Davide Cantavenera

Hi, I'm Davide Cantavenera.

Assistant Researcher in Visual Perception & Cognitive Neuroscience.

My research interests include behavioral experiments, non-invasive brain stimulation, and neuroimaging techniques to study the neural mechanisms of visual perception and how the brain constructs perceptual experience from sensory input. I am also interested in computational approaches to model cognitive processes.

University of Padua, Department of General Psychology
Master's Student

Curriculum Vitae

Experience

Research Internship — Department of General Psychology

Conducting visual neuroscience research within the laboratories of Prof. Gianluca Campana and Prof. Luca Battaglini, contributing across the full research pipeline from study conceptualization to manuscript preparation:

  • Designing and pre-registering psychophysical experiments on visual illusions (e.g., Flash Drag Effect), including participant recruitment, sample-size justification, and coordinating successive groups of research interns.
  • Implementing non-invasive brain stimulation protocols (tRNS, tACS, tDCS) targeting primary visual cortex (V1) and motion-sensitive area MT/V5.
  • Developing experimental scripts in jsPsych and PsychoPy, including adaptive staircase procedures, stimulus generation pipelines, and online phase-tracking routines.
  • Participating in the tACS Challenge Project, a multi-lab international initiative investigating the causal role of neural oscillations in visual perception.
  • Performing frequentist and Bayesian statistical analyses in Python, R, and MATLAB, applying computational modelling, and contributing to manuscript preparation across concurrent projects.

AI Evaluation Internship — R-TREE TECHNOLOGIES S.R.L.

Applied systematic evaluation methodologies to assess the output quality of Large Language Models (LLMs), bridging cognitive science principles with AI quality assurance:

  • Developed and applied structured annotation rubrics to evaluate contextual coherence, factual accuracy, and reasoning quality of LLM-generated content.
  • Conducted comparative analyses across models, synthesizing quantitative performance metrics into technical reports for the development team.

Education

M.Sc. in Applied Cognitive Psychology

Advanced coursework in attention, memory, executive functions, and decision-making, with emphasis on experimental methodology and human–technology interaction. Training encompasses psychometric assessment, multivariate statistics, neuroimaging fundamentals, and the design of applied interventions grounded in cognitive models. Thesis research focused on non-invasive brain stimulation and visual perception.

Postgraduate Diploma in Data Science & Data Management

Intensive program covering the methodological and computational foundations of data science: statistical inference, supervised and unsupervised machine learning, natural language processing, big-data architectures, and interactive data visualization. Applied these methods to real-world datasets through project-based coursework, developing end-to-end analytical pipelines from data wrangling to interpretive reporting.

Specialization Course in Tutoring for Learning

Evidence-based training in cognitive psychology applied to education, covering working memory, attentional control, metacognition, and self-regulated learning. Acquired competencies in diagnosing learning difficulties, designing individualized tutoring interventions, and translating cognitive-science findings into practical pedagogical strategies.

B.Sc. in Cognitive and Psychobiological Sciences

Foundational training in the biological and cognitive bases of behavior: sensory physiology, visual and auditory perception, memory systems, language processing, psychometrics, and developmental psychology. Coursework in neuroscience, statistics, and research methods provided the methodological grounding for subsequent specialization in experimental cognitive neuroscience.

Skills & Competencies

Programming & Data Analysis

PythonAdvanced
RAdvanced
MATLABIntermediate
Data Visualization (ggplot2, matplotlib, seaborn)Advanced
SQL & Data Wrangling (pandas, tidyverse)Intermediate

Experimental & Neurostimulation Tools

PsychoPyAdvanced
jsPsychAdvanced
tES Protocols (tRNS, tACS, tDCS)Advanced
OpenSesame / PavloviaIntermediate
JASP / jamoviIntermediate

AI & Machine Learning

Generative AI / LLM Prompting & EvaluationIntermediate
scikit-learn / ML PipelinesIntermediate
NLP & Text AnalyticsBeginner

Web & Dev Tools

Git & GitHubIntermediate
HTML / CSS / JavaScriptIntermediate
LaTeX & MarkdownIntermediate
Jupyter NotebooksAdvanced

Research Competencies

Experimental Design & Methodology

Within- and between-subjects psychophysical paradigms, power analysis, counterbalancing, and pre-registration of hypotheses.

Behavioral & Psychophysical Assessment

Adaptive staircase, signal-detection tasks, response accuracy, reaction times, and perceptual threshold estimation.

