Souhail Dhouib | Artificial Intelligence | Best Researcher Award

Posted on by ScienceFather

Prof. Souhail Dhouib | Artificial Intelligence | Best Researcher Award

Full Professor, Higher Institute of Industrial Management, University of Sfax, Tunisia

Prof. Souhail Dhouibย ๐ŸŒŸย is a distinguished academic and industry expert specializing in Artificial Intelligence and Operations Research. He holds the position of Full Professor at the Higher Institute of Industrial Management, University of Sfax, Tunisia, where he has taught for over twenty years. Prof. Dhouib is renowned for his pioneering work in matrix optimization concepts and has made significant contributions to decision-making and planning through his innovative algorithms and methodologies.

ProfileArtificial Intelligenceย 

ORCID

 

Education

Prof. Dhouib completed hisย Ph.D. in Quantitative Methodsย from the Faculty of Management and Economics Sciences, Sfax University, Tunisia (2004-2009). He also holds aย Masterโ€™s degree in Operations Research and Production Managementย (2001-2003) and aย Bachelorโ€™s degree in Management Information Systemsย (1992-1996), all from the same institution.ย ๐Ÿ“š๐ŸŽ“

Experience

Prof. Dhouib has over twenty years of extensive experience in both academia and industry. He has served as a General Manager and an Analyst Programmer, where he was involved in software development and implementation. His academic roles include positions as a Full Professor, Associate Professor, and Assistant Professor, contributing significantly to teaching and research.ย ๐Ÿข๐Ÿ’ป

Research Interests

Prof. Dhouib’s research focuses on Artificial Intelligence, Operations Research, and Optimization algorithms. His work spans various domains, including Logistics, Supply Chain Management, Business Intelligence Systems, and ERP. He is particularly known for his Dhouib-Matrix methods and their applications in cognitive robotics, multi-objective optimization, and path planning.ย ๐Ÿ”๐Ÿ“ˆ

Awards

Prof. Dhouib’s contributions to the field have been recognized through numerous journal publications, although specific awards are not listed in the provided information. His innovative research and development efforts continue to impact the industry and academia.ย ๐Ÿ†๐Ÿ‘

Publications

Intelligent Path Planning for Cognitive Mobile Robot Based on Dhouib-Matrix-SPP Methodย (2024) –ย Cognitive Robotics

Multi-Start Constructive Heuristic through Descriptive Statistical Metrics: The Dhouib-Matrix-4 Metaheuristicย (2024) –ย International Journal of Operational Research

Innovative Method to Solve the Minimum Spanning Tree Problem: The Dhouib-Matrix-MSTP (DM-MSTP)ย (2024) –ย Results in Control and Optimization

Enhancing the Dhouib-Matrix-4 Metaheuristic to Generate the Pareto Non-Dominated Set Solutions for Multi-objective Travelling Salesman Problem: The DM4-PMO Methodย (2024) –ย Results in Control and Optimization

Faster than Dijkstra and A* Methods for the Mobile Robot Path Planning Problem Using Four Movement Directions: The Dhouib-Matrix-SPP-4ย (2024) –ย Advances in Transdisciplinary Engineering, Mechatronics and Automation Technology

Nafis Uddin Khan | Artificial Intelligence | Best Researcher Award

Posted on by ScienceFather

Dr Nafis Uddin Khan | Artificial Intelligence | Best Researcher Awardย 

Dr Nafis Uddin Khan, SR University Warangal India, India

Dr. Nafis Uddin Khan is a distinguished academic and researcher at SR University in Warangal, India. His expertise spans a variety of fields, contributing significantly to both the academic community and industry advancements. Dr. Khan’s work is characterized by a strong focus on innovative solutions and sustainable practices, reflecting his commitment to addressing contemporary challenges through research and education. At SR University, he plays a pivotal role in mentoring students and leading research initiatives that aim to drive technological progress and societal impact.

Profile

Orcid

Education

ย  ย  ย  ย Bachelor of Engineering (B.E.) in Electronics and Telecommunication Engineering from Amravati Universityย  Maharashtra, in 2003.

