Isabella de Andrade

Researcher III, Samsung, Federal University of Pernambuco,  Brazil

November 2022 - Now

• I am participating in a project that is a collaboration between Samsung Brazil and the Federal University of Pernambuco related to smartwatch health applications

Undergraduate Research Intern, Federal Rural University of Pernambuco,  Brazil

September 2021 - June 2022

• I have participated in research for pedestrian tracking

• Firstly I contributed to the project by adding experiments using computer vision on a tracker that was already being developed using classic algorithms
  Note: this experience resulted in the publication "Generalizable Online 3D Pedestrian Tracking with Multiple Cameras" (VISAPP 2022)

• Then, I worked on another tracker using a Message Passing Neural Network architecture
  Note: this was the theme of my undergraduate thesis and resulted in the publication "Multi-Camera 3D Pedestrian Tracking Using Graph Neural Networks" (VISAPP 2023)

• The skills I improved here were Python, Pytorch, Pandas, Numpy, Anaconda, and Visual Studio 

A Study on the Influence of Sensors in Frequency and Time Domains on Context Recognition (Sensors 2023)

de Souza, P.; Silva, D.; de Andrade, I.; Dias, J.; Lima, J. P.; Teichrieb, V.; Quintino, J.P.; da Silva, F.Q. and Santos, A.L. (2023). A Study on the Influence of Sensors in Frequency and Time Domains on Context Recognition. Sensors, 23(12), p. 5756. DOI: 10.3390/s23125756.

Multi-Camera 3D Pedestrian Tracking Using Graph Neural Networks (VISAPP 2023)

de Andrade, I. and Lima, J. (2023). Multi-Camera 3D Pedestrian Tracking Using Graph Neural Networks. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-634-7; ISSN 2184-4321, pages 974-981. DOI: 10.5220/0011674700003417

Generalizable Online 3D Pedestrian Tracking with Multiple Cameras  (VISAPP 2022)

Lyra, V.; de Andrade, I.; Lima, J.; Roberto, R.; Figueiredo, L.; Teixeira, J.; Thomas, D.; Uchiyama, H. and Teichrieb, V. (2022). Generalizable Online 3D Pedestrian Tracking with Multiple Cameras. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-555-5, pages 820-827. DOI: 10.5220/0010842800003124

Azure AI Fundamentals (AI-900) - Microsoft Certificate, June 2022

Woman in AI - 30h Course, April - June 2022*

*In this program, I received mentorship from Microsoft employees to learn the topics covered in the Azure AI Fundamentals exam (AI-900).

Neural Networks and Deep Learning - Course on Coursera, August 2022**

**In this course I learned more about the math behind deep learning and also did programming exercises