Daria Semenova
- Junior Research Fellow:HSE Campus in Perm / Центр когнитивных нейронаук
- Lecturer, Doctoral Student:HSE Campus in Perm / Faculty of Computer Science, Economics, and Social Sciences / School of Economics and Finance
- Daria Semenova has been at HSE University since 2017.
Continuing education / Professional retraining / Internships / Study abroad experience
Basics of Writing an Empirical Research Article in English (40 hours), Moscow, Russia, 2022
The Neuromarketing Toolbox (19 hours), an online course on the Coursera platform from the University of Copenhagen Business School, 2022
Text data analysis in R and Python (82 hours), Perm, Russia, 2021
Global School on Empirical Research Methods (Course "Econometrics of Big Data"), Ljubljana, Slovenia, 2019
Econometrics, online course by B. Demeshev on the Coursera platform from the University Higher School of Economics, 2019
Advanced training courses Empowering your Academic Writing in English: Academic Writing vs General Writing (24 hours), Moscow, Russia, 2018
3d Winter School on Data Analytics, Nizhny Novgorod, Russia, 2018
Winter School of Economics of Sberbank and the Higher School of Economics, Moscow, Russia, 2018
World Championship in Econometrics Econometric Game 2018, Amsterdam, Netherlands, 2018
Advanced training courses "Academic communication in a foreign language environment (in the amount of 38 hours)", Perm, Russia, 2017
Summer Hackathon School on Customer Analytics (Customer Analytics Summer School), HSE-Perm, Perm, Russia, 2017
Young Faculty Support Program (Group of Young Academic Professionals)
Category "New Researchers" (2022)
Category "New Researchers" (2019)
Postgraduate Studies
2nd year of study
Approved topic of thesis: Willingness to pay in the food market: development of attributive and neuroeconomic approaches
Academic Supervisor: Molodchik, Mariya
Courses (2022/2023)
- Econometrics (Bachelor’s programme; Faculty of Management; 3 year, 1-4 module)Rus
- Econometrics (Bachelor’s programme; Faculty of Management; 3 year, 4 module)Rus
- Industrial Organization Theory (Bachelor’s programme; Faculty of Management; 3 year, 1, 2 module)Eng
- Past Courses
Courses (2019/2020)
Courses (2018/2019)
- Market Analysis (Bachelor’s programme; Faculty of Economics, Management, and Business Informatics; 2 year, 2 module)Rus
- Qualitative and Quantitative Methods of Elaboration and Adoption of Management Decisions (Bachelor’s programme; Faculty of Economics, Management, and Business Informatics; 2 year, 1-3 module)Rus
Publications7
- Article Ozhegov E. M., Teterina D. Methods of Machine Learning for Censored Demand Prediction // Lecture Notes in Computer Science. 2019. Vol. 11331. P. 441-446. doi
- Chapter Ozhegov E. M., Semenova D. Methods of Machine Learning for Censored Demand Prediction, in: Machine Learning, Optimization, and Data Science. 4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers / Ed. by G. Nicosia, P. Pardalos, G. Giuffrida, R. Umeton, V. Sciacca. Cham : Springer, 2019. doi P. 441-446. doi
- Chapter Daria Semenova, Maria Temirkaeva. The Comparison of Methods for Individual Treatment Effect Detection, in: Proceedings of the Fifth International Workshop on Experimental Economics and Machine Learning (EEML 2019),Perm, Russia, September 26, 2019 / Ed. by A. V. Buzmakov, K. Heinrich, D. I. Ignatov, D. Potapov, R. Tagiew. Vol. 2479. CEUR Workshop Proceedings, 2019. P. 46-56.
- Preprint Alexey Buzmakov, Daria Semenova, Maria Temirkaeva. The Comparison of Methods for Individual Treatment Effect Detection / Cornell University. Series Computer Science "arxiv.org". 2019. No. arXiv:1912.01443.
- Article Гордиенко А. С., Лозинская А. М., Тетерина Д. В., Шенкман (Попова) Е. А. Исследование зависимости потребления электроэнергии и температуры в России: региональный разрез // Известия РАН. Энергетика. 2019. № 1. С. 15-27. doi
- Preprint Ozhegov E. M., Teterina D. Ensemble method for censored demand prediction / NRU Higher School of Economics. Series EC "Economics". 2018. No. 200/EC/2018.
- Preprint Ozhegov E. M., Teterina D. Ensemble method for censored demand prediction / Cornell University. Series Computer Science "arxiv.org". 2018. No. arXiv:1810.09166.
Conferences
- 2022IX научная конференция «Соседи по науке» (Neighbors in Research) (Москва). Presentation: Оценка готовности платить: нейроэкономический подход
- 2019XX АПРЕЛЬСКАЯ МЕЖДУНАРОДНАЯ НАУЧНАЯ КОНФЕРЕНЦИЯ ПО ПРОБЛЕМАМ РАЗВИТИЯ ЭКОНОМИКИ И ОБЩЕСТВА (Москва). Presentation: Ensemble method for censored demand prediction
- Соседи по науке (Пермь). Presentation: Сравнение методов оценки индивидуального эффекта от воздействия
- Fifth International Workshop on Experimental Economics and Machine Learning (EEML 2019) (Пермь). Presentation: The Comparison of Methods for Individual treatment Effect Detection
- 2018The Fourth International Conference on Machine Learning, Optimization, and Data Science (Вольтерра). Presentation: Methods of Machine Learning for Censored Demand Prediction
- International Conference on Applied Research in Economics (Пермь). Presentation: Methods of Machine Learning for Censored Demand Prediction
- 2017Городская студенческая конференция "Математика в экономике" (Пермь). Presentation: Demand Estimation for Children Summer Camp
Series of workshops as part of the student seminar "Cooking up your first research"
At the end of December, researchers from the International Laboratory for the Economics of Intangible Assets held a series of workshops on academic writing “What-you-need-to know to write a Research Paper” for students, graduate students, research assistant and just everyone. Master classes were organized as part of the student seminar "Cooking up your first research".
IDLab Workshop
Daria Semenova, PhD student at the National Research University Higher School of Economics-Perm and IDLab employee, presented the study "Measuring effects of packaging on willingness-to-pay for chocolate: evidence from EEG experiment"
IDLab study image analysis with PyTorch
On June 20, 2022, the advanced training course "Python Programming for Image Analysis" began. As part of the course, IDLab members will learn machine learning methods that can be used for image analysis.
IDLab at the Neighbors in Research conference
IDLab researchers took part in the IX scientific conference "Neighbours in Research"
ID Lab ONLINE Workshop
Daria Semenova presented her Candidate of Science (PhD) thesis on Willingness to pay in the foodmarket: attributive VS neuroeconomic approaches. The thesis is supervised by Sofya Kulikova and Maria Molodchik