Haleh Hajizadeh

Master of Computational Cosmology

2017 - 2020

Shahid Beheshti University, Tehran, Iran

I continued my education as an MSc student in computational cosmology at Shahid Beheshti University, which is the best university in this field in Iran. I took courses like cosmology, astrophysics, general relativity, advanced quantum mechanics, computational physics, statistical mechanics. I completed my master's degree under the supervision of Dr. Marzieh Farhang (assistant professor at SBU) and Dr. Alireza Vafaei Sadr (postdoc at the University of Geneva).

Bachelor of physics

2012 - 2016

University of Tabriz, Tabriz, Iran

In The Search of Cosmic Strings on Planck’s Data with Image Processing, Statistical Tools and Machine Learning Methods

2018 - 2020

SBU, Tehran, Iran

• Cosmic Strings (CS) are topological defects that may have been produced in the early universe during a phase transition. Their detection would give a unique opportunity to study the physics of the phase transition in early universe. Our purpose was to search for CS's footprints on CMB by constraining their tension. We used CMB simulations to train machine learning algorithms and applied the obtained model on Planck's data. We wrote the research results in a paper accepted to be published in MNRAS.

PLAsTiCC (Photometric LSST Astronomical Time-Series Classification Challenge)

2019 - 2019

IPM, Tehran, Iran

• During my master, I participated in data science bootcamp and we chose to work on an astronomical data as the final project. My teammates and I worked on the PLAsTiCC. The challenge was to classify astronomical sources that vary with time into different classes from Large Synoptic Survey Telescope (LSST), scaling from a small training set to a vast test set the type the LSST will discover. We used the LightGBM algorithm to train a model to classify astronomical objects into different classes.

Classification of Galaxies based on their Infalling Time and Loss Mass in Galaxy groups with Machine Learning

2021 - Present

IPM, Tehran, Iran

• Today it is necessary to consider environmental effects that act at the clusters and groups to interpret the population of galaxies. One possibility is that environmental mechanisms may be preferentially working in higher-density environments, halting star formation and transforming galaxies morphologically. Therefore, it is essential to study clusters and groups of galaxies. We want to explore the correlation between galaxies' different features which related to their life in populations.

Searching for the relationship between Signal to Noise Ratio (SNR) and exposure time in Iranian National Observatory Lens Array

2020 - Present

IPM, Tehran, Iran

• This is a topic of an ongoing project that I started (Head of Iranian National Observatory) at IPM. Astronomers want to know how long they need to expose their image to reach the SNR they want. In this project, our goal is to find a correlation between SNR and exposure time and other parameters that can affect SNR, like filter type, in INOLA. Finally, we want to develop an algorithm based on our calculations that help people get parameters to reach a certain SNR.