Jingzhi Pu

Indiana University – Purdue University Indianapolis

Biochemistry, Genetics and Molecular BiologyPhysics and AstronomyMaterials Science

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 17 papers. Top paper: “Machine-Learning-Assisted Free Energy Simulation of Solution-Phase and Enzyme Reactions”.

Machine-Learning-Assisted Free Energy Simulation of Solution-Phase and Enzyme Reactions

Journal of Chemical Theory and Computation(2021)10.1021/acs.jctc.1c00565

N/A

0.710DataRank · unranked

113 citations

Junjie Yang, Richard Van, Evgeny Epifanovsky, Junming Ho, Jing Huang +5 more

Accelerating Ab Initio Quantum Mechanical and Molecular Mechanical (QM/MM) Molecular Dynamics Simulations with Multiple Time Step Integration and a Recalibrated Semiempirical QM/MM Hamiltonian

The Journal of Physical Chemistry B(2022)10.1021/acs.jpcb.2c02262

N/A

0.464DataRank · unranked

21 citations

Richard Van, Evgeny Epifanovsky, Jian Liu, Jingzhi Pu, Kwangho Nam +2 more

Interligand communication in a metal mediated LL′CT system – a case study

RSC Advances(2021)10.1039/d1ra04716g

N/A

0DataRank · unranked

1 citations

Kyle J. Colston, Stephen C. Ratvasky, Jingzhi Pu, Partha Basu, Sara A. Dille

Machine Learning Assisted Free Energy Simulation of Solution–Phase and Enzyme Reactions

ChemRxiv(2021)10.26434/chemrxiv.14745510.v1

N/A

0DataRank · unranked

12 citations

Junjie Yang, Richard Van, Evgeny Epifanovsky, Junming Ho, Jing Huang +5 more

Machine Learning Assisted Free Energy Simulation of Solution–Phase and Enzyme Reactions

ChemRxiv(2021)10.26434/chemrxiv.14745510

N/A

0DataRank · unranked

0 citations

Junjie Yang, Richard Van, Evgeny Epifanovsky, Junming Ho, Jing Huang +5 more

Facilitating ab initio QM/MM free energy simulations by Gaussian process regression with derivative observations

Physical Chemistry Chemical Physics(2022)10.1039/d2cp02820d

N/A

0DataRank · unranked

16 citations

Bryant Kim, Xiaoliang Pan, Yihan Shao, Jingzhi Pu, Ryan Snyder

Accelerating ab initio QM/MM Molecular Dynamics Simulations with Multiple Time Step Integration and a Recalibrated Semi-empirical QM/MM Hamiltonian

ChemRxiv(2022)10.26434/chemrxiv-2022-0zg7j

N/A

0DataRank · unranked

2 citations

Richard Van, Evgeny Epifanovsky, Jian Liu, Jingzhi Pu, Kwangho Nam +2 more

Machine learning based implicit solvent model for aqueous-solution alanine dipeptide molecular dynamics simulations

RSC Advances(2023)10.1039/d2ra08180f

N/A

0DataRank · unranked

31 citations

Richard Van, Xiaoliang Pan, Ji Hwan Park, Yuezhi Mao, Jingzhi Pu +3 more

Bridging semiempirical and ab initio QM/MM potentials by Gaussian process regression and its sparse variants for free energy simulation

The Journal of Chemical Physics(2023)10.1063/5.0156327

N/A

0DataRank · unranked

21 citations

Bryant Kim, Xiaoliang Pan, Yihan Shao, Jingzhi Pu, Ryan Snyder

Free Energy Profile Decomposition Analysis for QM/MM Simulations of Enzymatic Reactions

Journal of Chemical Theory and Computation(2023)10.1021/acs.jctc.3c00973

N/A

0DataRank · unranked

10 citations

Richard Van, Jingzhi Pu, Kwangho Nam, Yuezhi Mao, Yihan Shao +1 more

Training machine learning potentials for reactive systems: A Colab tutorial on basic models

Journal of Computational Chemistry(2023)10.1002/jcc.27269

N/A

0DataRank · unranked

9 citations

Ryan Snyder, Jianing Wang, Chance Lander, Carly Wickizer, Richard Van +7 more

The Training of Machine Learning Potentials for Reactive Systems: A Colab Tutorial on Basic Models

ChemRxiv(2023)10.26434/chemrxiv-2023-545gw

N/A

0DataRank · unranked

2 citations

Ryan Snyder, Jianing Wang, Chance Lander, Carly Wickizer, Richard Van +7 more

Free Energy Profile Decomposition Analysis for QM/MM Simulations of Enzymatic Reactions

ChemRxiv(2023)10.26434/chemrxiv-2023-mrm25

N/A

0DataRank · unranked

0 citations

Richard Van, Jingzhi Pu, Kwangho Nam, Yuezhi Mao, Yihan Shao +1 more

CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed

The Journal of Physical Chemistry B(2024)10.1021/acs.jpcb.4c04100

N/A

0DataRank · unranked

116 citations

Steven L. Austin, Arnaud Blondel, Eric D. Boittier, Stefan Boresch, Matthias Buck +68 more

Enhancing Gaussian process regression-accelerated QM/MM free energy simulations using atomic environment descriptors

ChemRxiv(2025)10.26434/chemrxiv-2025-hg8n7

N/A

0DataRank · unranked

0 citations

Dongru Li, T.‐L. HO, Bryant Kim, Hysum Qazi, Xiaoliang Pan +3 more

Enhancing Gaussian process regression-accelerated QM/MM free energy simulations using atomic environment descriptors

ChemRxiv(2025)10.26434/chemrxiv-2025-hg8n7-v2

N/A

0DataRank · unranked

0 citations

Dongru Li, T.‐L. HO, Bryant Kim, Hysum Qazi, Xiaoliang Pan +3 more

Reaction Path-Force Matching in Collective Variables: Determining Ab Initio QM/MM Free Energy Profiles by Fitting Mean Force

Journal of Chemical Theory and Computation(2021)10.1021/acs.jctc.1c00245

N/A

0DataRank · unranked

23 citations

Ryan Snyder, Mulpuri Nagaraju, Yan Zhou, Pedro Ojeda-May, Seth Keeton +4 more