ย  ย  ย  ย Master of Technology (M.Tech.) in Software Systems from S.A.T.I. Vidisha under Rajiv Gandhi Technological University, Bhopal, in 2008.

ย  ย  ย  ย  Doctor of Philosophy (Ph.D.) in Signal and Image Processing from the Atal Bihari Vajpayee โ€“ Indian Institute of Information Technology & Management, Gwalior

Professional experience

  1. Workshop Coordinator: Coordinated a two-day workshop titled “Synthesis of Wisdom: Crafting AI Tutor Assistants, Navigating Future-Ready Digital Libraries and Elevating Pedagogy in the Age of Skill Enhancement and AI Mastery” on February 02โ€“03, 2024, at the School of CS & AI, SR University, Warangal, India.
  2. Faculty Development Program Coordinator: Coordinated โ€œUtkarsh โ€“ Take Flight,โ€ a two-day Faculty Development Program on Leadership and Excellence in Quality Education organized by Jaypee University of Information Technology, Solan (H.P.), on December 22โ€“23, 2022.
  3. Chief Coordinator: Served as Chief Coordinator in a student outreach activity organized by the Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Solan (H.P.), on December 20, 2022.
  4. Invited Session Chair: Served as an Invited Session Chair in the Congress on Intelligent Systems (CIS 2020), World Conference in virtual format, on September 05โ€“06, 2020.
  5. Organizing Committee Member and Reviewer: Participated as an Organizing Committee Member and Reviewer in the Congress on Intelligent Systems (CIS 2020), World Conference in virtual format, on September 05โ€“06, 2020.
  6. Convener: Organized a one-week online short-term course on โ€œRecent Advances in Computational Intelligence for Signal Processingโ€ (RACISP โ€“ 2020) at Jaypee University of Information Technology, Solan (H.P.), from August 10โ€“15, 2020.
  7. Coordinator: Coordinated a five-day short-term course on โ€œRecent Advances in Signal and Image Processingโ€ (RASIP โ€“ 2019) at Jaypee University of Information Technology, Solan (H.P.), from June 24โ€“28, 2019.
  8. Organizing Committee Member: Served in the organizing committee for the 5th IEEE International Conference on โ€œSignal Processing, Computing and Controlโ€ (ICSPC 2019) organized by the Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Solan (H.P.), from October 10โ€“12, 2019.
  9. Invited Session Chair: Chaired an invited session in the 2019 IEEE International Conference on โ€œImage Information Processingโ€ (ICIIP 2019) organized by the Department of Computer Science and Engineering, Jaypee University of Information Technology, Solan (H.P.), from November 15โ€“17, 2019.
  10. Organizing Committee Member: Participated as an organizing committee member in the 4th IEEE International Conference on โ€œSignal Processing, Computing and Controlโ€ (ICSPC 2017) at Jaypee University of Information Technology, Solan (H.P.), from September 21โ€“23, 2017.
  11. Invited Session Chair: Served as an invited session chair at the 7th IEEE International Conference on โ€œComputational Intelligence and Communication Networksโ€ (CICN 2015) at Gyan Ganga Institute of Technology and Science, Jabalpur (M.P.), on December 12, 2015.
  12. National Advisory Committee Member: Served on the National Advisory Committee for the National Conference on Contemporary Computing organized by the Department of Computer Science and Information Technology, Chameli Devi Group of Institutions, Indore (M.P.), from October 21โ€“22, 2016.

Research Focus

ย  ย  ย  Fuzzy Logic and Optimization: Utilizing fuzzy logic for applications in signal and image processing, including the development of fuzzy-based diffusion coefficient functions for selective noise smoothing.

ย  ย  ย  Medical Image Processing: Enhancing medical imaging techniques, such as de-speckling in ultrasound and X-ray images, and improving image de-noising using soft optimization techniques.

ย  ย  ย  Pattern Analysis in Machine Intelligence: Investigating pattern analysis and its applications within machine intelligence to improve the accuracy and efficiency of image processing algorithms.

