Milena Trajanoska
Student, Machine Learning & Data Science enthusiast
Passionate about applied ML & DS research in real-life scenarios
Interested in healthcare and life sciences
Optimizing business processes through data-driven decisions
Passionate about applied ML & DS research in real-life scenarios
Interested in healthcare and life sciences
Optimizing business processes through data-driven decisions
Work Experience
Machine Learning & Back-End Engineer at Loka, Inc., Skopje, Macedonia
November 2021 – Present
Helping start-ups form Silicon Valley develop high-tech products and empowering
technological advancements. Developing Machine Learning and Deep Learning - based solutions
with great focus on NLP including transformer architectures, deep neural networks and
statistical methods.
Implementing full-scale infrastructures for Machine Learning applications using AWS
services, extensive focus on Amazon SageMaker. Implementing MLOps pipelines for model
parameter-tuning, model training and validation with metrics and artifacts versioning.
Technology stack: AWS, Python, TensorFlow / Keras, PyTorch, Sklearn, SQL
Part-time Student Researcher - Data Science at Macedonian Academy of Sciences and Arts, Skopje, Macedonia
August 2021 – PresentPart time student researcher in the field of Data Science, Machine Learning, and Deep Learning. Assessing macroeconomic issues of European countries, with special emphasis on the Republic of Macedonia. Contributing towards the improvement of institutional structures in my country of origin through implementing state-of-the-art analysis and modeling. The results from the analysis are used by the Economic Chamber of North Macedonia in their decision making process.
Technology stack: Python, TensorFlow / Keras, Sklearn, LaTeX
Education
Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Skopje, Macedonia
October 2018 – PresentHard-working undergraduate student, in my final year of studies. Very enthusiastic about the latest technological developments in the fields of AI and ML. Current top student of the entire generation with a GPA of 9.88.
Expected graduation date: October 2022.
Internships
Machine Learning Intern at Loka Inc., Skopje, Macedonia
July 2021 – October 2021
Implementing high-performing image classification Deep Learning models.
Utilizing transfer learning for state-of-the-art DL models such as MobileNetV2 and VGG16.
Leveraging neural network ensemble methods including: majority voting, Bayesian weighted
averaging and integrated model stacking.
Developing mobile application using Google's Flutter Framework and developing back end API
using Python with the Flask Framework.
Creating complete model pipeline for incremental re-training and deployment using Amazon
SageMaker.
Technology stack: Python, Keras, Tensorflow, Flutter, Flask, Amazon SageMaker.
Software Engineer Intern at Netcetera DOOEL, Skopje, North Macedonia
August 2020 – October 2020
Implementing new features for a micro-services platform aiming to empower actions towards
sustainable environmental development, Pulse Eco.
Unit testing the services layer and manual testing of the user interface.
Bug fixing and security improvements. Implementing smart internationalization on two
languages: English and Macedonian.
Technology stack: Java Spring Boot, Maven, JUnit, Mockito, Git, JavaScript, Docker,
JQuery, CSS, D3.js
Scientific Articles and Projects
Dietary, comorbidity, and geo-economic data fusion for explainable COVID-19 mortality prediction
Soon to be published in the journal Expert Systems with Applications. The Impact Factor of this journal is 6.954, ranking it 24 out of 273 in Engineering, Electrical & Electronic.
More details about scientific articles upon request.
FedCSIS 2022 Challenge: Predicting the Costs of Forwarding Contracts
Ranked 10th out of 135 teams from 24 countries around the world.
Basic Movie Recommendation System
Comparison of the performance of vanilla matrix factorization for collaborative filtering and content-boosted collaborative filtering, including embeddings from movie plots generated using TF-IDF.
Recommendation System for the MovieLens 100K dataset based on matrix factorization techniques for collaborative filtering.
Automobile and real-estate price estimation
Web-crawler architecture
Results for the housing price assessment
Semantic Image Segmentation
Basic image segmentation of the Oxford pets benchmark dataset.
Using convolutional neural networks with a U-net architecture for producing segmentation maps.
Example result:
