Mr. Hossein Dini | Computational Neuroscience | Best Researcher Award

Mr. Hossein Dini | Computational Neuroscience | Best Researcher Award

Mr. Hossein Dini, Aalborg University, Denmark

Ā Mr. Hossein Dini is a distinguished neuroscientist with over seven years of extensive experience in EEG and fMRI data analysis. Their career is marked by significant collaborations with leading industries such as Neurons Inc. and g.techmedical, as well as prestigious academic institutions like Georgia State University, USA. Specializing in brain-related disorders, including ADHD, epilepsy, and psychiatric conditions, Dr. [Name] has developed a strong reputation for their ability to analyze complex data and apply programming skills in statistics, MATLAB, Python, and AI/machine learning to their research.Dr. Hossein Dini obtained their Bachelor’s degree in Electrical Engineering from [University], Iran, where they innovatively designed and implemented a solar panel converter. This early work laid the foundation for their future endeavors in biomedical engineering. Pursuing a Master of Science in Biomedical Engineering, they focused on EEG functional connectivity analysis in children with ADHD, applying advanced techniques such as Functional Network Connectivity (FNC) and graph theoretical features to EEG data. This research was pivotal in advancing understanding of facial emotion recognition in ADHD children.

Professional Profile

Scopus

 

šŸŽ“ Education šŸŽ“

  • Ph.D. in Neuroscience, Aalborg University, Denmark (2020 – Present)
    • Thesis: EEG analysis for narrative cognition and decision-making in mixed reality systems.
  • M.Sc. in Biomedical Engineering, Iran (2016 – 2019)
    • Thesis: EEG functional connectivity analysis in children with ADHD during facial emotion recognition tasks.
  • B.Sc. in Electrical Engineering, Iran (2011 – 2016)
    • Thesis: Design and implementation of a solar panel converter.

šŸ’¼ Employment šŸ’¼

  • Marie Skłodowska-Curie Ph.D., Aalborg University, Denmark (2021 – Present)
    • Focus: Predictive deep-learning models, automation for EEG data processing, statistical evaluations, and analysis of human physiological responses in virtual reality environments.
  • Freelancer, Sharif PR, Iran (2016 – 2019)
    • Focus: Machine learning, signal processing, and statistical analysis.

šŸ† Conference Publications šŸ†

  • EEG Power Spectral Density Investigation in Children with ADHD (2019)
    • Oral presentation at the International Human Brain Mapping Conference
  • EEG Theta and ERP Responses to Congruent vs. Incongruent Brands (2021)
    • Poster presentation at the Society for Neuroscience Conference
  • Dynamic Functional Connectivity Predicts Treatment Response to Electroconvulsive Therapy in Major Depressive Disorder (2021)
    • Oral presentation at Biological Psychiatry Conference
  • Default Mode Network Dynamic Functional Network Connectivity Predicts Psychotic Symptom Severity (2022)
    • Presentation at the IEEE Annual International Conference
  • Prediction of Sleep Quality Scores Using Dynamic Functional Network Connectivity (2022)
    • Presentation at the Alzheimer’s Association International Conference
  • Picture Classification into Different Levels of Narrativity Using Subconscious Processes and Behavioral Data: An EEG Study (2022)
    • Published in proceedings of NeuroIS Retreat

šŸŒŸ Personal Interests šŸŒŸ

I enjoy traveling, playing sports, listening to music, reading, and astronomical observation. šŸ€šŸŽ¶šŸ“ššŸ”­

 

Publications Notes:šŸ“„

EEG theta and N400 responses to congruent versus incongruent brand logos

Digital narratives in extended realities

Default mode network dynamic functional network connectivity predicts psychotic symptom severity

Dynamic Functional Connectivity Predicts Treatment Response to Electroconvulsive Therapy in Major Depressive Disorder

Narrative Cognition in Mixed Reality Systems: Towards an Empirical Framework