Ateke Goshvarpour | Biomedical and Healthcare Applications | Editorial Board Member

Assist. Prof. Dr. Ateke Goshvarpour | Biomedical and Healthcare Applications | Editorial Board Member

Assistant Professor | Imam Reza International University | Iran

Dr. Ateke Goshvarpour, affiliated with Imam Reza International University, Mashhad, Iran, is a distinguished researcher specializing in biomedical signal processing, cognitive neuroscience, and computational modeling of brain activity. With a prolific research portfolio comprising 70 publications and over 1,095 citations across 727 scholarly documents, Dr. Goshvarpour has established a strong global reputation for her contributions to the understanding and classification of cognitive and mental disorders using advanced signal analysis techniques.Her recent works focus on EEG-based diagnosis of schizophrenia, emotion recognition, and cognitive assessment, integrating concepts from quantum-inspired computation, chaotic dynamics, and neural connectivity analysis. Notable studies such as “Enhancing Schizophrenia Diagnosis through EEG Frequency Waves and Information-Based Neural Connectivity Feature Fusion” and “Quantum-Inspired Feature Extraction Model for Enhanced Schizophrenia Detection” highlight her innovative approach in bridging neuroscience with machine learning and chaos theory. Through the development of spectral–spatiotemporal models and graph-based signal representations, she provides novel pathways for noninvasive brain disorder diagnostics and affective computing.Collaborating with a network of 21 co-authors, Dr. Goshvarpour demonstrates an interdisciplinary outlook, integrating engineering, data science, and psychology to improve diagnostic precision and healthcare outcomes. Her h-index of 20 reflects both the impact and consistency of her research influence. Beyond academia, her work contributes significantly to societal well-being by enabling early and accurate detection of neurological conditions and enhancing emotional intelligence systems.Dr. Goshvarpour’s dedication to advancing the frontier of biomedical and cognitive signal processing underscores her role as a leading figure in computational neuroscience research, fostering a deeper understanding of human cognition through data-driven and bio-inspired intelligence frameworks.

Profiles: ORCID |  Scopus | Google Scholar

Featured Publications

1.Goshvarpour, A. (2025). Enhancing schizophrenia diagnosis through EEG frequency waves and information-based neural connectivity feature fusion. Biomedical Signal Processing and Control.

2.Goshvarpour, A. (2025). Quantum-inspired feature extraction model from EEG frequency waves for enhanced schizophrenia detection. Chaos, Solitons & Fractals. Cited By : 1

3.Goshvarpour, A. (2025). Cognitive-inspired spectral spatiotemporal analysis for emotion recognition utilizing electroencephalography signals. Cognitive Computation. Cited By : 4

4.Goshvarpour, A. (2025). Asymmetric measures of polar Chebyshev chaotic map for discrete/dimensional emotion recognition using PPG. Biomedical Signal Processing and Control. Cited By : 1

5.Goshvarpour, A. (2025). Diagnosis of cognitive and mental disorders: A new approach based on spectral–spatiotemporal analysis and local graph structures of electroencephalogram signals. Brain Sciences. Cited By : 3

Dr. Ateke Goshvarpour’s pioneering research in biomedical signal processing and neurocomputational modeling is transforming the early detection of mental and cognitive disorders. By integrating EEG analytics, chaos theory, and AI-driven methods, her work bridges neuroscience and technology—advancing precision diagnostics, enhancing emotional intelligence systems, and fostering global innovation in digital health and mental well-being.

Dr. Micheal Arowolo | Bioinformatics | Best Researcher Award

Dr. Micheal Arowolo | Bioinformatics | Best Researcher Award

Doctorate at University of Missouri, United States

Professional Profile

Summary:

Dr. Michael Olaolu Arowolo is a distinguished Nigerian computer scientist and academic with a robust background in computer science. Born on September 12, 1988, he holds a Ph.D. from Landmark University, Nigeria, an M.Sc. from Kwara State University, and a B.Sc. from Al-Hikmah University. Currently a research scholar and assistant professor at the University of Missouri, Columbia, his expertise spans machine learning, big data, data mining, bioinformatics, and computer arithmetic. Dr. Arowolo is an active member of several professional organizations, including IEEE and ISCB, and has been recognized among the top 500 authors in Nigeria by Elsevier. His career includes significant teaching and research roles, numerous professional trainings, and contributions to university development and community services.

👩‍🎓Education:

Dr. Michael Olaolu Arowolo has a robust educational background in computer science. He earned his Doctor of Philosophy (Ph.D.) in Computer Science from Landmark University, Omu-Aran, Kwara State, Nigeria, between 2018 and 2021. Prior to this, he completed his Master of Science (M.Sc.) in Computer Science from Kwara State University, Malete, Kwara State, Nigeria, from 2014 to 2017. Dr. Arowolo’s foundational academic journey began with a Bachelor of Science (B.Sc.) (Hons) in Computer Science from Al-Hikmah University, Ilorin, Kwara State, Nigeria, where he graduated with Second Class Honors (Lower Division) between 2008 and 2012. His early education includes the Senior School Certificate Examination (SSCE) from Modelak Science College, Ilorin, Kwara State, Nigeria (1998-2004), and the First School Leaving Certificate (FSLC) from ECWA L.G.E.A Primary School ‘B’, Ilorin, Kwara State, Nigeria (1991-1998).

