Position: Data Analyst
Category: Data Science
English level: upper
Years of experience: 0


I am currently pursuing a Master's Degree in Biology with a specialization in Bioinformatics at Kyiv's National University of Shevchenko. While I don't have professional work experience yet, my strong passion lies in leveraging AI technology to make a positive impact on the world. Currently, I am focused on developing a novel neural network architecture that optimizes model size and accuracy more efficiently. My other pet projects include the development of a deep reinforcement learning framework for protein design. Pandas, Matplotlib and NumPy frameworks are integral to this project, enabling efficient data analysis, manipulation and visualisation. With Pandas, I organize and preprocess protein alignment tables, while NumPy facilitates fast numerical computations, that are later plotted in Matplotlib

During my Bachelor's degree, I gained valuable experience working with neural networks. Specifically, I developed a deep learning classifier using a dataset of microphotographs to differentiate between 24 distinct human chromosome types. I took responsibility for dataset preparation (using Numpy), data augmentation, and employed GPU acceleration and parallelization techniques to enhance learning efficiency.

Throughout the project, I explored various neural network architectures, including a single-layered perceptron-like model, a six-layered perceptron-like model, a CNN based on ResNet50v2, a custom-designed CNN, a vision transformer, and a mixed architecture combining attention and convolutional layers. I implemented these models using TensorFlow in Python. While three of the architectures were trained in the Google Colab environment, the others required the utilization of a cluster with eight GPUs, enabling faster training.

To ensure accurate evaluation, I divided the dataset into training, evaluation, and testing subsets using an 80:10:10 ratio. This allowed me to fine-tune architecture-related and optimizer-related hyperparameters, optimizing the models' performance.

I am eager to apply my theoretical knowledge, practical experience, and determination to contribute to projects that utilize AI technology for impactful outcomes. I am confident that my skills in neural networks, data preparation, and hyperparameter optimization will enable me to make significant contributions in the field.
I would prefer to engage with endeavors that align with my values and ethical principles. As such, I'm not inclined to contribute to companies that engage in predatory practices or profit from exploitation and bigotry. I believe in supporting organizations that prioritize fairness, social responsibility, and inclusivity. Additionally, as someone who values the importance of ethical AI, I seek to align myself with organizations that share this commitment to creating technology that is both innovative and conscientious.