Sepideh Shahsavarani

ac63yx@r.postjobfree.com, +1-650-***-****

www.linkedin.com/in/sepideh-shahsavarani-581a8a151/ RESEARCH

INTERESTS

Data Science: Mining, Visualization, Modeling, Statistical Inference, Machine Learning, Deep Learning (Arti cial intelligent), Statistical and Regression Analysis

EDUCATION Ph.D, High Energy Physics, University of Texas at Arlington, 2012 - 2018, GPA: 4.0/4.0

Advisors: Dr. Amir Farbin

Dissertation Title: \Measurement of the Electron-Neutrino Elas- tic Scattering Cross-Section in Mini Booster Neutrino Experiment at Fermi National Laboratory"

Master of Science, Fundamental Particle Physics, Ferdowsi Univer- sity, Mashhad, Iran, 2006 - 2009, GPA: 3.9/4.0

Advisor: Dr. Mohammad Ebrahim Zomorrodian

Dissertation Title:\Perturbative Explanation of Particles Spectrum after Electron/Positron Collision in Center of Mass Energy 60 GeV "

Bachelor of Science, Solid State Physics, Ferdowsi University, Mash- had, Iran, 2002 - 2006, GPA: 3.8/4.0

RELATED

COURSES AND

CERTIFICATE

University of Texas at Arlington (Ph.D.): Quantum eld theory 1(Probability Theory), Quantum Field Theory 2 (Probability Theory), Advanced Particle Physics (Advanced Probability Theory), Experi- mental Particle Physics (Modeling Physical Data), Applied Machine Learning in Physics (Neural Networks and Deep Learning).

Stanford University (certi cate): Machine Learning https://www.coursera.org/account/accomplishments/certi cate/Z9SUCQ7DDV8B

deeplearning.ai (certi cate):

Neural Networks and Deep Learning

https://www.coursera.org/account/accomplishments/verify/C9EABCYD3J3Y Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

https://www.coursera.org/account/accomplishments/certi cate/JQHZMEPP9BLH Structuring Machine Learning Projects

https://www.coursera.org/account/accomplishments/verify/MYXUYDAJHHLB Convolutional Neural Networks

https://www.coursera.org/account/accomplishments/verify/5QYYU9ZBADTJ RESEARCH

PROJECTS

AND

EXPERIENCE

Research Assistant, University of Texas at Arlington 2013 - 2018

Fermi National Accelerator Laboratory:

{ MiniBooNE Experiment: Analyzed 120GB data of particles interaction in mineral oil detector. The recorded data, which can be thought as images, is turned into features using sophisti- cated "reconstruction" algorithms. My research involved statisti- cal modeling and interpretation of a speci c subset of this data to extract the electron-neutrino elastic scattering cross-section (the probability of interaction). Did the 2 dimensional t of data to Monte Carlo simulation events with all systematic errors in my data using the CERN tting software (Hist tter), also, it has been done with my own tting code in ROOT data analysis software, also I hired the power of the python programing like numpy, scipy, matplotlib to do tting, and visualizing the data, and the errors. By Analyzing the data using python library reduced the codebase size by 50% and ran twice faster.

{ LArIAT Experiment: Simulated a large sample (15 million examples/16TB data) of Neutrino interactions in Liquid Argon. First, tried GoogleNet DNN to do particles classi cation, had to do down sampling and reduced the resolution to be able to use it out-of-the-box. In the second stage, tried di erent mod- els in Keras (high-level neural networks library) to classify parti- cles/interactions in the detector with higher resolution. The bet- ter results obtained than doing the physical reconstruction codes to separate the particles/interaction.

Instructor

{ University of Texas at Arlington 2012 - 2013: Physics Lab

{ Azad University, Iran 2009-2011: Fundamental Physics Courses for Non-Physics Major

SKILLS General: Problem solving, programming, data visualization, data analysis frameworks, data reduction, statistical analysis, writing tech- nical reports

Programming Languages : Python, C++(familiar)

Markup Languages: LATEX, HTML

General Software: Linux (Ubuntu), bash, git, mathematica

Data Science/DL Libraries: Ca e, TensorFlow, Keras, matplotlib, numpy, pandas, scipy, octave

High Energy Physics Software: ROOT, PyROOT, RooFit, RooSt- ats, HistFactory, MadGraph, Larsoft, HistFitter