Kevin McLoughlin

Lawrence Livermore National Laboratory — United States

Computer Science · Physical Sciences

21h-index1.6kcitations84works0.82yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Computational Drug Discovery Methods(18), Machine Learning in Materials Science(11), Viral gastroenteritis research and epidemiology(10), Animal Virus Infections Studies(10), Gene expression and cancer classification(9)

Publications84 total

ChemBERTa-3: an open source training framework for chemical foundation models
Digital Discovery·2026· 1 citedOpen Access
ChemBERTa-3: An Open Source Training Framework for Chemical Foundation Models
Zenodo (CERN European Organization for Nuclear Research)·2025Open Access
ChemBERTa-3: An Open Source Training Framework for Chemical Foundation Models
Zenodo (CERN European Organization for Nuclear Research)·2025Open Access
ChemBERTa-3: An Open Source Training Framework for Chemical Foundation Models
Zenodo (CERN European Organization for Nuclear Research)·2025Open Access
ChemBERTa-3: An Open Source Training Framework for Chemical Foundation Models
2025· 2 citedOpen Access
ChemBERTa-3: An Open Source Training Framework for Chemical Foundation Models
2025· 2 citedOpen Access
Evaluating point-prediction uncertainties in neural networks for protein-ligand binding prediction
Artificial Intelligence Chemistry·2023· 4 citedOpen Access
Generative Molecular Design and Experimental Validation of Selective Histamine H1 Inhibitors
2023· 5 citedOpen Access
Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery
arXiv (Cornell University)·2022Open Access
Model Choice Metrics to Optimize Profile-QSAR Performance
2022Open Access
High-throughput virtual screening of small molecule inhibitors for SARS-CoV-2 protein targets with deep fusion models
2021· 2 citedOpen Access
Discovery of Small-Molecule Inhibitors of SARS-CoV-2 Proteins Using a Computational and Experimental Pipeline
Frontiers in Molecular Biosciences·2021· 27 citedOpen Access
Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models
The International Journal of High Performance Computing Applications·2021· 37 citedOpen Access
High-Throughput Virtual Screening of Small Molecule Inhibitors for\n SARS-CoV-2 Protein Targets with Deep Fusion Models
arXiv (Cornell University)·2021· 1 citedOpen Access
Gut microbiome associations with outcome following co-infection with porcine reproductive and respiratory syndrome virus (PRRSV) and porcine circovirus type 2 (PCV2) in pigs immunized with a PRRS modified live virus vaccine
Veterinary Microbiology·2021· 9 citedOpen Access
Machine Learning Models to Predict Inhibition of the Bile Salt Export Pump
Journal of Chemical Information and Modeling·2021Open Access
An Action Research Enquiry into the potential of SolidWorks in the teaching of rotation in Junior Certificate Technical Graphics
International Journal for Transformative Research·2020· 1 citedOpen Access
AMPL: A Data-Driven Modeling Pipeline for Drug Discovery
Journal of Chemical Information and Modeling·2020· 5 citedOpen Access
Machine Learning Models to Predict Inhibition of the Bile Salt Export\n Pump
arXiv (Cornell University)·2020Open Access
Split Optimization for Protein/Ligand Binding Models
arXiv (Cornell University)·2020Open Access
page 1 of 5Next →

Frequent Co-authors

Crystal Jaing(19), Shea N. Gardner(16), James B. Thissen(12), Jonathan Allen(12), Tom Slezak(5), Derek Jones(5), Stewart He(5), Raymond R. R. Rowland(4), Nicholas A. Be(4), Felice C. Lightstone(4), Brian J. Bennion(4), Bharath Ramsundar(4), Megan C. Niederwerder(3), Monica K. Borucki(3), Feliza Bourguet(3), Adam Zemła(3), Aryan Amit Barsainyan(3), Rida Irfan(3), Connor Joseph Amorin(3), Arun Thiagarajan(3)