Non-Invasive Brain Stimulation

tRNS, tACS, and tDCS protocols targeting V1 and MT/V5, including electrode montage, safety procedures, and sham conditions.

Data Science & Statistical Inference

Frequentist and Bayesian frameworks, mixed-effects modeling, and end-to-end data visualization pipelines in Python and R.

Scientific Writing & Communication

Research manuscripts following APA guidelines, conference presentations, poster design, and peer-review contributions.

Research Ethics & Compliance

Ethical review procedures, informed consent, GDPR-compliant data management, and open-science practices.

Intern Supervision & Team Collaboration

Training and coordinating successive groups of research interns across multiple semesters of data collection, and working effectively in lab teams and multi-lab international research environments.

Computational Modelling

Building and testing computational models of cognitive processes and brain stimulation effects using Python and MATLAB.

Languages

IT

Italian

Native

Born and raised

EN

English

C1 - Advanced

15 months in Florida

ES

Spanish

B2 - Upper Intermediate

3 months in Andalusia

Download CV

Research Projects

Flash Drag Effect - V5/MT & V1 Motion Integration

tRNS V1 Bayesian

tRNS on V1 and Flash Drag Effect

Investigating how transcranial Random Noise Stimulation on V1 reduces the Flash Drag Effect through stochastic resonance, enhancing signal detection in noisy transient stimuli.

Design Data Collection Analysis Writing
View Animated Project
TMS V5/MT Timing

TMS Disruption on V1/MT and FDE

Using TMS to disrupt V1 and MT at different time windows to test Bayesian correction mechanisms: V1 disruption increases FDE, MT disruption decreases it by blocking motion priors.

Design Data Collection Analysis Writing
View Animated Project
tACS Alpha Oscillations

tACS Entrainment and FDE Dynamics

Alpha-band (10Hz) tACS entrainment reveals opposite phase-dependent effects: MT stimulation peaks reduce FDE (inhibiting correction), while V1 stimulation peaks increase FDE (inhibiting detection).

Design Data Collection Analysis Writing
View Animated Project

Publications

  • Complementary Visual Assessment: Validation of a High-Precision Eye-Tracking Kinetic Perimetry in the Evaluation of Visual Field Deficits in Hemianopia

    Oletto CM, Costalunga F, Altieri E, Pugliese C, Semenzato L, Errigo S, Cantavenera D, Battaglini L

    Restorative Neurology and Neuroscience

    Design Data Collection Analysis Writing In Review Publication
  • Entrainment of Perceptually Relevant Brain Oscillations in Visual Contour Integration: Evidence from a Transcranial Alternating Current Stimulation Study

    Contemori G, Di Dona G, Musa M, Rampado L, Oletto CM, Cantavenera D, Ardelean D, Ronconi L, Battaglini L, Bertamini M

    TBD

    Design Data Collection Analysis Writing In Review Publication
  • The Effects of Transcranial Random Noise Stimulation in an Orientation Discrimination Task

    Roccato M, Cantavenera D, Pavan A, Campana G

    TBD

    Design Data Collection Analysis Writing In Review Publication
  • TMS Experiment on Visuo-Spatial Attention and Inhibition

    Moret B, Cantavenera D, Campana G

    TBD

    Design Data Collection Analysis Writing In Review Publication
  • Computational Neuroscience Project on Noise Signals and Artificial Neurons

    Cantavenera D, Roccato M, Battaglini L

    Signals

    Design Data Collection Analysis Writing In Review Publication
  • Zoom Out Effect & Mental Imagery in Spatial Perception

    Roccato M, Cantavenera D, Campana G

    TBD

    Design Data Collection Analysis Writing In Review Publication

Code & Repositories

Check out my open source contributions and research code on GitHub.

This repository hosts my personal landing page, showcasing my CV, publications, research interests, and personal reflections. Built to share my work and ideas in Visual Perception & Cognitive Neuroscience, and to provide an easy way to get in touch.

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A machine learning assignment developed for the course Machine Learning for Brain and Cognition - University of Padua. Standard data analysis and machine learning pipeline to a real-world water quality dataset, including exploratory data analysis, preprocessing, model training, evaluation, and critical interpretation of results.

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Research Interests

A curated collection of papers that inspire my work, categorized by topic.

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Blog

Thoughts on research, code, and caffeine.

  • Welcome to My Research Blog

    Introducing my new academic website and blog, where I'll share insights on visual perception, cognitive neuroscience, and the intersection of human and artificial intelligence.

    Read more