The Inverse Problems for Computational Psychophysiology

The Science Partner Journal Cyborg and Bionic Systems is now considering submissions for a Special Issue on the Inverse Problems for Computational Psychophysiology.

Scope

In the past decade, the theory of computational psychophysiology (CP) has been successfully applied to understand, diagnose, and treat the psychiatric disorders (e.g., the depressive disorders). By leveraging the power of artificial intelligence and big data, CP has empowered the diagnosis and treatment of psychiatric disorders from the era of subjective description to the era of data-driven methods. Nevertheless, the fundamentals of CP are still not well studied, which restrains a deep understanding about the human mind working mechanism. The mathematical inverse problem tool can benefit the way when exploring the fundamentals of CP. We are organizing this special issue in Cyborg and Bionic Systems to attract prospective contributions from the scientific community on topics which include, but are not limited to:

  • The theory, methodology, and paradigm of the inverse problems for computational psychophysiology.
  • Explainable models for computational psychophysiology.
  • Mathematical methods for optimizing the modelling of computational psychophysiology.
  • Medical applications by using the inverse problems for computational psychophysiology.
  • Perspectives, challenges, and ethical issues of the inverse problems for computational psychophysiology.

    Guest Editors

    Dr. Bin Hu, Beijing Institute of Technology

    Bin HU received his Ph.D. degree in computer science from the Institute of Computing Technology, Chinese Academy of Science in 1998. He is a (Full) Professor and the Dean of the School of Medical Technology at Beijing Institute of Technology, China. He is a National Distinguished Expert, the Chief Scientist of 973 as well as the National Advanced Worker in 2020, who was elected as a Fellow of the Institution of Engineering and Technology (IET). He is a Member of the Steering Council of the ACM China Council and the Vice-Chair of the China Committee of the International Society for Social Neuroscience. He serves as the Editor-in-Chief for the IEEE Transactions on Computational Social Systems. He is also the TC Co-Chair of computational psychophysiology in the IEEE Systems, Man, and Cybernetics Society (SMC), and the TC Co-Chair of cognitive computing in IEEE SMC. He is a member of the Computer Science Teaching and Steering Committee as well as the Science and Technology Committee. He (co-)authored more than 400 publications (10 000+ citations, h-index 51). His awards include the 2014 China Overseas Innovation Talent Award, the 2016 Chinese Ministry of Education Technology Invention Award, the 2018 Chinese National Technology Invention Award, and the 2019 WIPO-CNIPA Award for Chinese Outstanding Patented Invention. He is a Principal Investigator for large grants such as the National Transformative Technology “Early Recognition and Intervention Technology of Mental Disorders Based on Psychophysiological Multimodal Information”, which have greatly promoted the development of objective, quantitative diagnosis and non-drug interventions for mental disorders.

    Dr. Kun Qian, Beijing Institute of Technology

    Kun QIAN received his doctoral degree for his study on automatic general audio signal classification in 2018 in electrical engineering and information technology from Technische Universität München (TUM), Germany. From 2021, he has been appointed as a (Full) Professor with a title of “Teli Young Fellow” at the Beijing Institute of Technology, China. He has a strong collaboration tradition with prestigious universities in Germany, Japan, Singapore, UK, and the USA. Dr. Qian serves as an Associate Editor for the IEEE Transactions on Affective Computing, Frontiers in Digital Health, and BIO Integration. He (co-)authored more than 90 publications in peer reviewed journals, and conference proceedings having received more than 1.5k citations (h-index 21).

    Dr. Ye Zhang, MSU-BIT University

    Ye ZHANG received the B.S. degree in information and computing sciences from Zhejiang University, Hangzhou, China in 2007, and the M.S. degree in physics and the Ph.D. degree in mathematical physics from Lomonosov Moscow State University, Moscow, Russia in 2011 and 2014, respectively. He is a Full Professor with the Beijing Institute of Technology, Beijing, China, and Shenzhen MSU-BIT University, Shenzhen, China. Currently, he is also vice-dean of the Faculty of Computational Mathematics and Cybernetics at Shenzhen MSU-BIT University, and the executive director of MSU-BIT-SMBU joint research center on computational mathematics and control. He awards include the Kovalevskaya grant for International Congress of Mathematicians in 2022, the High-level Overseas Talents: Youth Project in 2020, and the Humboldt Research Fellowship in 2017, respectively. His research interests include mathematical modeling and numerical analysis of inverse problems in mathematical physics. He is a Principal Investigator for large grants such as the Beijing Natural Science Key Project “Modern Regularization Methods of Inverse Problems and Their Applications”, which have greatly promoted the development of modern theorems and applications of some inverse problems in science and engineering. He published more than 30 articles in some top journals in the field of inverse problems (such as “Inverse Problems”, “Journal of Inverse and Ill-Posed Problems”, “Inverse Problems and Imaging” and “Inverse Problems in Science and Engineering”) and also in the fields of applied mathematics and statistics (such as “SIAM Journal on Imaging Sciences”, “Journal of the American Statistical Association”, etc.). He is the referee for more than 20 mathematical and statistical journals.