Awards and Honorsย 

Zhidong CAO | Data Science | Best Researcher Award

Posted on by ScienceFather

Mr. Zhidong CAO | Data Science |ย ย Best Researcher Award

Zhidong CAO at Institute of Automation, Chinese Academy of Sciences, China

Zhidong CAO is a renowned professor and principal investigator at the National Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences. With a Doctor of Science degree, he has made significant contributions to the field of artificial intelligence and has been recognized for his work in various national and international platforms.

Profile

Orcid

Education

Zhidong CAO earned his Ph.D. from the Institute of Geographic Sciences and Natural Resources Research at the Chinese Academy of Sciences in 2008. He also holds a Masterโ€™s degree and a Bachelorโ€™s degree from Changsha University of Science and Technology, completed in 2005 and 2001 respectively.

Research Focus

His research interests lie primarily in the areas of multimodal artificial intelligence systems, social computing, and geographic information analysis. He has been instrumental in several key national scientific and technological projects, including the National Medium- and Long-term Scientific and Technological Development Plan (2021-2035) and the New Generation Artificial Intelligence Strategic Plan.

Professional Journey

Zhidong CAO began his professional journey as a Postdoctoral Fellow at the Institute of Automation, Chinese Academy of Sciences, in 2008. He progressed to become an Assistant Researcher in 2010, then an Associate Researcher in 2011, and has been serving as a Researcher since 2020. His roles have seen him engage deeply with various research projects and contribute significantly to the field of automation and artificial intelligence.

Honors & Awards

Throughout his career, Zhidong CAO has received numerous prestigious awards. Notable among these are the Beijing Science and Technology Progress Award (Second Prize, 2022), the China Surveying and Mapping Society Science and Technology Award (Grand Prize, 2021), and the Chinese Society of Simulation Natural Science First Prize (2018). His contributions have also been recognized by the Chinese Association of Automation and the Chinese Preventive Medicine Association.

Publications Noted & Contributions

Zhidong CAO has an impressive portfolio of over 120 research papers published in leading domestic and international journals and conferences. He has also authored three books, further establishing his expertise in his field. His research has earned him six scientific and technological awards, underscoring his significant contributions to the advancement of artificial intelligence and related domains.

  1. Coordinated Cyber Security Enhancement for Grid-Transportation Systems With Social Engagement
    • Journal: IEEE Transactions on Emerging Topics in Computational Intelligence
    • DOI: 10.1109/TETCI.2022.3209306
    • Contributors: Pengfei Zhao, Shuangqi Li, Paul Jen-Hwa Hu, Zhidong Cao, Chenghong Gu, Da Xie, Daniel Dajun Zeng
    • Summary: This article discusses methods for enhancing cybersecurity in grid-transportation systems through coordinated efforts and social engagement. It emphasizes the importance of integrating social factors and community involvement in cybersecurity strategies.
  2. Energy-Social Manufacturing for Social Computing
    • Journal: IEEE Transactions on Computational Social Systems
    • DOI: 10.1109/TCSS.2024.3379254
    • Contributors: Alexis Pengfei Zhao, Shuangqi Li, Yanjia Wang, Paul Jen-Hwa Hu, Chenye Wu, Zhidong Cao, Faith Xue Fei
    • Summary: This article explores the concept of energy-social manufacturing, which integrates energy systems with social computing to enhance efficiency and sustainability. The research highlights the role of social computing in optimizing energy production and consumption.
  3. Modeling the Coupling Propagation of Information, Behavior, and Disease in Multilayer Heterogeneous Networks
    • Journal: IEEE Transactions on Computational Social Systems
    • DOI: 10.1109/TCSS.2023.3306014
    • Contributors: Tianyi Luo, Duo Xu, Zhidong Cao, Pengfei Zhao, Jiaojiao Wang, Qingpeng Zhang
    • Summary: This study models the interactions and propagation dynamics of information, behavior, and disease within multilayer heterogeneous networks. It provides insights into how these elements influence each other and spread across different network layers.
  4. Socially Governed Energy Hub Trading Enabled by Blockchain-Based Transactions
    • Journal: IEEE Transactions on Computational Social Systems
    • DOI: 10.1109/TCSS.2023.3308608
    • Contributors: Pengfei Zhao, Shuangqi Li, Zhidong Cao, Paul Jen-Hwa Hu, Chenghong Gu, Xiaohe Yan, Da Huo, Tianyi Luo, Zikang Wang
    • Summary: This article examines how blockchain technology can facilitate socially governed energy hub trading. It discusses the implementation of blockchain-based transactions to enhance transparency, security, and efficiency in energy markets.
  5. A Cross-Lingual Transfer Learning Method for Online COVID-19-Related Hate Speech Detection
    • Journal: Expert Systems with Applications
    • DOI: 10.1016/j.eswa.2023.121031
    • Contributors: Lin Liu, Duo Xu, Pengfei Zhao, Daniel Dajun Zeng, Paul Jen-Hwa Hu, Qingpeng Zhang, Yin Luo, Zhidong Cao
    • Summary: This research presents a method for detecting COVID-19-related hate speech online using cross-lingual transfer learning. The study demonstrates the effectiveness of the proposed method in identifying hate speech across different languages, aiding in the fight against online misinformation and discrimination.

