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Omri Abarbanel, Ph.D.

Computational Chemistry Ph.D., University of Pittsburgh.
Download full CV HERE.

EXPERIENCE

  • 2024 – Current

    Research Data Scientist - Post-doctoral Fellow, National Energy Technology Laboratory, Pittsburgh

  • 2018 – 2024

    PhD Candidate, Hutchison Group, Pittsburgh

  • 2016 – 2018

    Research Intern, Ulijn Group, New York

  • 2016 – 2018

    Teaching Assistant, CUNY Hunter College, New York

  • 2011 – 2016

    IT, Social and Digital Media Director, Israel Tourism Office, New York

  • 2010 – 2011

    SaaS Tier 1, RSA, Israel

  • 2007 – 2010

    Network Administrator, Israel Defense Force

RESEARCH INTERESTS

  • Data Science
  • Machine Learning
  • Material Discovery
  • Drug Discovery
  • Computational Chemistry

SKILLS

  • Research

    90%

  • Python

    90%

  • Bash

    75%

  • Data Visualization (Matplotlib, Seaborn, Plotly, etc.)

    80%

  • Data Manipulation (Pandas, numpy, etc.)

    75%

  • Machine Learning (Scikit-Learn, Pytorch, Tensorflow, Keras)

    80%

  • SQL

    60%

PROJECTS

2025

WellBERT - LLM model to extract information from oil and gas well inspector comments
A BERT based model to extract information from oil and gas well inspector comments.

2024

QupKake - micro-pKa prediction model
A graph-neural network model for predicting pKa values of small molecules.

2022

xTB Parsing Support for cclib
Adding xTB parsing support for the cclib python package.

2023

Pi-System Features for Machine Learning
Creating a descriptors for conjugated molecules for machine learning.

2021

Machine Learning to Accelerate Screening for Marcus Reorganization Energies
Combining machine learning and quantum mechanical features to find conjugated polymers with low reorganization energy

2022

Finding High-Spin Polymers Using Genetic Algorithms
Accelerating the search for novel materials using genetic algorithms.

RECENT PUBLICATIONS

[All Publications]
  1. Cclib 2.0: An Updated Architecture for Interoperable Computational Chemistry
    Berquist, Eric, Dumi, Amanda, Upadhyay, Shiv, Abarbanel, Omri D., Cho, Minsik, Gaur, Sagar, Cano Gil, Victor Hugo, Hutchison, Geoffrey R., Lee, Oliver S., Rosen, Andrew S., Schamnad, Sanjeed, Schneider, Felipe S. S., Steinmann, Casper, Stolyarchuk, Maxim, Vandezande, Jonathon E., Zak, Weronika, and Langner, Karol M.
    The Journal of Chemical Physics, vol. 161, pp. 042501, Jul, 2024
  2. QupKake: Integrating Machine Learning and Quantum Chemistry for micro-pKa Predictions
    Abarbanel, Omri, and Hutchison, Geoffrey
    ChemRxiv, 2023
  3. Strategies for Computer-Aided Discovery of Novel Open-Shell Polymers
    Abarbanel, Omri D., Rozon, Julisa, and Hutchison, Geoffrey R.
    The Journal of Physical Chemistry Letters, vol. 13, pp. 2158-2164, 2022