More About Gerardo

Gerardo has always been motivated by the search for knowledge. He enjoy understanding the origin and evolution of all sort of natural phenomenon because he sees this as a way to improve his life and the life of people around him. This drove him to become a physicist and the way he chose to study nature was using programming tools. Computers are logical, reliable and efficient (most of the time) and a potential way to predict and improve our future. He has applied his programming skills (since he was a ḱid) to research, both in academia and industrial environments, in a variety of interesting areas, such as:

- Quantum chemistry
- Nanoscience
- Molecular Dynamics
- Condensed Matter
- Artificial intelligence (applied to physics and chemistry)
- Drug discovery
- Quantum Computers

Learn More About Gerardo

Private Sector Experience

Founder, CEO & Programmer of QCS Company with more than 40 successful complex commercial software projects in the scientific, academic, private and government sectors.

Academic Experience

With four postdocs (research associate or research assitant) in Artificial Intelligence (AI) in Quantum Chemistry, Condensed Matter Physics, Molecular Dynamics and AI in Drug Design.

Academic experience (2006-2021)

Progaming lenguages used: Python 2.0, Scikit, Numpy

Bachelor in Physics (2011)

Relativistic effects calculations in Au and Mg.

National Autonomous University of Mexico

PhD in Theoretical and Computational Physical-Chemistry (2015)

Electrostatic theories, polarization and Nanoswitches in Material Science.

The University of Nottingham

Postdoc in Artificial Inteligence in Drug Discovery (2016)

Machine Learning and Cheminformatics to predict drug selectivity based on structural fingerprints

The University of Nottingham

Postdoc in Molecular Dynamics and Kinetic Monte Carlo simulations (2016)

Modelling glass lattice transitions to investigate the microscope details of the dynamics of cristals, glasses and supercooled liquids.

The Hong Kong Polytechnic University

Postdoc in Sagnac Matter Wave Interferometry (2017)

To describe the Sagnac effect in a system with magnetically trapped atoms for a precise gyroscope, a numerical solution of the Gross-Pitaevskii equation.

The University of Nottingham

Postdoc in Machine Learning in Quantum Chemistry and NMR (2018-2020)

Introducing machine learning techniques such as Gradient-Enhanced Kriging, Neural Networks and SVM for surrogate models in numerical atomistic simulations to improve the wave functions, molecular geometry optimizations and the chemial shift in NMR.

Uppsala University

Honourable ABTA Doctoral Research Award

University College London (UCL-2015)

Awarded for the national training school in theoretical chemistry

University of Oxford (2012)

PhD Scholarship Award

University of Nottingham (2011)

Private Sector Experience (2003-2011)

(Relevant Clients as a CEO and programer of Identitas and QSS)

Multimedia programmed for Microsoft to the Microsoft Tech-Ed Conference. Mainly in Visual Basic with some elements in action script.

Diverse Software and Hardware projects were made for the museum papalote more than 15 projects for different exhibisions were , using different programming lenguages such as C++, Action Script, Lingo and others.

Multimedia programmed in Lingo to promote services of Xerox company. The company made 10M copies for distribution accross Northamerica and Latinamerica.

Explora Science Museum. More than 10 software and hardware projects using different programming lenguages, including C++ with DirectX. Two of them 3D Virtual Reallity games with helmeths and gloves.

Warner Jenkinson Latinoamerica (now sensient) is the biggest company for colorants in the world. Two projects were made a Multimedia DVD to show they services and a virtual laboratory were they Clients can choose the color of the food and the software calculated the chemical forfula of the colorants, this project involved research in chemical transformation from RGB to basic color food.

