Position: NLP Researcher/Engineer
Category: Data Science
English level: fluent
Years of experience: 1.5

1) Being selected as a participant in the WVU Neuroscience Undergraduate Research Opportunity in the summer of 2022. Has completed a research project by participating in didactic classes, research lab meetings, and presentations with the total equivalent of 6 credit hours.

2) Presented my research on the topic "An Effective Method for Learning Ukrainian Word Vectors" ContribuLing 2022 conference;

3) March AI Hackathon 2021: our team got to the final round of the hackathon;

Coursera Certified courses:
- NLP with Attention Models
- NLP with Classification and Vector Spaces
- Applied Social Network Analysis in Python
- Intro to Data Science
- Applied Text Mining in Python
1. Junior NLP Researcher ‒ Ukrainian Catholic University ML Lab, Jun 2021 - Dec 2022
• researched the topic of learning word embeddings for Ukrainian;
• published the paper and presented it at UNLP&EACL2023;
• led the UCU ML Lab Medium blog, writing short summary articles on NLP topics such as GEC and Fact-checking from the Master thesis of UCU students.

2. NLP engineer / Data Scientist, Jul 2021 - Nov 2022
• improved morphological parsing pipeline;
• developed rule-based methods for phrase matching;
• evaluated speech recognition models for Ukrainian, Polish, German, and Czech
• conducted research on a variety of NLP tasks;
• worked with large corpora and different languages;

3. Research Intern at WVU Rockefeller Neuroscience Institute, Jun 2022 - Jul 2022
 • Neuroscience Undergraduate Research Opportunity (NURO) participant.
 • researched the topic "Decoding Neural Control Signals from High-Density Electromyography."
• presented a poster at Summer Undergraduate Research Symposium, West Virginia University Morgantown, United States, June 2022. 

4. Python Instructor, Jul 2019 - Aug 2020
 • prepared and presented lectures for students in the Intro to Python course;
 • evaluated home assignments and final projects;

Other projects:
1) Accent classification for native and non-native English speakers: processed raw human speech, extracted features with the MFCC method, implemented a simple CNN model, and got 98% accuracy on the test set.

2) Testing Topic Modeling techniques on Ukrainian corpus UA-GEC: utilized available topic modeling methods - LSA, pLSA, LDA - on Ukrainian corpora using the Gensim library and evaluated it with the help of coherence measure.

3) Developed an Intelligent Health AI Assistant to determine the diagnosis and the doctor based on specified symptoms during the March AI Hackathon.

4) Words prediction system based on N-gram Language Model: implement language model for parallel n-gram extraction from large text corpora (~40Gb) in C++. Develop GUI application for its usage.
I am interested in NLP and Computational Linguistics, Research positions. I want to dedicate my future career to research and work in the science sector.