Ляна

Liana Lotarets
Mathematician
CONTACTS
+380 67 12 11 662 2 Telegram 2 GitHub 2
[открыть контакты](см. выше в блоке «контактная информация») 2 LinkedIn 2 Kharkiv, Ukraine

SUMMARY
A mathematician with knowledge of Python and Data Science. My strength lies in my diverse expertise across various
fields of mathematics. I aim to further develop my mathematical skills by collaborating with experienced professionals
and contributing to the company’s success.

HARD SKILLS
• Mathematics • Differential Equations • Numerical Analysis

• Python • Linear Algebra • Mathematical Statistics
• OOP • Mathematical Analysis • Probability Theory
• Analytic Geometry • Functional Analysis • Combinatorics
• Differential Geometry • Complex Analysis • Discrete Mathematics

SOFT SKILLS
• Lifelong Learning • Desire to learn • Helpfulness
• Task prioritising • Information seeking

LANGUAGES
English – intermediate Ukrainian – native Japanese – elementary

PUBLICATIONS
• LOTARETS, LIANA (2022) "Geodesics of fiberwise cigar soliton deformation of the Sasaki metric," Turkish Journal of Math-
ematics: Vol. 46: No. 1, Article 10. DOI 2
• LOTARETS, LIANA (2024) "Twisted Sasaki metric on the unit tangent bundle and harmonicity," Turkish Journal of Math-
ematics: Vol. 48: No. 2, Article 4. DOI 2
• Lotarets, L. (2024). A characteristic property of Sasakian manifolds. Proceedings of the International Geometry Center,
17(3), 218-231. DOI 2

WORK EXPERIENCE
Freelance, Math Tutor
2018 – Present
– Successfully assisted an entrant in preparing for master’s studies by providing foundational knowledge in nu-
merical methods, optimization methods, probability theory and statistics.
– Successfully assisted entrants in preparing for the bachelor’s degree entrance exam in mathematics.
National Research Foundation of Ukraine (NRFU), Grantees
2021 – 2022

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 – Published a scientific article with the results of research supported by the National Research Foundation of
Ukraine funded by the Ukrainian State budget in frames of project 2020.02/0096 “Operators in infinite-dimensional
spaces: the interplay between geometry, algebra and topology”.
Akhiezer Foundation, Grantees
2023 – 2024
– Published a scientific article with the results of research supported by the Akhiezer Foundation.

PROJECTS
MNIST classification + OOP, GitHub 2

Tools/Technologies: Python, OOP, Keras, Matplotlib, Scikit-learn, Deep Learning, CNN
Description: MNIST classification using OOP three models: Random Forest, Feed-Forward Neural Network, Con-
volutional Neural Network.
Achievements: All models performed excellently. Random Forest (accuracy 97%, size 137.51 MB) is not the best
choice, as it is less accurate and significantly larger than the other models. The Convolutional Neural Network
(accuracy 99%, size 10.4 MB) is a much better option compared to Random Forest. However, if model size is a
critical factor, the Feed-Forward Neural Network (accuracy 98%, size 5.39 MB) is also a good alternative.
Binary Prediction of Poisonous Mushrooms, kaggle 2
Tools/Technologies: Python, Pandas, Scikit-learn
Description: A Pet-project based on a Kaggle dataset from the competition Binary Prediction of Poisonous Mush-
rooms. The goal of this competition is to predict whether a mushroom is edible or poisonous based on its phys-
ical characteristics.
Achievements: The most challenging part of the task was data preprocessing, as the data was not pre-cleaned.
The model demonstrates high accuracy: Private Score is 0.98012, which means 98% accuracy.

Ukraine’s birth rate (1950–2019), GitHub 2
Tools/Technologies: Python, Pandas, Matplotlib
Description: Analysis of the table Birth Rate in Regions of Ukraine (1950–2019) from the website Population of
Ukraine 2.
Achievements: Local birth rates in the late 1990s and early 2000s were found to be the lowest during the period
from 1950 to 2019. Additionally, it can be concluded that right-bank regions generally have higher birth rates
than left-bank regions.

EDUCATION
V. N. Karazin Kharkiv National University
2015–2019, Bachelor’s degree, Mathematics
2019–2021, Master’s degree, Mathematics

IT School GoIT
June 2024 – January 2025, Data Scientist

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