Maria Komarova Email & Phone Number

Yerevan, Am

Yerevan, Armenia

By communicating with clients and experts from related fields, I designed and developed services for machine learning, data processing, and CI/CD:- SaaS Platform with ML Models: Architected and developed an asynchronous SaaS platform providing ML model predictions via a secured API. Migrated the frontend to align with the new service. Technologies: FastAPI, PostgreSQL, RabbitMQ, Kafka, Redis, AWS.- Genomic Data Storage Service: Full ownership of a genomic data storage service. Established the service as an architectural and best-practice benchmark for other projects. Technologies: FastAPI, PostgreSQL, S3, SQLAlchemy, pytest, alembic.- ETL Pipeline for Genomic Data: Designed and optimized an ETL pipeline to enhance performance, reducing processing time by 3-4x through strategic use of threading and data processing libraries. Technologies: Luigi, pandas, S3.- CI/CD Template Engine: Developed a CI/CD template engine to streamline and automate processes for approximately 10 microservices, significantly reducing setup time to around 1 hour. Technologies: Go, Bash.

Yerevan, Armenia

I implemented data science solutions, developed, and deployed web services as well as ETL pipelines:- Migration to Kubernetes and CI/CD Setup: Migrated all microservices to Kubernetes, creating and optimizing CI/CD pipelines to streamline deployment. Technologies: Docker, Kubernetes, Helm, Concourse CI.- Cancer Treatment Prediction Pipeline: Contributed to a comprehensive pipeline for predicting optimal cancer treatments using genomic data. Technologies: Prefect, pandas.- Microservices for Genomic Pipeline: Developed and maintained microservices surrounding the genomic data pipeline, enhancing functionality and performance. Technologies: FastAPI, PostgreSQL, Celery.- Laboratory Data ETL: Designed and implemented an ETL pipeline for laboratory data processing, including database design based on business requirements. Technologies: Apache Airflow, SQLAlchemy, PostgreSQL.- Flow Cytometry Analysis Package: Developed a Python package for the analysis of flow cytometry data, facilitating the validation of ML models for immune cell classification. Technologies: pandas, xmltree.

I contributed to Brain-Computer Interface research with a focus on machine learning algorithms:- Brain-Computer Interface Development: Implemented preprocessing algorithms for EEG signals, such as ICA, feature extraction (Fast Fourier Transform, Wavelet Transform) and classification algorithms (SVM, KNN, etc.) for recognizing image categories based on brain activity. Technologies: numpy, scikit-learn, xgboost, PyTorch.- Desktop Application for BCI Developers: Contributed to the development of a desktop application for Brain-Computer Interface (BCI) researchers. Created a component for artifact removal using ICA. Technologies: PyQT, matplotlib.- Academic Contributions: Co-authored 3 scientific publications, advancing research in the field of Brain-Computer Interfaces. Presented results at conferences.

Master'S Degree, Biological And Medical Physics

Bachelor'S Degree, Applied Mathematics And Physics