Majid Sohrabi

Lecturer, Doctoral Student: Faculty of Computer Science / School of Data Analysis and Artificial Intelligence
Lecturer: International College of Economics and Finance
Research Assistant: Faculty of Computer Science / Laboratory for Models and Methods of Computational Pragmatics

Majid Sohrabi has been at HSE University since 2022.

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Responsibilities

– Supervising of undergraduate and graduate students for thesis, coursework, and research projects.

– Conducting classes in disciplines in accordance with the curriculum.

– Conducting research / Writing scientific articles.

Education

2022

Master's
HSE University

2017

Bachelor's in Computer Science
University of Science and Technology of Mazandaran

Professional Interests

machine learning deep learning Interpretable Machine Learning data mining natural language processing genetic algorithm

Awards and Accomplishments

Scholarship "Pokrovskaya Perspective (2023-2024; 2024-2025)"

Bonus for young teachers of the Faculty of Computer Science from among graduates (2022-2023)
Young Faculty Support Programme (Group of Young Academic Professionals)
Category "New Lecturers" (2023–2024)

Postgraduate Studies

3rd year of study
Approved topic of thesis: Speciation in Genetic Algorithms with Interplay Among Species
Academic Supervisor: Vasilii Gromov

Courses (2024/2025)

Applied Quantitative Logistics (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Eng
Applied Quantitative Logistics (Mago-Lego; 3, 4 module)Eng
Data Analytics and Mining (Master’s programme; Faculty of Social Sciences; 2 year, 1, 2 module)Eng
Data Analytics and Mining (Mago-Lego; 1, 2 module)Rus
Intro to Programming in Python (Master’s programme; Faculty of Social Sciences; 1 year, 4 module)Eng
Intro to Programming in Python (Mago-Lego; 4 module)Eng
Intro to Programming in Python (Mago-Lego; 3, 4 module)Eng
Intro to Programming in Python (Master’s programme; Institute for Cognitive Neuroscience; 1 year, 3, 4 module)Eng
Introduction into Data Analytics and Mining (Mago-Lego; 1, 2 module)Eng
Introduction to Programming in R and Python (Mago-Lego; 2, 3 module)Eng
Machine Learning and Data Mining (Master’s programme; Faculty of Computer Science; 2 year, 1, 2 module)Eng
Machine Learning and Data Mining (Mago-Lego; 1, 2 module)Eng
Programming in Python (Master’s programme; Faculty of Humanities (Nizhny Novgorod); 1 year, 1, 2 module)Eng
Programming in Python (Mago-Lego; 1, 2 module)Eng
Statistics for Social Science (Bachelor’s programme; Faculty of World Economy and International Affairs; 2 year, 1, 2 module)Eng
Past Courses

Courses (2023/2024)

Applied Quantitative Logistics (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Eng
Applied Quantitative Logistics (Mago-Lego; 3, 4 module)Eng
Combinatorics, Graphs and Boolean Logic (Bachelor’s programme; Faculty of Computer Science; 3 year, 3, 4 module)Eng
How to Examine and Predict Time Series: Methods and Applications (Master’s programme; Faculty of Computer Science field of study Applied Mathematics and Informatics, field of study Applied Mathematics and Informatics; 2 year, 1, 2 module)Eng
How to Examine and Predict Time Series: Methods and Applications (Mago-Lego; 1, 2 module)Eng
Intro to Programming in Python (Master’s programme; Institute for Cognitive Neuroscience; 1 year, 3, 4 module)Eng
Intro to Programming in Python (Mago-Lego; 3, 4 module)Eng
Machine Learning and Data Mining (Master’s programme; Faculty of Computer Science; 2 year, 1, 2 module)Eng
Machine Learning and Data Mining (Mago-Lego; 1, 2 module)Eng
Mentor's seminar "Population and Development" (Master’s programme; Faculty of Social Sciences; 1 year, 1-4 module)Eng
Programming in Python (Master’s programme; Faculty of Humanities (Nizhny Novgorod); 1 year, 1, 2 module)Eng
Programming in Python (Mago-Lego; 1, 2 module)Eng
Research and Design Seminar "Modern Digital Technologies of Text Analytics" (Master’s programme; Faculty of Humanities (Nizhny Novgorod); 2 year, 2, 3 module)Eng

Courses (2022/2023)

Applied Quantitative Logistics (Master’s programme; Faculty of Computer Science field of study Applied Mathematics and Informatics, field of study Applied Mathematics and Informatics; 1 year, 3, 4 module)Eng
Applied Quantitative Logistics (Mago-Lego; 3, 4 module)Eng
Combinatorics, Graphs and Boolean Logic (Bachelor’s programme; Faculty of Computer Science; 3 year, 3, 4 module)Eng
How to Examine and Predict Time Series: Methods and Applications (Mago-Lego; 1, 2 module)Rus
How to Examine and Predict Time Series: Methods and Applications (Master’s programme; Faculty of Computer Science; 2 year, 1, 2 module)Rus
Introduction to Programming in R and Python (Mago-Lego; 2 module)Eng
Introduction to Programming in R and Python (Master’s programme; Faculty of Economic Sciences field of study Finance and Credit, field of study Finance and Credit; 2 year, 2 module)Eng
Research and Design Seminar "Modern Digital Technologies of Text Analytics" (Master’s programme; Faculty of Humanities (Nizhny Novgorod); 2 year, 1-3 module)Eng

Timetable for today

Full timetable

Grants

PhD studies under Russian Federation Scholarship 2022-2025.

M.Sc. studies under Russian Federation Scholarship 2020-2022.

Research projects - Thesis/Coursework (BSc, MSc) in Genetic Engineering Algorithm and Speciation

Genetic Algorithm (GA) is one of the pioneer evolutionary approaches in combinatorial optimization problems such as Allocation, Scheduling, Supply Chain Network, etc. The problem of interest is a type of NP-hard, and in most cases, it's impossible to find the optimal solution (exact solution). The basic GA algorithm interactively searches the solution space by two main operators, Crossover and Mutation. Although the result of the algorithm is promising, some limitations are using random crossover, mutation, and premature convergence, making the algorithm unable to find the global optimum. To address these limitations, we apply different approaches, redesigning the algorithm pipeline, pattern mining, clustering, etc. to search the solution space properly. Find my recent papers on Genetic Engineering Algorithms (GEA).

There are different projects related to this topic for BSc, and MSc (Thesis/Coursework) on implementing, testing, and developing your approaches to improve the algorithm. The valuable contribution is to find a better new local optimum or global optimum solution.

All projects involve programming and in English, those who are interested on the topic and improving English, programming, ML, DL are welcome to contact me.

Employment history

Title	Organization	Duration
Lecturer	Department of Data Analysis and Artificial Intelligence, HSE University	Sep 2022 - Present
Research Assistant	Laboratory of Models and Methods of Computational Pragmatics, HSE University	Mar 2022 - Present
Research Assistant	University of Science and Technology of Mazandaran	Oct 2015 - Agu 2017
Teaching Assistant	University of Science and Technology of Mazandaran	Jan 2014 - Dec 2015

Feb

2023

‘Working in Academia Is My Lifelong Desire’

Majid Sohrabi is a 28 year-old student from Iran currently enrolled in a doctoral programme at the HSE University Faculty of Computer Science. Before starting his PhD, he graduated with honours from the university’s Master of Data Science programme. In addition to studying, he also works as an assistant at the School of Data Analysis and Artificial Intelligence and a research assistant at the Laboratory for Models and Methods of Computational Pragmatics.