Paulina Alejandra Moran Mendez

Contributing in the definition and creation of the company's categories for comment classification by applying linguistic concepts. Additionally, building and updating automatic classifiers using regular expressions and python scripts. As well as creating python scripts to automate simple tasks.

Trained and tested statistical language models, voice ABNF grammars and Intent detection models for Open Question solutions for a high-impact project in the US market. Worked actively with clients analyzing feedback to gain a deeper understanding of their requirements and preferences, annotating data, fixing models and elevating project outcomes.

Assisted in management and classification of the clients social media interactions with their users by analyzing comments, annotating data and classifying them by categories by taking into account the categories concepts, user intent and the social context.

Used and helped build a database to research, gather, analyze and present data to improve the attention, communication and resolution of patients' problems. As well as designing a proposal for the creation of a specialized English course for nurses by creating a curriculum.

Designed tool based on linguistic elements that allowed the identification of offensiveness in texts in order to annotate a dataset used for training of classification models. Resulted in re-validation of the labeling of the corpus belonging to the Language Technologies laboratory of INAOE. This led to a major improvement by increasing the kappa agreement from 58% to 92%

Created a collaborative project alongside Korean students directed to high school students with the aim of expanding their knowledge of different cultures.

Organized by the Korean National Commission for UNESCO. Participated as a representative of Mexico by giving a seminar to students at a Korean secondary school and also created the contents and material of the seminar.