    Dr. Enrique Herrera-Viedma, University of Granada

    Enrique HERRERA-VIEDMA received the M.Sc. and Ph.D. degrees in computer science from the University of Granada, Granada, Spain, in 1993 and 1996, respectively. He is currently a Professor of computer science and AI and the Vice-President for research and knowledge transfer with the University of Granada. His H-index is 69 (more than 17 000 citations received in the Web of Science and 85 in Google Scholar), with more than 29 000 cites received. He has been identified as one of the World’s most influential researchers by the Shanghai Centre and Thomson Reuters/Clarivate Analytics in both the scientific categories of computer science and engineering, from 2014 to 2018. His current research interests include group decision making, consensus models, linguistic modeling, aggregation of information, information retrieval, bibliometric, digital libraries, web quality evaluation, recommender systems, blockchain, smart cities, and social media.

    Dr. Yoshiharu Yamamoto, The University of Tokyo

    Yoshiharu YAMAMOTO received the B.Sc., M.Sc., and Ph.D. degrees in education from The University of Tokyo, Tokyo, Japan, in 1984, 1986, and 1990, respectively. Since 2000, he is a Professor at the Graduate School of Education, The University of Tokyo, where he is teaching and researching physiological bases of health sciences and education. His research interests include biomedical signal processing, nonlinear and statistical biodynamics, and health informatics. Dr. Yamamoto is currently an Associate Editor of the IEEE Transactions on Biomedical Engineering, and an Editorial Board Member of the Technology and Biomedical Physics and Engineering Express. He is also the president of the Healthcare IoT Consortium, Japan. He (co-)authored more than 230 publications in peer reviewed books, journals, and conference proceedings leading to more than 12 000 citations (h-index 59).

    Dr. Björn Schuller, Imperial College London

    Björn W. SCHULLER received his diploma, doctoral degree, habilitation, and Adjunct Teaching Professor in Machine Intelligence and Signal Processing all in EE/IT from TUM in Munich/Germany. He is Full Professor of Artificial Intelligence and the Head of GLAM at Imperial College London/UK, Full Professor and Chair of Embedded Intelligence for Health Care and Wellbeing at the University of Augsburg/Germany, co-founding CEO and current CSO of audEERING – an Audio Intelligence company based near Munich and in Berlin/Germany, independent research leader within the Alan Turing Institute and Royal Statistical Society Lab’s Data, Analytics and Surveillance Group, as part of the UK Health Security Agency, and permanent Visiting Professor at HIT/China amongst other Professorships and Affiliations. Previous stays include Guest Professor at Southeast University in Nanjing/China, Full Professor at the University of Passau/Germany, Key Researcher at Joanneum Research in Graz/Austria, and the CNRS-LIMSI in Orsay/France. He is a Fellow of the IEEE and Golden Core Awardee of the IEEE Computer Society, Fellow of the BCS, Fellow of the ISCA, Fellow and President-Emeritus of the AAAC, and Senior Member of the ACM. He (co-)authored 1,200+ publications (45k+ citations, h-index=98), is Field Chief Editor of Frontiers in Digital Health and was Editor in Chief of the IEEE Transactions on Affective Computing amongst manifold further commitments and service to the community. His 40+ awards include having been honored as one of 40 extraordinary scientists under the age of 40 by the WEF in 2015. He served as Coordinator/PI in 15+ European Projects, is an ERC Starting and DFG Reinhart-Koselleck Grantee, and consultant of companies such as Barclays, GN, Huawei, Informetis, or Samsung.

      Submission Deadline

      February 28, 2023

        Submission Instructions

        Please select "Special Issue: The Inverse Problems for Computational Psychophysiology" as the section/category during the submission process. Please also indicate in your cover letter that your submission is intended for inclusion in the special issue.