About Me
Photo Caption: Following trends on Social Media, I explained myself to ChatGPT and asked to describe me as a photo, this is the result.
As a Marie Skłodowska-Curie fellow at the Department of General Psychology, University of Padua, my primary research focuses on visual processing speed using cutting-edge technologies such as eye-tracking and EEG. I am particularly interested in investigating neural activity during perceptual learning. My research encompasses areas such as visual attention, visual cognition, and visual search, with a significant focus on attention mechanisms. I conduct various experiments, including psychophysical training aimed at improving visual processing speed.
I am an avid user of scientific coding, particularly in Python and Java, and I have developed a range of efficient codes and experiments. I have a strong interest in statistical and mathematical modeling, and I am currently working on developing new models to enhance eye-tracking technology and mathematical models of vision.
In addition, I have initiated a non-resident collaboration with the University of Harvard at the Visual Attention Lab under the guidance of Jeremy Wolfe, where I will be joining them in February 2025 for a six-month research visit.
My career goal is to become an academic professor, and I continuously strive to enhance my skills. Previously, I conducted research on emotions, particularly in the context of COVID-19. My experience encompasses teaching, laboratory management, data collection, and data analysis. As a hobby, I enjoy coding, designing experiments, and conducting analyses.
If I were a mathmatical Model?!
If I were a mathematical model, I would describe myself as:
$$R(t) = \alpha \cdot V(t) + \beta \cdot C(t) + \gamma \cdot S(t) + \delta \cdot E(t)$$
Where:
– \( V(t) \): Represents my research in visual processing and cognition, encompassing psychophysical experiments, neurocognitive studies, and statistical modeling.
– \( C(t) \): Reflects my expertise in scientific coding and algorithm development, primarily in Python and Java.
– \( S(t) \): Captures my collaborative endeavors, such as my Marie Skłodowska-Curie fellowship, my research at the University of Padua, and my upcoming collaboration with Harvard.
– \( E(t) \): Encompasses my teaching, laboratory management, and educational initiatives.
Each component evolves over time, \( t \), and the weights \( \alpha, \beta, \gamma, \delta \) signify the relative importance or time investment in these areas.
It would be better if I explain more that:
– Visual Processing and Cognition Research (\( V(t) \)): \[
V(t) = \int_{t_0}^{t} f_{\text{psychophysical}}(x) + f_{\text{neurocognitive}}(x) + f_{\text{statistical modeling}}(x) \, dx
\]
– Coding and Innovation (\( C(t) \)): \[
C(t) = \sum_{i=1}^{n} c_{\text{python}}^i + c_{\text{java}}^i
\]
– Scientific Collaborations (\( S(t) \)): \[
S(t) = \text{Marie Curie}(t) + \text{UniPd}(t) + \text{Harvard}(t)
\]
– Education and Teaching (\( E(t) \)): \[
E(t) = \int_{t_0}^{t} g_{\text{teaching}}(x) + g_{\text{management}}(x) \, dx
\]
This model encapsulates my dynamic and multifaceted academic journey, growing steadily as \( t \) progresses.