Majid Sohrabi
- Assistant, Doctoral Student:Faculty of Computer Science / School of Data Analysis and Artificial Intelligence
- Research Assistant:Faculty of Computer Science / Laboratory for Models and Methods of Computational Pragmatics
- Majid Sohrabi has been at HSE University since 2022.
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
Young Faculty Support Programme (Group of Young Academic Professionals)
Category "New Lecturers" (2023-2024)
Postgraduate Studies
2nd year of study
Approved topic of thesis: Speciation in Genetic Algorithms with Interplay Among Species
Academic Supervisor: Gromov, Vasilii
Courses (2023/2024)
- Applied Quantitative Logistics (Master’s programme; Faculty of Computer Science; 1 year, 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 "01.04.02. Прикладная математика и информатика", field of study "01.04.02. Прикладная математика и информатика"; 2 year, 1, 2 module)Eng
- Intro to Programming in Python (Master’s programme; Institute for Cognitive Neuroscience; 1 year, 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
- Research and Design Seminar "Modern Digital Technologies of Text Analytics" (Master’s programme; Faculty of Humanities (Nizhny Novgorod); 2 year, 2, 3 module)Eng
- Past Courses
Courses (2022/2023)
- Applied Quantitative Logistics (Master’s programme; Faculty of Computer Science; 1 year, 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; 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; 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
Publications3
- Article Sohrabi M., Fathollahi-Fard A. M., Vasilii A. Gromov. Genetic Engineering Algorithm (GEA): An Efficient Metaheuristic Algorithm for Solving Combinatorial Optimization Problems // Automation and Remote Control. 2024. Vol. 85. No. 3. P. 274-286. doi
- Article Сохраби М., Фатхоллахи-Фард А., Громов В. А. АЛГОРИТМ ГЕНЕТИЧЕСКОЙ ИНЖЕНЕРИИ (GEA): ЭФФЕКТИВНЫЙ МЕТАЭВРИСТИЧЕСКИЙ АЛГОРИТМ ДЛЯ РЕШЕНИЯ ЗАДАЧ КОМБИНАТОРНОЙ ОПТИМИЗАЦИИ // Автоматика и телемеханика. 2024. № 3. С. 23-37. doi
- Article Gromov V., Zvorykina E., Beschastnov Y., Sohrabi M. Date-Driven Approach for Identifying State of Hemodialysis Fistulas: Entropy-Complexity and Formal Concept Analysis // Working papers by Cornell University. Series math "arxiv.org". 2023. Article 14399. doi
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 |
|
Assistant |
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 Fellow |
University of Science and Technology of Mazandaran |
Oct 2015 - Agu 2017 |
|
Teaching Assistant |
University of Science and Technology of Mazandaran |
Jan 2014 - Dec 2015 |
‘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.