 

Rainer Knauf | Evolutionary Algorithms | Lifetime achievement Award

Posted on by ScienceFather

Prof Dr Rainer Knauf | ย Evolutionary Algorithms |ย ย Lifetime achievement Award

Fachgebietsleiter fรผr KI atย ย Technische Universitรคt Ilmenau,ย Germany

Rainer Knauf is an apl. Prof. Dr.-Ing. habil., currently serving as the Chair of Artificial Intelligence at the Faculty of Computer Science and Automation, Technical University Ilmenau, Germany. He earned his Diploma Engineer (Dipl.-Ing.) in Electrical and Computer Engineering in 1987, followed by a Doctor of Engineering (Dr.-Ing.) in Computer Engineering in 1990, and a Doctor of Engineering habilitatus (Dr.-Ing. habil.) in Computer Science in 2000, all from Technical University Ilmenau. His research focuses on knowledge acquisition, validation, and refinement of intelligent systems, inductive inference, and machine learning.

 

profile

๐ŸŽ“ Education:

  • Dipl.-Ing. in Electrical and Computer Engineering
    Technical University Ilmenau, Germany
    ๐Ÿ“… February 5, 1987
  • Dr.-Ing. in Computer Engineering
    Technical University Ilmenau, Germany
    ๐Ÿ“… September 25, 1990
    Dissertation: โ€œApplying Logic Programming to Design Knowledge Based Systems for Diagnostic Problemsโ€
  • Dr.-Ing. habil. in Computer Science
    Technical University Ilmenau, Germany
    ๐Ÿ“… November 15, 2000
    Habilitation: โ€œValidating Rule Based Systems: A Complete Methodologyโ€

๐Ÿ’ผ Professional Experience:

  • Full Professor (apl. Prof.)
    Chair of Artificial Intelligence, Technical University Ilmenau
    ๐Ÿ“… March 2010 – Present
  • Associate Professor (Privatdozent)
    Chair of Artificial Intelligence, Technical University Ilmenau
    ๐Ÿ“… April 2004 – February 2010
  • Assistant Professor (Privatdozent)
    Technical University Ilmenau
    ๐Ÿ“… December 2000 – March 2004
  • Scientific Assistant
    Technical University Ilmenau
    ๐Ÿ“… September 1991 – November 2000
  • Scientific Associate
    Ilmenau Institute of Technology
    ๐Ÿ“… March 1987 – August 1991

๐Ÿ… Awards & Recognitions

  • Fellowship Awards from the Japan Society for the Promotion of Science ๐Ÿ“œ (2008, 2011, 2015)
  • Graduate Faculty Scholar at the University of Central Florida ๐ŸŽ“ (2010)

Research Focus: Evolutionary Algorithms ๐Ÿงฌ๐Ÿ’ก

Research Interests:

  • Optimization and Search Algorithms: Rainer Knauf’s work in evolutionary algorithms involves developing and improving algorithms for optimization and search problems. These algorithms are inspired by the principles of natural selection and genetics.
  • Artificial Intelligence Applications: He applies evolutionary algorithms to various AI challenges, including machine learning, robotics, and automated reasoning.
  • Knowledge Acquisition and Refinement: His research integrates evolutionary algorithms with knowledge-based systems to enhance the processes of knowledge acquisition, validation, and refinement.
  • Data Mining: Knauf explores the use of evolutionary algorithms in data mining, particularly in extracting meaningful patterns and insights from large datasets.
  • Inductive Inference: His work also includes using evolutionary algorithms for inductive inference, aiming to generalize from specific data to broader rules or patterns.

