Andrii Len added .md file 2025 (#2536)

* Andrii Len added 2025 .md file

* Andrii Len updated 2025 .md file

* Andrii .md file 2025 updated

* style: pre-commit fixes

* Andrii Len update

* Update Andrii Len

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: Andreylen

_fellows/2024/Andreylen.md

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+---
+layout: fellow
+pagetype: fellow
+shortname: Andreylen
+permalink: "/fellows/Andreylen.html"
+fellow-name: "Andrii Len"
+title: "Andrii Len - IRIS-HEP Fellow"
+active: true
+dates:
+  - start: 2022-06-27
+    end:   2022-09-18
+  - start: 2023-07-03
+    end:   2023-09-22
+  - start: 2024-06-03
+    end:   2024-08-21
+  - start: 2025-06-02
+    end:   2025-08-24
+photo: "/assets/images/team/fellows-2022/Andrii-Len.jpg"
+institution: "Taras Shevchenko National University of Kyiv"
+e-mail: "andrlen2002@gmail.com"
+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:
+      - "Ece Asilar (CERN)"
+    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"
+  - project_title: "Topological Rare Hadron Decay Tagging with DNN: Deep neural net topological tagger for rare hadron decay identification"
+    project_goal: >
+      One of the main challenges of this project will be to identify and build an
+      effective DNN architecture to train a new model that will not only match BDT
+      in performance but gives a significant improvement to the analysis sensitivity.
+    mentors:
+      - "Dmytro Kovalskyi (MIT)"
+    proposal: "/assets/pdf/fellows-2024/UKR010-proposal-Andrii-Len.pdf"
+  - project_title: "Mitigating the Impact of Simulation Mis-Modeling on DNN Training: Building Robust DNNs in the Presence of Detector Mis-Modeling"
+    project_goal: >
+      In this project, we will compare two methods to mitigate Simulation Mis-modeling
+      impact on training: First one is to exclude simulated data completely (use only
+      real data for training) and the second one is to modify loss function to include
+      penalty terms for mis-modeling. We will assess relative performance and identify
+      common trends of these approaches to find an optimal solution.
+    mentors:
+      - "Dmytro Kovalskyi (MIT)"
+    proposal: "/assets/pdf/fellows-2025/UKR005-proposal-Andrii-Len.pdf"
+presentations:
+  - title: "The usage of Deep Learning for QCD background estimation"
+    date: 2022-10-19
+    url: "https://indico.cern.ch/event/1199559/contributions/5097272/attachments/2531407/4355497/IRIS-Hep%20Andrii_Len_Final_Presentation.pdf"
+    meeting: "IRIS-HEP Fellows Presentations 2022"
+    meetingurl: "https://indico.cern.ch/event/1199559/"
+    recordingurl: "https://youtu.be/gEaqn7C9ipY"
+    focus-area: "ia"
+current_status: ""
+github-username: "Andreylen"
+---