About me
I am currently a Data Scientist in Appgate’s R&D department, leveraging my analytical skills, programming abilities, and knowledge in Machine & Deep learning to discover insights for the company’s cybersecurity products. Also I’m a professor in the data science master’s program at EIG business school. My background includes a master’s degree, research assistantships and published academic papers, demonstrating my research capabilities as well as a passion for advancing the field of computer science. I am motivated to continue pursuing my research interests through doctoral studies focused on tackling complex problems in computer science and developing innovative computational solutions.
Research Interests
My research interests center on advancing computer vision techniques and expanding their applications across disciplines. My experience includes the creation of vision-language models for sign language translation in video and also computer vision models for Biomedical challenges such as COVID-19 diagnosis or cardiac disease prediction. The full list of my research interests is:
- Vision-language domain.
- Biomedical applications.
- Graph Representation Learning.
Publications at a glance
Vision-language publications: Sign language recognition
- How important is motion in sign language translation?, IET Computer Vision, 2021.
- Understanding Motion in Sign Language: A New Structured Translation Dataset, ACCV, 2020.
- Towards on-line sign language recognition using cumulative SD-VLAD descriptors, CCC, 2018.
- A kinematic gesture representation based on shape difference VLAD for sign language recognition, ICCVG, 2018.
Biomedical imaging publications
- Kinematic motion representation in Cine-MRI to support cardiac disease classification, TCIV, 2022.
- Deep learning representations to support COVID-19 diagnosis on CT-slices, Biomédica, 2021.
- A Covid-19 Patient Severity Stratification using a 3D Convolutional Strategy on CT-Scans, ISBI, 2021.
- Regional multiscale motion representation for cardiac disease prediction, STSIVA, 2019.
Cybersecurity publications
- Phishing website detection using deep learning, In progress.