Prof. Fatma Zahra Sayadi | Neuro-AI Awards | Women Researcher Award

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Prof. Fatma Zahra Sayadi | Neuro-AI Awards | Women Researcher Award

Prof. Fatma Zahra Sayadi, Ecole Nationale d’Ingenieur de Sousse (ENISO)/ laboratoire Noccs, Tunisia

Fatma Zahra Sayadi is an Associate Professor specializing in Electronics and Microelectronics at the National Engineering School of Sousse (ENISO) in Tunisia. With a diverse academic background spanning from electrical engineering to digital innovation, she holds a Doctor of Engineering qualification and has over 25 years of experience in academia. Sayadi’s research interests include embedded systems, video processing, FPGA-based design, signal processing, image processing, and computer engineering, with notable contributions in intelligent pattern recognition and deep learning for medical applications. She has supervised numerous doctoral and master’s theses and has an extensive publication record, including journal papers, conference presentations, and book chapters. Additionally, Sayadi is actively involved in organizing international scientific events and serves on various scientific committees, reflecting her commitment to advancing knowledge and fostering innovation in her field.

Professional Profile:

Google Scholar

👩‍🎓 Education:

Fatma El Zahra Sayadi pursued her academic journey in Tunisia, culminating in several notable achievements. In 2006, she completed her Ph.D. in Physics with a specialization in Electronics from the Faculty of Sciences of Monastir. Her research during this period laid the foundation for her future contributions to the field. Subsequently, in 2018, she attained her Habilitation à diriger la Recherches (HDR) from the same institution, further solidifying her expertise and paving the way for her to supervise research. This significant milestone marked her ability to guide and mentor aspiring researchers in her field. Building upon her academic accomplishments, Fatma continued her pursuit of knowledge and professional development. In 2020, she obtained a Certificate of Complementary Education (CEC) from the Faculty of Medicine of Sousse. This certification reflected her commitment to staying abreast of advancements in pedagogical and digital innovation, enhancing her teaching methodologies and academic contributions. Through her dedication to continuous learning and research excellence, Fatma El Zahra Sayadi has established herself as a respected figure in the realm of electronics and microelectronics.

🏆 Awards:

In 2023, Fatma El Zahra Sayadi was honored with the prestigious Best Research Proposal Award at the 4th Forum for Women in Research, hosted by the University of Sharjah. This accolade stands as a testament to her outstanding contributions and innovative ideas in the field of electronics and microelectronics. Her research proposal showcased her ability to address pressing issues and push the boundaries of knowledge within her discipline. This recognition not only underscores her academic prowess but also highlights her dedication to advancing research and empowering women in STEM fields. By receiving this esteemed award, Fatma further solidified her reputation as a trailblazer and role model in the academic community.

🔍 Research Activities:

Fatma El Zahra Sayadi’s impact on the academic community is reflected in her impressive scholarly metrics and contributions. With an h-index of 14 and 575 citations on Google Scholar, she has demonstrated the influence and reach of her research endeavors. Her work has been disseminated widely, with 35 journal papers and 36 conference papers enriching the scholarly discourse in electronics and microelectronics. Additionally, Fatma has contributed significantly to the academic literature through her involvement in six chapters in edited scientific books, providing valuable insights to readers in her field.Beyond her own research output, Fatma has played a crucial role in nurturing the next generation of scholars. Having supervised seven Ph.D. theses and eight master theses, she has shared her expertise and guidance with emerging researchers, facilitating the creation of new knowledge and advancing the frontiers of science. Through her prolific scholarship and dedication to mentorship, Fatma El Zahra Sayadi continues to leave a lasting impact on the academic landscape.

Publication Top Notes:

  1. Optimized parallel implementation of face detection based on GPU component
    • Published: 2015 in Microprocessors and Microsystems
    • Cited by: 36
  2. Optimisation of HEVC motion estimation exploiting SAD and SSD GPU‐based implementation
    • Published: 2018 in IET Image Processing
    • Cited by: 30
  3. Harris corner detection on a NUMA manycore
    • Published: 2018 in Future Generation Computer Systems
    • Cited by: 37
  4. Fast CU partition-based machine learning approach for reducing HEVC complexity
    • Published: 2020 in Journal of Real-Time Image Processing
    • Cited by: 45
  5. CNN-SVM learning approach based human activity recognition
    • Published: 2020 in Image and Signal Processing: 9th International Conference, ICISP 2020
    • Cited by: 58

 

 

 

Prof. Camillo Porcaro | BCI

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Prof. Camillo Porcaro : Leading Researcher in BCI

Prof. Camillo Porcaro, Department of Neuroscience (DNS), Italy

🎉 Congratulations, Prof. Camillo Porcaro! 

🏆 On behalf of ScienceFather, we celebrate your remarkable achievement in winning the prestigious Best Researcher Award! Your dedication, innovative research, and scholarly contributions have left an indelible mark in your field. 🌟 Your commitment to advancing knowledge and pushing the boundaries of research is truly commendable. Here’s to your continued success in shaping the future of academia and making invaluable contributions to your field.

🧠 Dr. Camillo Porcaro is a passionate computational neuroscientist 🤖 with expertise in extracting insights from non-invasive brain activity measures. He earned his PhD with honors in ‘Functional Neuroimaging’ in 2008 at ITAB, University of Chieti, Italy 🎓. As a Postdoctoral Fellow at the University of Birmingham, he delved into simultaneous EEG/fMRI research 🧑‍🔬. In 2011, he secured an independent research position at the Institute of Neuroscience, Newcastle University 🏴󠁧󠁢󠁥󠁮󠁧󠁿.

