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* Merging changes to existing Fellows md file ofr Andrii Len * Deleted * fixing dates --------- Co-authored-by: Rob Tuck <[email protected]>
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title: Andrii Len - IRIS-HEP Fellow | ||
active: True | ||
dates: | ||
start: 2022-06-27 | ||
- start: 2022-06-27 | ||
end: 2022-09-18 | ||
- start: 2023-07-03 | ||
end: 2023-09-22 | ||
photo: /assets/images/team/fellows-2022/Andrii-Len.jpg | ||
institution: Taras Shevchenko National University of Kyiv | ||
e-mail: [email protected] | ||
project_title: The usage of Deep Learning for QCD background estimation | ||
project_goal: > | ||
projects: | ||
- project_title: The usage of Deep Learning for QCD background estimation | ||
project_goal: > | ||
The focus of the present project is to find optimal deep learning models to be used for the separation of signal and background events. | ||
mentors: | ||
mentors: | ||
- Ece Asilar (CERN) | ||
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proposal: /assets/pdf/fellows-2022/211-proposal-Andrii-Len.pdf | ||
proposal: /assets/pdf/fellows-2022/211-proposal-Andrii-Len.pdf | ||
- project_title: Predict CMS data popularity to improve its availability for physics analysis | ||
project_goal: > | ||
The focus of the project is to aggregate and extract data usage information, find data's features and optimal Machine Learning models to predict the probability that a dataset will be accessed in the next month. | ||
mentors: | ||
- Dmytro Kovalskyi, Rahul Chauhan, Hasan Ozturk | ||
proposal: /assets/pdf/fellows-2023/U009-proposal-Andrii-Len.pdf | ||
presentations: | ||
- title: The usage of Deep Learning for QCD background estimation | ||
date: 2022-10-19 | ||
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