Soft Computing - Call for Papers: Trustworthiness in soft computing techniques

CLOSED FOR SUBMISSIONS

Guest Editors:

Shahid Hussain, Assistant Professor, Penn State University, Behrend, PA, USA (Lead Guest Editor)
Arif Ali Khan, Assistant Professor, University of Oulu, Finland
Wen-Li Wang, Assistant Professor, Penn State University, Behrend, PA, USA

CLOSED FOR SUBMISSIONS

Description: 

Soft computing techniques are considered important across a vast array of industries, including health, manufacturing, banking and retail. Soft computing deals with approximate models by combining techniques and concepts and handling imprecision and uncertainty as a computational paradigm. The research community recommends different solutions for real-world problems requiring the system to combine data, knowledge, techniques and methods from certain sources. These systems aim to learn from the changing environments and replace the human expertise of any domain to make informed decisions. 
Moreover, research communities in various domains have successfully deployed soft computing techniques such as Natural Language Processing (NLP), Artificial Intelligence (AI), and Machine Learning (ML) approaches to design and implement complex systems. However, the promises of these techniques like improving productivity, reducing costs, and safety have now been considered with worries, that these complex techniques and opaque systems might bring more social harm than economical good.
People start thinking beyond the operational capabilities of soft computing techniques and investigate the trustworthiness aspects of developing powerful and potentially life consequential technologies. The ethical harm brought by soft computing techniques might jeopardize human control. These potential threats set a stage for trustworthiness discussion with respect to the point of view of policymakers, academic researchers and industrial practitioners. Exploring the trustworthiness aspects of soft computing techniques will ensure that their actions are ethically aligned with human values that should not be compromised.
This special issue aims to provide a platform for practitioners, researchers and policymakers to discuss the trustworthiness of soft computing techniques by considering social, managerial, organizational, economical and technical aspects.

Papers in the field of trustworthiness in applied computing on (but not limited to) the following topics are invited for submission:

•    Knowledge development technique for trustworthiness
•    Tools for trustworthiness analysis
•    Validation and verification approaches for trustworthiness
•    Type of data (structured, unstructured and semi-structured) for trustworthiness analysis
•    Fairness measures, metrics and indicator
•    Software Engineering practices for trustworthiness
•    Automation in repairing the biased models/classifiers/predictors
•    Human factors related to fairness 
•    AI Ethics
•    Policy, compliance and legislation of trustworthiness
•    Technological perspective of ethics
•    Human-centered values
•    Fairness properties and requirements
•    Accountability, responsibility and transparency
•    Fairness in sentiment analysis
•    Trustworthiness automation
•    Sustainability

SUBMISSION - IMPORTANT INFORMATION

• All papers will be peer-reviewed. Before any special issue is given final approval to be put into production, additional rigorous integrity checks are carried out by the Editor-in-Chief, Special Issues Assistant Editor, Editorial Team, Production Office and by Springer Nature.
•  Authors should follow the formatting and submission instructions for Soft Computing: https://www.springer.com/journal/500/submission-guidelines (this opens in a new tab)
• During the first submission step in Editorial Manager select 'Original article' as the article type. In further steps you should confirm that your submission belongs to this special issue by choosing the special issue title from the drop-down menu.
• Submissions should be original papers and should not be under consideration for publication elsewhere.

Guest Editor Biographies: 

Shahid Hussain is working as an Assistant Professor at the Computer Science and Software Engineering Department, School of Engineering, Penn State University Behrend, Erie, PA, USA. Before Joining PSU, he has worked as a Pro temp (NTTF) at the Computer and Information Science Department, University of Oregon, Eugene, Oregon, USA. He is a research collaborator at SERC, MID Lab, Smart Intelligence team, SERC-KUST, and SE-CU (HK) team. His current research focus is to explore the software engineering practices for High Performance Computing (HPC) software packages and applications to improve their process and benchmark their quality levels, to automate the document generation for open-source software, and to explore the implications of Machine learning, Artificial Intelligence (AI), Big data analysis and soft computing technique in analysis and design of software.

Arif Ali Khan works as an Assistant Professor with the M3S Unit, Empirical Software Engineering in Software, Systems and Services, University of Oulu, Finland. Previously he worked as a faculty member with the Faculty of Information Technology, University of Jyvaskyla, Finland; College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China; and Department of Computer Science, COMSATS University, Islamabad, Pakistan. He received a BS degree in software engineering from the University of Science and Technology, Bannu, Pakistan and an MSc degree in information technology from Universiti Teknologi PETRONAS, Malaysia. He obtained a PhD degree in software engineering from the Department of Computer Science, City University of Hong Kong. He has participated in and managed several empirical software engineering-related research projects. Khan has expertise in software process improvement, global software development, multi-criteria decision analysis, DevOps, microservices architecture, AI ethics, agile software development, requirements change management, soft computing, and evidence-based software engineering. He is professionally active in conducting publication-based research workshops, serving as guest editor in main track software engineering journals, and editing software engineering research books. He has published over 60 articles in peer-reviewed software engineering conferences and journals.

Wen-Li Wang is an associate professor of Computer Science and Software Engineering at Penn State Behrend. He received the B.S. in Management Information Systems from NCCU, Taipei, Taiwan in 1991, and both the M.S. and Ph.D. in Computer Science from the State University of New York SUNY at Albany in 1996 and 2002 respectively where he received the best thesis award in 2003 for his work. Dr. Wang joined the Penn State Behrend faculty in August of 2002.
Dr. Wang's first engineering job was as a LAN administrator for the Department of MIS in Taipei, Taiwan in 1993-1994. He then worked as a graduate assistant and teaching assistant while completing his education at SUNY-Albany. Dr. Wang is a member of the Institute of Electrical and Electronic Engineers IEEE.