Machine Learning Research Associate
Resume:
Eshel Faraggi
Profile
Unique and passionate physicist
with over 30 years experience in
predicting the outcome of
complex systems. Leading
developer for a framework to
predict the scaling of hysteresis,
laser absorption by the retina,
and the 3D structure of proteins.
Responsible for implementing
the bi-modal distribution of the
protein dihedrals into protein
structure prediction tools. Was
among the first to introduce ML
into 3D protein prediction. Over
15 years experience in ML and AI.
A pioneer of this approach in
bioinformatics.
Google scholar publication list
Contact details
@ ********@*****.***
m mamiris.com
B 1620 E 72ND ST, Indianapolis,
Indiana, USA
Personal information
Citizenship: Israel, USA
Languages: Hebrew (native),
English (native), Arabic (D2)
Skills
• Mechanics, E&M, Fluid Dyn.
• Machine Learning
• FORTRAN, C Matlab, Math.
• Linux, BASH, Perl, Python, JAVA
• MS Word, Excel, PowerPoint
• Empath, Photographer, Musician
• Carpenter
Education
Ph.D. Physics University of Texas at Austin 1996–2003
Thesis title: Ferromagnetic properties of partially filled two-dimensional Ising lattices
Mean field and Ising models of percolating ferromagnets and hysteresis. B.Sc. Physics/Mathematics Hebrew University, Jerusalem 1993–1996 Experience
Adjunct Professor at Department of Physics, Indiana University Indianapolis, Indianapolis, Indiana USA 2024–Now
Teaching undergraduate physics
Adjunct Professor at Department of Physics, Indiana University Purdue University Indianapolis, Indianapolis, Indiana USA 2017–2024
Teaching undergraduate physics
Consultant at Battelle Center for Mathematical Medicine, Nationwide Children’s Hospital, Columbus, OH 2012–2024
Machine learning models for protein structure prediction and predicting the effect of genetic variation. The role of entropy in protein structure. Physicist at Research and Information Systems, LLC, Indianapolis, Indiana 2012–Now
Machine learning in protein structure and variation. Electromagnetism in biological cell division. Understanding nuclear structure from only electro- magnetic charge and its quantum interaction.
Visiting Professor at Dept. of Biochem. and Mol. Bio., Indiana University School of Medicine, Indianapolis, Indiana 2012–2017
Machine learning in protein structure and disorder. Research Associate at CCBB, School of Informatics, Indiana University Purdue University, Indianapolis, Indiana 2007–2012
Predicting protein dihedrals, ASA, disorder, and 3D structure. Research Associate at Department of Physics, Florida International University, Miami, Florida 2003–2007
Fluid/solid thermodynamic modelling for laser/retina interaction. Selected Publications
2022 Faraggi, E; There is only charge: Heisenberg-Coulomb based theory of the quarks, nucleons, and the nuclei. Authorea Preprints. 2019 Faraggi, E, Dunker, AK, Jernigan, RL, & Kloczkowski, A; Entropy, Fluctu- ations, and Disordered Proteins. Entropy, 21, 764. 2017 Faraggi, E, Dunker, AK, Sussman JL, & Kloczkowski A; Comparing NMR and X-ray protein structure: Lindemann-like parameters and NMR disorder. J. of Biomol. Struc. and Dyn. 1-11.
2015 Faraggi E & Kloczkowski A; GENN: a GEneral Neural Network for learning tabulated data with examples from protein structure prediction. Artificial Neural Networks. Springer New York, 165-178. 2014 Faraggi E, Zhou Y, & Kloczkowski A; Accurate single-sequence pre- diction of solvent accessible surface area using local and global features. Proteins, 82, 3170.
2014 Faraggi E & Kloczkowski A; A global machine learning based scoring function for protein structure prediction. Proteins, 82, 752 2012 Faraggi E; Symmetrical charge-charge interactions in ionic solutions: implications for biological interactions arxiv.org/abs/1201.0556
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