Daniel Silva
@danielsilva
Deep Learning enthusiast with a passion for healthcare.
What I'm looking for
I'm Daniel José Barros Silva, a driven and motivated individual with a strong background in Bioengineering and a passion for Deep Learning, particularly in the healthcare sector. With a solid foundation in Computer Vision and experience in developing model architectures and training procedures, I'm committed to advancing my skills and knowledge in this field.
Throughout my academic and professional journey, I've had the opportunity to work on various projects and internships, including developing natural language processing and Interpretable AI techniques, fine-tuning algorithms for edges and breast contour detection, and generating clinical reports for Interpretable AI using X-Rays. I'm excited to continue exploring the applications of Deep Learning in healthcare and contributing to innovative projects that make a meaningful impact.
In addition to my technical skills, I'm a team player with excellent problem-solving abilities and a strong work ethic. I'm always looking to stay up-to-date with the latest breakthroughs and advances in AI and Neuroscience, and I'm excited to collaborate with like-minded individuals who share my passion for innovation and improvement.
Experience
Work history, roles, and key accomplishments
Master Thesis Intern
INESC TEC / Netherlands Cancer Institute
Feb 2023 - Sep 2023 (7 months)
Developed model architectures and training procedures inspired by Disentanglement Representation Learning to improve generalizability in Chest X-ray Multi-Center Data.
Intern
INESC TEC / Champalimaud Foundation
Sep 2022 - Dec 2022 (3 months)
Fine-tuning of algorithms for edges and breast contour detection, for the aesthetic evaluation of Breast Cancer Conservative Treatment.
Intern
Faculty of Engineering INESC TEC
Feb 2022 - Sep 2022 (7 months)
Developed natural language processing and Interpretable AI techniques for generating Clinical Reports for Interpretable AI Education using X-Rays.
Intern
INESC TEC
Mar 2021 - Jul 2021 (4 months)
Learned and developed neuronal networks in Pytorch for Interpretable Machine Learning for Mammography Screening.
Education
Degrees, certifications, and relevant coursework
Daniel hasn't added their education
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Location
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