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Click here or scroll down to respond to this candidateCandidate's Name
ProfileUnique and passionate physicistwith over 30 years experience inpredicting the outcome ofcomplex systems. Leadingdeveloper for a framework topredict the scaling of hysteresis,laser absorption by the retina,and the 3D structure of proteins.Responsible for implementingthe bi-modal distribution of theprotein dihedrals into proteinstructure prediction tools. Wasamong the rst to introduce MLinto 3D protein prediction. Over15 years experience in ML and AI.A pioneer of this approach inbioinformatics.Google scholar publication listContact details@ EMAIL AVAILABLEH PHONE NUMBER AVAILABLEm mamiris.comB 1620 E 72ND ST, Indianapolis,Indiana, USAPersonal informationCitizenship: Israel, USALanguages: 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 CarpenterEducationPh.D. Physics University of Texas at Austin 19962003Thesis title: Ferromagnetic properties of partially lled two-dimensional Ising latticesMean eld and Ising models of percolating ferromagnets and hysteresis. B.Sc. Physics/Mathematics Hebrew University, Jerusalem 19931996 ExperienceAdjunct Professor at Department of Physics, Indiana University Indianapolis, Indianapolis, Indiana USA 2024NowTeaching undergraduate physicsAdjunct Professor at Department of Physics, Indiana University Purdue University Indianapolis, Indianapolis, Indiana USA 20172024Teaching undergraduate physicsConsultant at Battelle Center for Mathematical Medicine, Nationwide Childrens Hospital, Columbus, OH 20122024Machine 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 2012NowMachine 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 20122017Machine learning in protein structure and disorder. Research Associate at CCBB, School of Informatics, Indiana University Purdue University, Indianapolis, Indiana 20072012Predicting protein dihedrals, ASA, disorder, and 3D structure. Research Associate at Department of Physics, Florida International University, Miami, Florida 20032007Fluid/solid thermodynamic modelling for laser/retina interaction. Selected Publications2022 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. Articial Neural Networks. Springer New York, PHONE NUMBER AVAILABLE 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 |
