Iury Rogerio S.

Key Skills

Software

Other

Top Subject Matter

Community programs data curation (education-related)

Facial expression / emotion recognition dataset generation and model testing

Top Data Types

Text

Computer Code Programming

Top Task Types

Data Collection

Emotion Recognition

Freelancer Overview

University Intern, Federal University of Paraíba (University Intern). Brings 16+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Candidate Doctor of Philosophy, University of Coimbra (2020) and Master of Information Technology, Federal University of Paraíba (2019). AI training focuses on data types such as Text, Computer Code, and programming, as well as labeling workflows including Data Collection and Emotion Recognition.

Labeling Experience

Outlier Projects

AudioText Generation

Diverse range of projects for Outlier, data annotation, image to text, audio to text, translation and human voice recognition.

2025 - Present

University Intern, Federal University of Paraíba (University Intern)

TextData Collection

Updated community-program datasets by collecting and maintaining teacher and student information and related records. Identified inconsistencies across teacher and student fields to improve dataset quality and downstream usability. Verified and validated resource requests tied to financing new community research activities. • Cleaned and reconciled dataset entries • Performed consistency checks on entity attributes • Supported research readiness through data verification • Tracked and maintained updated records for community programs

2016 - 2016

Summer Internship, ELTE Neural Information Processing Group (NPIG)

OtherEmotion Recognition

Developed a genetic algorithm to generate face patterns aligned with FACS-based feature representations. Implemented a face generator to create an emotion-face dataset for training and evaluation. Tested an emotion recognition system to improve emotion detection performance. • Built synthetic data generation pipeline • Generated an emotion-focused dataset for model development • Implemented and experimented with a genetic algorithm for pattern generation • Evaluated emotion recognition outcomes to refine detection

2014 - 2014

Education

Work History