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Mojtaba Haghighatlari
Observed name:
Haghighatlari, Mojtaba
Institution:
Pfizer (United States)
Observed institutions:
State University of New York,
Sharif University of Technology,
Pfizer (United States),
University at Buffalo, State University of New York,
University of California, Berkeley
ORCID:
0000-0002-3779-2246
Observed ORCID:
0000-0002-3779-2246
OpenAlex ID:
A5000952998
NewtonNet: a Newtonian message passing network for deep learning of interatomic potentials and forces
2022
·
Mojtaba Haghighatlari
, Jie Li
, et al.
·
Digital Discovery
·
137
Advances of machine learning in molecular modeling and simulation
2019
·
Mojtaba Haghighatlari
, Johannes Hachmann
·
Current Opinion in Chemical Engineering
·
131
PDF
Learning to Make Chemical Predictions: The Interplay of Feature Representation, Data, and Machine Learning Methods
2020
·
Mojtaba Haghighatlari
, Jie Li
, et al.
·
Chem
·
116
PDF
ChemML : A machine learning and informatics program package for the analysis, mining, and modeling of chemical and materials data
2020
·
Mojtaba Haghighatlari
, Gaurav Vishwakarma
, et al.
·
Wiley Interdisciplinary Reviews Computational Molecular Science
·
94
Extended experimental inferential structure determination method in determining the structural ensembles of disordered protein states
2020
·
James Lincoff
, Mojtaba Haghighatlari
, et al.
·
Communications Chemistry
·
64
PDF
IDPConformerGenerator: A Flexible Software Suite for Sampling the Conformational Space of Disordered Protein States
2022
·
João M. C. Teixeira
, Zi Hao Liu
, et al.
·
The Journal of Physical Chemistry A
·
63
Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining
2019
·
Mohammad Atif Faiz Afzal
, Mojtaba Haghighatlari
, et al.
·
The Journal of Physical Chemistry C
·
63
A deep neural network model for packing density predictions and its application in the study of 1.5 million organic molecules
2019
·
Mohammad Atif Faiz Afzal
, Aditya Sonpal
, et al.
·
Chemical Science
·
46
Learning to evolve structural ensembles of unfolded and disordered proteins using experimental solution data
2023
·
Oufan Zhang
, Mojtaba Haghighatlari
, et al.
·
The Journal of Chemical Physics
·
40
PDF
Building and deploying a cyberinfrastructure for the data-driven design of chemical systems and the exploration of chemical space
2018
·
Johannes Hachmann
, Mohammad Atif Faiz Afzal
, et al.
·
Molecular Simulation
·
38
A benchmark dataset for Hydrogen Combustion
2022
·
Xingyi Guan
, Akshaya Das
, et al.
·
Scientific Data
·
23
PDF
Low-temperature gas–solid carbonation of magnesia and magnesium hydroxide promoted by non-immersive contact with water
2016
·
James Highfield
, Jason Chen
, et al.
·
RSC Advances
·
21
Open Chemistry, JupyterLab , REST , and quantum chemistry
2020
·
Marcus D. Hanwell
, Chris Harris
, et al.
·
International Journal of Quantum Chemistry
·
15
PDF
Thinking Globally, Acting Locally: On the Issue of Training Set Imbalance and the Case for Local Machine Learning Models in Chemistry
2019
·
Mojtaba Haghighatlari
, Ching-Yen Shih
, et al.
·
ChemRxiv
·
12
Towards Autonomous Machine Learning in Chemistry via Evolutionary Algorithms
2019
·
Gaurav Vishwakarma
, Mojtaba Haghighatlari
, et al.
·
ChemRxiv
·
11
Mining for Potent Inhibitors through Artificial Intelligence and Physics: A Unified Methodology for Ligand Based and Structure Based Drug Design
2024
·
Jie Li
, Oufan Zhang
, et al.
·
Journal of Chemical Information and Modeling
·
10
Protein Dynamics to Define and Refine Disordered Protein Ensembles
2022
·
Pavithra M. Naullage
, Mojtaba Haghighatlari
, et al.
·
The Journal of Physical Chemistry B
·
10
PDF
A Physics-Infused Deep Learning Model for the Prediction of Refractive Indices and Its Use for the Large-Scale Screening of Organic Compound Space
2019
·
Mojtaba Haghighatlari
, Gaurav Vishwakarma
, et al.
·
ChemRxiv
·
10
PDF
HLAIIPred: cross-attention mechanism for modeling the interaction of HLA class II molecules with peptides
2025
·
Mojtaba Haghighatlari
, Nicholas Marze
, et al.
·
Communications Biology
·
8
PDF
A Physics-Infused Deep Learning Model for the Prediction of Refractive Indices and Its Use for the Large-Scale Screening of Organic Compound Space
2019
·
Mojtaba Haghighatlari
, Gaurav Vishwakarma
, et al.
·
ChemRxiv
·
8
Towards Autonomous Machine Learning in Chemistry via Evolutionary Algorithms
2019
·
Gaurav Vishwakarma
, Mojtaba Haghighatlari
, et al.
·
ChemRxiv
·
7
Thinking Globally, Acting Locally: On the Issue of Training Set Imbalance and the Case for Local Machine Learning Models in Chemistry
2019
·
Mojtaba Haghighatlari
, Ching-Yen Shih
, et al.
·
ChemRxiv
·
6
PDF
Making Machine Learning Work in Chemistry: Methodological Innovation, Software Development, and Application Studies
2019
·
Mojtaba Haghighatlari
·
3
Idpconformergenerator: A flexible software suite for sampling the conformational space of disordered protein states
2023
·
João M.C. Teixeira
, Zi Hao Liu
, et al.
·
Biophysical Journal
·
2
PDF
Design of organic materials with tailored optical properties: Predicting quantum-chemical polarizabilities and derived quantities
2022
·
Gaurav Vishwakarma
, Aditya Sonpal
, et al.
·
Elsevier eBooks
·
2
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Works count:
31
Citation count:
944
H-index:
13
I10-index:
18
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