 2024

2023

Conducting A/B Experiments with a Scalable Architecture.

Andrew Hornback, Sungeun An, Scott Bunin, Stephen Buckley, John Kos, Ashok K. Goel

CoRR, 2023

The Universal NFT Vector Database: A Scaleable Vector Database for NFT Similarity Matching.

Samrat Sahoo, Nitin Paul, Agam Shah, Andrew Hornback, Sudheer Chava

CoRR, 2023

A Scalable Architecture for Conducting A/B Experiments in Educational Settings.

Andrew Hornback, Stephen Buckley, John Kos, Scott Bunin, Sungeun An, David A. Joyner, Ashok K. Goel

Proceedings of the Tenth ACM Conference on Learning @ Scale, 2023

GeneDAE: A Sparse Denoising Autoencoder for Deriving Interpretable Gene Embeddings.

Monica Isgut, Neha Jain, Andrew Hornback, Karan Samel, May Dongmei Wang

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

Latent Topic Extraction as a Source of Labeling in Natural Language Processing.

Andrew Hornback, Yuanda Zhu, Monica Isgut, Wenqi Shi, Arjita Nema, Blake J. Anderson, May D. Wang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022

Incorporating Habitats in Conceptual Models and Agent-Based Simulations: Expanding the Virtual Ecological Research Assistant (VERA).

Scott Bunin, Willventchy Celestin, Andrew Hornback, Spencer Rugaber

Proceedings of the L@S'22: Ninth ACM Conference on Learning @ Scale, New York City, NY, USA, June 1, 2022

Development of a generalizable multi-site and multi-modality clinical data cloud infrastructure for pediatric patient care.

Andrew Hornback, Wenqi Shi, Felipe O. Giuste, Yuanda Zhu, Ashley M. Carpenter, Coleman Hilton, Vinieth N. Bijanki, Hiram Stahl, Gary S. Gottesman, Chad Purnell, Henry J. Iwinski, J. Michael Wattenbarger, May D. Wang

Proceedings of the BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7, 2022