euhruska
computational pharmaceutical science | high-throughput atomistic simulation and explainable machine learning
Charles UniversityAtlanta
Pinned Repositories
ash
ASH is a Python-based computational chemistry and QM/MM environment, primarily for molecular calculations in the gas phase, explicit solution, crystal or protein environment.
atomistic-software
Tracking citations of atomistic simulation engines
AutoSolvate
Automated workflow for generating quantum chemistry calculation of explicitly solvated molecules
CHEM531
CV-latex
euhruska.github.io
ExTASY
user-friendly and scalably execute adaptive sampling molecular dynamics on HPCs
MLbook
Case study for the "Quantum Chemistry in the Age of Machine Learning" book chapter
hruska-lab.github.io
Hruška Lab Website
AutoSolvate
Automated workflow for generating quantum chemistry calculation of explicitly solvated molecules
euhruska's Repositories
euhruska/ash
ASH is a Python-based computational chemistry and QM/MM environment, primarily for molecular calculations in the gas phase, explicit solution, crystal or protein environment.
euhruska/atomistic-software
Tracking citations of atomistic simulation engines
euhruska/AutoSolvate
Automated workflow for generating quantum chemistry calculation of explicitly solvated molecules
euhruska/CHEM531
euhruska/CV-latex
euhruska/euhruska.github.io
euhruska/ExTASY
user-friendly and scalably execute adaptive sampling molecular dynamics on HPCs
euhruska/Hruskathesis
PhD thesis
euhruska/MLbook
Case study for the "Quantum Chemistry in the Age of Machine Learning" book chapter
euhruska/PCA
euhruska/SI_data_AutoSolvate
SI data for paper "AutoSolvate: A toolkit for automating quantum chemistry design and discovery of solvated molecules"
euhruska/SI_data_redox_paper
SI data for paper "Bridging the Experiment-Calculation Divide: Machine Learning Corrections to Redox Potential Calculations in Implicit and Explicit Solvent Models"