Majid Sohrabi
Majid Sohrabi
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Lecturer,
Research Assistant,
HSE University (click here )
Bio: Majid Sohrabi received his B.Sc. in Computer Science at the Department of Computer Science at the University of Science and Technology of Mazandaran in 2017, and his M.Sc. in Data Science at the Department of Data Analysis and Artificial Intelligence at the National Research University Higher School of Economics, Moscow in 2022. He is an instructor and research assistant at the Faculty of Computer Science in the Department of Data Analysis and Artificial Intelligence and Laboratory for Models and Methods of Computational Pragmatics at HSE University, respectively. His research interests include Medical Data Analysis, Data Analysis in Healthcare, Data Mining, Machine Learning, and Deep Learning.
Recent News:
[October 12, 2022] Supervision of students in Term Papers and Thesis are available. HSE M.Sc. and B.Sc. students are welcome to contact me.
[September 1, 2022] I will be joining the Faculty of Computer Science at HSE University as an instructor.
Education.
Education.
2022 - Present
PhD in Computer Science, National Research University Higher School of Economics
- Thesis: "Speciation in Genetic Algorithm with Interplay Among Species", Supervisor: Prof. Vasiili Gromov
2020 - 2022
MSc in Data Science, National Research University Higher School of Economics
- Term Paper: "Globally Optimal Decision Algorithms for Machine Learning", Supervisor: Prof. Oleg Pianykh
- Thesis: "Physics-Informed Neural Networks for Medical Diagnostics", Supervisor: Prof. Vasiili Gromov
2013 - 2017
BSc in Computer Science, University of Science and Technology of Mazandaran
Research.
Research.
Liquid Neural Networks: Medical Applications
Liquid Neural Networks: Medical Applications
Multi-Model Methods for Drug-Drug Interaction Extraction using Textual and Structural Data
Multi-Model Methods for Drug-Drug Interaction Extraction using Textual and Structural Data
Genetic Engineering Algorithm (GEA), a Modified Version of Genetic Algorithm
Genetic Engineering Algorithm (GEA), a Modified Version of Genetic Algorithm
Selected Publication.
Selected Publication.
[1] Gromov, V.A., Zvorykina, E.I., Beschastnov, Y.N., Sohrabi, M. (2024). Date-Driven Approach for Identifying State of Hemodialysis Fistulas: Entropy-Complexity and Formal Concept Analysis. In: Ignatov, D.I., et al. Recent Trends in Analysis of Images, Social Networks and Texts. AIST 2023. Communications in Computer and Information Science, vol 1905. Springer, Cham. https://doi.org/10.1007/978-3-031-67008-4_19
[2] Sohrabi, M., Fathollahi-Fard, A.M. & Gromov, V.A. Genetic Engineering Algorithm (GEA): An Efficient Metaheuristic Algorithm for Solving Combinatorial Optimization Problems. Autom Remote Control 85, 252–262 (2024). https://doi.org/10.1134/S000511792403007X
Teaching.
Teaching.
Fall 2024
Machine Learning and Data Mining
Machine Learning
Data Analysis and Mining
Statistics for Social Science
Winter 2024
Introduction to Programming in Python
Deep Learning
Applied Quantitative Logistics
Combinatorics, Graph, Boolean Logics
Fall 2023
Machine Learning and Data Mining
Time Series Analysis and Forecasting
Modern Digital Technologies of Text Analysis
Programming in Python
Mentor's Seminar "Population and Development"
Fall 2022
Time Series Analysis and Forecasting
Modern Digital Technologies of Text Analysis
Introduction to Programming in R and Python
Winter 2023
Analysis and Visualization of Networks
Applied Quantitative Logistics
Combinatorics, Graph, Boolean Logics
Previously Taught
Fundamentals of Computer Programming
Advance Computer Programming
Contact.
Contact.
Mail:
msohrabi [at] hse [dot] ru
Phone:
+7 (929) ***-**-**
Address:
Room S940, 11 Pokrovsky Bulvar, Pokrovka Complex, Moscow, Russia.
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