 

Professional Memberships:

  • IEEE: Member since March 2021 (Membership No. 96234988)
  • APISE: Member since September 2019 (Membership No. M20190918110)
  • ISCB: Member since May 2019
  • Nigerian Bioinformatics and Genomics Network: Member since May 2019 (Membership No. NBGNI380)
  • SDIWC: Member since March 2017
  • EAI: Member since February 2017
  • IAENG: Member since September 2015 (Membership No. 158851)
  • Oracle Database SQL Certified Expert: Oracle University, March 2014
  • Researcher IDs: Scopus (57214819505), ORCID (0000-0002-9418-5346), Web of Science (ABD-4157-2020)

Professional Trainings:

  • Apr 2023: NIH-Biomedical Entrepreneurship Training for Aging (BETA) Program
  • Apr 2020: WHO “Infection Prevention and Control for Novel Coronavirus” Health Emergencies Program
  • Apr 2020: WHO “Introduction to Go. Data-Field Data Collection, Chains of Transmission and Contact Follow-Up” Health Emergencies Program
  • Nov 2013: SQL, Linux, and Oracle Training
  • May 2013: Project Management and Microsoft Project Training
  • Oct 2010: CCNA “Cisco Certified Network Associate” Training

Work Experience:

  • 2022-Present: Research Scholar / Instructor / Assistant Professor, Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, USA.
  • 2021: Lecturer II, Department of Computer Science, Landmark University, Omu-Aran, Kwara State, Nigeria.
  • 2020-2021: Assistant Lecturer, Department of Computer Science, Landmark University, Omu-Aran, Kwara State, Nigeria.
  • 2018-2020: Graduate Lecturer, Institute of Professional Studies, Department of Computer Science, Kwara State University, Malete, Kwara State, Nigeria.
  • 2019: Ad-Hoc Registration Area Technician, Independent National Electoral Commission (INEC), Oke-Ode, Kwara State, Nigeria.
  • 2016-2017: IT Consultant, Dalayak IT Consults, Ilorin, Kwara State, Nigeria.
  • 2013-2015: Computer Analyst, Baylings Enterprises, Ilorin, Kwara State, Nigeria.
  • 2012-2013: Computer Analyst (NYSC), Ogun-Oshun River Basin Development Authority, Abeokuta, Ogun State, Nigeria.

Awards and Recognitions:

  • Recognized among the top 169 of the top 500 authors by Elsevier Scholarly Output in Nigeria over the period of 2019-2023 (SciVal).

Skills:

  • Programming Languages: PHP, Visual Basic, SQL, Java, MATLAB, Linux, Microsoft, Python.

Research Interests and Expertise:

  • Machine Learning
  • Big Data
  • Data Mining
  • Bioinformatics
  • Computer Arithmetic

Teaching Experience (2018-2023):

  • Courses Taught:

    • Theory of Computing (CMP 306)
    • Internet Technology (IDEL 207)
    • Data Communication & Computer Networks (HECE 443)
    • Introduction to File Processing (HCSC 202)
    • Assembly Language Programming (HECE 445)
    • Web Technology (HCSC 208)
    • Systems Modelling and Simulation (HCSC 411)
    • Foundation of Sequential Program (CSC 218)
    • Artificial Intelligence (CSC 415)
    • Computer Appreciation I & II (HGNS 103, HGNS 104)
    • Object Oriented Programming Language (CMP 302)
    • Computer Application (HCSC 201)

Administrative Positions:

  • Academic Level Adviser, Computer Science 400L (2021-2022)
  • Examination Officer, Computer Science (2021-2022)
  • Member, University Ranking Committee, Landmark University (2022)
  • Instructor, H3ABioNet’s Introduction to Bioinformatics course (IBT_2021)

Contributions to University Community Development:

  • Member of Landmark University Sustainable Development Goal 9 (“Industry, Innovation, and Infrastructure”)
  • Member of the Local Organizing Committee, 2nd Nigerian Bioinformatics and Genomics Network (#NBGN21) Conference (2021)
  • Social Director, Al-Hikmah University Alumni Association

Publications Top Noted:

Paper Title: Adsorptive removal of synthetic food dyes using low-cost biochar: Efficiency prediction, kinetics and desorption index evaluation
  • Authors: Bankole, D.T., Inyinbor, A.A., Oluyori, A.P., Arowolo, M.O.
  • Journal: Bioresource Technology Reports
  • Volume: 25
  • Pages: 101709
  • Year: 2024
Paper Title: Mitigating cyber threats in healthcare systems: The role of artificial intelligence and machine learning
  • Authors: Wisdom, D.D., Vincent, O.R., Igulu, K., Christian, A.U., Baba, G.A.
  • Book: Artificial Intelligence and Blockchain Technology in Modern Telehealth Systems
  • Pages: 369–408
  • Year: 2024
Paper Title: Classification of customer churn prediction model for telecommunication industry using analysis of variance
  • Authors: Babatunde, R., Abdulsalam, S.O., Abdulsalam, O.A., Arowolo, M.O.
  • Journal: IAES International Journal of Artificial Intelligence
  • Volume: 12
  • Issue: 3
  • Pages: 1323–1329
  • Year: 2023
Paper Title: Phishing Detection in Blockchain Transaction Networks Using Ensemble Learning
  • Authors: Ogundokun, R.O., Arowolo, M.O., Damaševičius, R., Misra, S.
  • Journal: Telecom
  • Volume: 4
  • Issue: 2
  • Pages: 279–297
  • Year: 2023
Paper Title: Machine learning-based IoT system for COVID-19 epidemics
  • Authors: Arowolo, M.O., Ogundokun, R.O., Misra, S., Agboola, B.D., Gupta, B.
  • Journal: Computing
  • Volume: 105
  • Issue: 4
  • Pages: 831–847
  • Year: 2023