Ministery of culture of Italy

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Microsoft
Papalote
Xerox
Explora
Warner
Ministery
Henkel
Marani
Fide

Relevant Publications

Restricted-Variance Molecular Geometry Optimization Based on Gradient-Enhanced Kriging

Journal of Chemical Theory and Computation (2020)

The Halogen Bond of Halonium Ions: Benchmarking DFT Methods and Machine Learning for the Description of NMR Chemical Shifts

Journal of Chemical Theory and Computation (2020)

Restricted-Variance Constrained, Reaction Path, and Transition State Molecular Optimizations Using Gradient-Enhanced Kriging

Journal of Chemical Theory and Computation (2020)

Predicting polarisation hemisphere switch in C 60 due to the motion of an internal point charge with a classical electrostatic and DFT solutions

arXiv:1803.04512 (2019)

The influence hydrogen atom addition has on charge switching during the motion of a metal atom in endohedral Ca@C 60 H 4 isomers

Philosophical Transactions A of the Royal Society

Towards a molecular switch based on metal atoms trapped in endohedral fullerene

Phys. Chem. Chem. Phys. (2014)

Relativistic DFT calculations of magnetic moments on pristine and thiolated Mn@Au x (x=6,12)

Phys. Chem. Chem. Phys. (2014)

Experimental binding energies for the metal complexes [Mg(NH3)n]2+, [Ca(NH3)n]2+ and [Sr(NH3)n]2+ determined from kinetic energy release measurements

J. Phys. Chem. A, 118, 8525–32 (2014)

Surface-charge distribution on a dielectric sphere due to an external point charge: examples of C 60 and C 240 fullerenes

Phys. Chem. Chem. Phys. (2013)

Gerardo Raggi

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More About Gerardo

Private Sector Experience

Academic Experience

Academic experience (2006-2021)

Bachelor in Physics (2011)

Relativistic effects calculations in Au and Mg.

PhD in Theoretical and Computational Physical-Chemistry (2015)

Electrostatic theories, polarization and Nanoswitches in Material Science.

Postdoc in Artificial Inteligence in Drug Discovery (2016)

Machine Learning and Cheminformatics to predict drug selectivity based on structural fingerprints

Postdoc in Molecular Dynamics and Kinetic Monte Carlo simulations (2016)

Modelling glass lattice transitions to investigate the microscope details of the dynamics of cristals, glasses and supercooled liquids.

Postdoc in Sagnac Matter Wave Interferometry (2017)

To describe the Sagnac effect in a system with magnetically trapped atoms for a precise gyroscope, a numerical solution of the Gross-Pitaevskii equation.

Postdoc in Machine Learning in Quantum Chemistry and NMR (2018-2020)

Introducing machine learning techniques such as Gradient-Enhanced Kriging, Neural Networks and SVM for surrogate models in numerical atomistic simulations to improve the wave functions, molecular geometry optimizations and the chemial shift in NMR.

Honourable ABTA Doctoral Research Award

Awarded for the national training school in theoretical chemistry

PhD Scholarship Award

Private Sector Experience (2003-2011)

(Relevant Clients as a CEO and programer of Identitas and QSS)

Relevant Publications

Restricted-Variance Molecular Geometry Optimization Based on Gradient-Enhanced Kriging

The Halogen Bond of Halonium Ions: Benchmarking DFT Methods and Machine Learning for the Description of NMR Chemical Shifts

Restricted-Variance Constrained, Reaction Path, and Transition State Molecular Optimizations Using Gradient-Enhanced Kriging

Predicting polarisation hemisphere switch in C 60 due to the motion of an internal point charge with a classical electrostatic and DFT solutions

The influence hydrogen atom addition has on charge switching during the motion of a metal atom in endohedral Ca@C 60 H 4 isomers

Towards a molecular switch based on metal atoms trapped in endohedral fullerene

Relativistic DFT calculations of magnetic moments on pristine and thiolated Mn@Au x (x=6,12)

Experimental binding energies for the metal complexes [Mg(NH3)n]2+, [Ca(NH3)n]2+ and [Sr(NH3)n]2+ determined from kinetic energy release measurements

Surface-charge distribution on a dielectric sphere due to an external point charge: examples of C 60 and C 240 fullerenes