Soroosh Shalileh
- Research Fellow:Center for Language and Brain
- Laboratory Head:Vision Modelling Laboratory
- Soroosh Shalileh has been at HSE University since 2018.
Responsibilities
- Mathematical formulation of a given research problem
- Optimisation of formulated problem
- Implementation of the formulated problem and the developed algorithm
- Fine-tuning and adopting the existing machine learning/Data Science methods on various projects
- Writing Scientific papers
Education and Degrees
- 2021
Candidate of Sciences* (PhD)
HSE University - 2017
Master's
Исламский университет Азад
According to the International Standard Classification of Education (ISCED) 2011, Candidate of Sciences belongs to ISCED level 8 - "doctoral or equivalent", together with PhD, DPhil, D.Lit, D.Sc, LL.D, Doctorate or similar. Candidate of Sciences allows its holders to reach the level of the Associate Professor.
Teaching Assistant for the Course Moderm Methods of Data Analysis, Lecturer Prof. Boris Mirkin (2018 - up to now)
Dissertation for a degree of Candidate of Science
S. Shalileh Clustering feature-rich networks using data recovery approach
Publications14
- Article Shalileh S. An Effective Partitional Crisp Clustering Method Using Gradient Descent Approach // Mathematics. 2023. Vol. 11. No. 12. Article 2617. doi
- Article Mirkin B., Shalileh S. Community Detection in Feature-Rich Networks Using Data Recovery Approach // Journal of Classification. 2022. Vol. 39. P. 432-462. doi
- Article Shalileh S., Mirkin B. Community Partitioning over Feature-Rich Networks Using an Extended K-Means Method // Entropy. 2022. Vol. 24. No. 5. Article 626. doi
- Chapter Shalileh S., Mirkin B. A Method for Community Detection in Networks with Mixed Scale Features at Its Nodes, in: Complex Networks & Their Applications IX. Volume 1: Proceedings of the Ninth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2020. Springer, 2021. P. 3-14. doi
- Chapter Shalileh S., Mirkin B. An Extension of K-Means for Least-Squares Community Detection in Feature-Rich Networks, in: COMPLEX NETWORKS 2021: Complex Networks & Their Applications X.. Springer, 2021. P. 285-296. doi (in press)
- Chapter Shalileh S., Mirkin B. Detecting Communities in Feature-Rich Networks with a K-Means Method, in: Intelligent Data Engineering and Automated Learning – IDEAL 2021. Springer, 2021. P. 539-547. doi (in press)
- Chapter Shalileh S. Improving Maximum Likelihood Estimation Using Marginalization and Black-Box Variational Inference, in: Intelligent Data Engineering and Automated Learning – IDEAL 2021. Springer, 2021. P. 204-212. doi (in press)
- Article Shalileh S., Mirkin B. Least-squares community extraction in feature-rich networks using similarity data // Plos One. 2021. Vol. 16. No. 7. Article 0254377. doi
- Article Shalileh S., Mirkin B. Summable and nonsummable data‐driven models for community detection in feature‐rich networks // Social Network Analysis and Mining. 2021. Vol. 11. No. 1. P. 1-23. doi
- Chapter Shalileh S., Mirkin B. A Data Recovery Method for Community Detection in Feature-Rich Networks, in: 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). Association for Computing Machinery (ACM), 2020. doi P. 99-104. doi
- Chapter Shalileh S., Mirkin B. A One-by-One Method for Community Detection in Attributed Networks, in: Intelligent Data Engineering and Automated Learning – IDEAL 2020/ 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part II Vol. 12490: Lecture Notes in Computer Science. Cham : Springer, 2020. P. 413-422. doi
- Chapter Shalileh S., Mirkin B. Detection of an unspecified number of communities in feature-rich networks, in: Proceedings of MARAMI 2020 - Modèles & Analyse des Réseaux : Approches Mathématiques & Informatiques - The 11th Conference on Network Modeling and Analysis(Vol-2750) Vol. Vol-2750: Modèles & Analyse des Réseaux : Approches Mathématiques & Informatiques - Network Modeling and Analysis 2020. CEUR-WS.org, 2020. P. 1-12.
- Chapter Shalileh S., Shahdi S. O. Crowd scenes analysis using multiple sliding windows classifiers and Histogram of Oriented Gradient, in: 2017 10th Iranian Conference on Machine Vision and Image Processing (MVIP). IEEE, 2017. doi P. 31-38. doi
Employment history
Nov. 2019 – present HSE-LAMBDA: Research Assistant
Jan. 2018 – Dec. 2020 HSE University: Teaching Assistance
Jun. 2017 – Nov. 2019 Natimatica Ltd.: Machine Learning and Computer Vision Data Engineer
Feb. 2015 – Sept. 2016 Freelance Control Engineer
Sept. 2011 – Sept. 2015 TMB-co: Research and Development (R&D) Technical Manager in Designing and Producing
Sept. 2013 – Dec. 2014 Qazvin Islamic Azad University of Iran: Teacher Assistant
Thermodynamics and Entropy Research eConference
The head of the laboratory Shalileh Soroosh presented a talk at the conference