My Research Interests
I am passionate about applying my engineering skills to solving real-world challenges in Neuroengineering. My focus is on Brain-Computer Interfaces (BCIs), specifically in the areas of rehabilitation, neurofeedback, and diagnostic applications.
In particular, I am studying neuromarkers of visual information integration for BCI applications, contributing to the development of more effective and user-friendly neurotechnologies. I am eager to push the boundaries of human-computer interaction through my research in neuroengineering and signal processing.
If you're interested in these topics, let's connect! You can learn more about the ingoing experiments we have on the website of the lab !
My Technical Skills
I have strong coding skills in Python, gained through various academic projects and internships. Additionally, I have experience using Matlab for signal processing and motion tracking with Inertial Measurement Units (IMUs). Check out my GitHub profile for more details.
My expertise extends to Machine Learning, with a focus on deep learning techniques. I am actively working to deepen my knowledge of BCI and EEG signal processing through my ongoing PhD research.
In addition, I am expanding my skills in UX/UI design and web development, with a special interest in improving user experience in neurotechnology applications. I am currently taking a Coursera course to further enhance these skills.
You can learn more about my projects and skills by checking my CV!
My Current Projects
PhD Research: Neuromarkers of Visual Information Integration for BCI
I am investigating EEG neuromarkers associated with visual information integration, focusing on improving Brain-Computer Interfaces (BCIs) for rehabilitation and neurofeedback applications.
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Experiment on Feedback and Starburst Reactive BCI
I am conducting an experiment to evaluate the effect of real-time feedback on user performance in Starburst reactive BCIs, an exciting frontier in enhancing BCI usability and user experience.
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Teaching Assistant and Private Tutor
I am assisting in practical classes for neuroengineering at ISAE-Supaero and teaching mathematics, physics, and computer science to students in preparatory classes and high school.
My Most Relevant Achieved Projects
Development of a Robust Reactive BCI (2024)
During my master's thesis at ISAE-Supaero, I developed features for the Starburst BCI, such as real-time performance evaluation and visualization tools, aimed at enhancing user experience.
EEG-Stroke (2024)
I worked on developing an intention of movement classification algorithm using EEG data, helping stroke patients regain control over their motor functions. The project also included the development of a user-friendly application for real-time classification.
Speaker at Neuroday Conference (2024)
I presented on Brain-Computer Interfaces and the latest research at ISAE-Supaero during the annual "Neuroday" conference, which brought together experts in neuroscience and BCI technology.
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fNIRS Artifacts of Motion (2023)
During my internship with Dr. Hasan Ayaz, I developed a Generative Adversarial Network (GAN) to model and recover missing fNIRS data, demonstrating its potential over traditional methods. The article is currently in progress.
IMU Upper-limb Motion Tracking (2022)
Developed an algorithm in Matlab to track upper-limb motion for post-stroke rehabilitation diagnostics. This project was published in a scientific journal.
Link to the paper I'm acknowledged in.