Professional Profiles:

.   Google Scholar

.   ORCID

.   Scopus

.   Loop Frontiers

🎓 Education:
  • Ph.D. (2004-2008):
    • Title: “Functional Neuroimaging: from cells to systems”
    • Institution: Institute for Advanced Biomedical Technologies (ITAB), Chieti University, Italy
    • Honours: With honors
    • Thesis Focus: “Development of Tools to Estimate Functional Connectivity among Cerebral Sensorimotor Sources”
  • Master II Level (2001-2004):
    • Degree: “Bank, Insurance and Finance Management”
    • Institution: Faculty of Economics, University of Rome “La Sapienza”, Italy
    • Thesis: “Applying Independent Component Analysis to Factor Model in Finance”
  • Ms Computer Science (1995-2001):
    • Degree: Computer Science
    • Institution: Faculty of Science, Mathematics, Physics and Natural, University of Rome “La Sapienza”, Italy
    • Collaboration: ISTC-National Research Council (CNR) at the Fatebenefratelli Hospital (Isola Tiberina, Rome, Italy)
    • Dissertation: Coherence analysis of bio-electrical signals

🔬📚 Academic journey spanning neuroscience, finance, and computer science, showcasing a diverse skill set and expertise.

🏆 Awards & Honours:

2022:

  • 🥇 Best PhD Contribution – IEEE MetroXRAINE:
    • Title: “Human-in-the-Loop Approach for Enhanced Mobile Robot Navigation.”
    • Authors: K. Omer, F. Ferracuti, A. Freddi, S. Iarlori, A. Monteriù, and C. Porcaro.
    • Read more

2021:

  • 🎖️ Editor’s Choice Awards – Brain Science Journal:
    • Title: “Hybrid Deep Learning (hDL)-Based Brain-Computer Interface (BCI) Systems: A Systematic Review.”
    • Authors: Alzahab NA, Apollonio L, Di Iorio A, Alshalak M, Iarlori S, Ferracuti F, Monteriù A, Porcaro C.
    • Read more

2020:

  • 🏆 Best Poster – NYC Neuromodulation Online Conference:
    • Title: “Brain changes due to personalized neuromodulation against multiple sclerosis fatigue.”
    • Authors: Camillo Porcaro, Carlo Cottone, Andrea Cancelli, Massimo Bertoli, Eugenia Gianni, Teresa L’Abbate, Giancarlo Zito, Franca Tecchio.
    • View poster

2017-23:

  • 🌐 Honorary Senior Research Fellow – Birmingham University, UK.

2016:

  • 🎓 NeuroImage Editors’ Choice Award:
    • Recognized for the paper: “Global signal modulation of single-trial fMRI response variability: Effect on positive vs. negative BOLD response relationship.”

🌟 An impressive collection of awards, showcasing Dr. Camillo Porcaro’s outstanding contributions to neuroscientific research and technology.

🧠 Research Interests 🔬🌐 :
  • Source identification from electrophysiological recordings 📊
  • Cerebral sensorimotor cortical function 🧑‍💻
  • Machine Learning in neuroscience 🤖
  • MEG-EEG/fMRI Integration for comprehensive brain mapping 🧠🔗
  • Exploration of Resting State Networks (RSNs) 🌀
  • Brain Machine Interface (BMI) development and applications 🤝
  • Investigation of Functional & Effective Connectivity in the brain 🌐
  • Fractal Dimension Analysis for understanding complex brain dynamics 🔄
  • Study of Neurodegenerative Pathologies 🧬

A diverse and comprehensive range of research interests, covering various aspects of neuroscience, from basic brain function to applications in neurodegenerative diseases and language processing. 🌐🔬

📚 Publication Impact and Citations : 

Scopus Metrics:

  • 📝 Publications: 98 documents indexed in Scopus.
  • 📊 Citations: A total of 2,357 citations for his publications, reflecting the widespread impact and recognition of Prof. Camillo Porcaro’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 3233 📖
    • h-index: 35 📊
    • i10-index: 71 🔍
  • Since 2018:
    • Citations: 2103 📖
    • h-index: 25 📊
    • i10-index: 66 🔍

👨‍🏫 A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. 🌐🔬

Publications ( Top Note ) :

1.   Optimization of an independent component analysis approach for artifact identification and removal in magnetoencephalographic signals

.  Published in Clinical Neurophysiology in 2004 with 322 citations.

2.   Detecting large‐scale networks in the human brain using high‐density electroencephalography

.  Published in Human brain mapping in 2017 with 155 citations.

3.   Spontaneous EEG alpha oscillation interacts with positive and negative BOLD responses in the visual–auditory cortices and default-mode network

.  Published in Neuroimage in 2013 with 134 citations.

4.   Electroencephalographic fractal dimension in healthy ageing and Alzheimer’s disease

.  Published in PloS one in 2016 with 116 citations.

5.   An information theoretic approach to EEG–fMRI integration of visually evoked responses

.  Published in Neuroimage in 2010 with 77 citations.

6.   Removing speech artifacts from electroencephalographic recordings during overt picture naming

.  Published in Neuroimage in 2015 with 75 citations.

7.   Intrinsic variability in the human response to pain is assembled from multiple, dynamic brain processes

.  Published in Neuroimage in 2013 with 72 citations.

8.   High-gamma band activity of primary hand cortical areas: a sensorimotor feedback efficiency index

.  Published in Neuroimage in 2008 with 68 citations.

9.   Cortical short-term fatigue effects assessed via rhythmic brain–muscle coherence

.  Published in Experimental brain research in 2006 with 67 citations.

10.   Multimodal functional network connectivity: an EEG-fMRI fusion in network space

.  Published in PloS one in 2011 with 61 citations.