Citation:

Cited by:

  • All: 1082 citations
  • Since 2019: 253 citations

h-index:

  • Overall: 16
  • Since 2019: 7

i10-index:

  • Overall: 33
  • Since 2019: 4

Publication Top Notes:

  • “Didactic design through storyboarding: Standard concepts for standard tools”
    • Authors: KP Jantke, R Knauf
    • Publication: Proceedings of the 4th International Symposium on Information and Communication Technologies
    • Citations: 122 (2005)
    • Summary: This paper explores the use of storyboarding as a method for didactic design, emphasizing standard concepts to standardize tools for educational purposes.
  • “A framework for validation of rule-based systems”
    • Authors: R Knauf, AJ Gonzalez, T Abel
    • Publication: IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
    • Citations: 80 (2002)
    • Summary: This paper presents a comprehensive framework for validating rule-based systems, addressing the need for systematic validation processes in artificial intelligence.
  • “Validation of human behavior representation”
    • Authors: SY Harmon, VB Barr, AJ Gonzalez, DC Hoffmann, R Knauf
    • Publication: University Library
    • Citations: 45 (2006)
    • Summary: The authors discuss methodologies for validating models of human behavior representation, crucial for developing reliable AI systems that simulate human actions.
  • “Modeling didactic knowledge by storyboarding”
    • Authors: R Knauf, Y Sakurai, S Tsuruta, KP Jantke
    • Publication: Journal of Educational Computing Research
    • Citations: 39 (2010)
    • Summary: This research focuses on the use of storyboarding to model didactic knowledge, enhancing the design and delivery of educational content through structured visual methods.
  • “Toward reducing human involvement in validation of knowledge-based systems”
    • Authors: R Knauf, S Tsuruta, AJ Gonzalez
    • Publication: IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans
    • Citations: 25 (2006)
    • Summary: This paper proposes methods to minimize human intervention in the validation process of knowledge-based systems, aiming for more autonomous and efficient validation techniques.
  • “Tweet credibility analysis evaluation by improving sentiment dictionary”
    • Authors: T Kawabe, Y Namihira, K Suzuki, M Nara, Y Sakurai, S Tsuruta, R Knauf
    • Publication: 2015 IEEE Congress on Evolutionary Computation (CEC)
    • Citations: 24 (2015)
    • Summary: This work evaluates the credibility of tweets by enhancing sentiment dictionaries, leveraging evolutionary computation techniques to improve the accuracy of sentiment analysis.
  • “A simple optimization method based on backtrack and GA for delivery schedule”
    • Authors: Y Sakurai, K Takada, N Tsukamoto, T Onoyama, R Knauf, S Tsuruta
    • Publication: 2011 IEEE Congress of Evolutionary Computation (CEC)
    • Citations: 22 (2011)
    • Summary: The authors present an optimization method combining backtracking and genetic algorithms (GA) to improve delivery scheduling, demonstrating the application of evolutionary algorithms in logistics.
  • “Generation of a minimal set of test cases that is functionally equivalent to an exhaustive set, for use in knowledge-based system validation”
    • Authors: T Abel, R Knauf, AJ Gonzalez
    • Publication: Proceedings of the 9th FLAIRS Conference
    • Citations: 22 (1996)
    • Summary: This paper discusses a method for generating a minimal set of test cases that maintains functional equivalence to an exhaustive set, enhancing the efficiency of knowledge-based system validation.
  • “Modeling academic education processes by dynamic storyboarding”
    • Authors: Y Sakurai, S Dohi, S Tsuruta, R Knauf
    • Publication: Journal of Educational Technology & Society
    • Citations: 21 (2009)
    • Summary: The study models academic education processes through dynamic storyboarding, offering a structured approach to designing and implementing educational curricula.
  • “Validating Rule-Based Systems: A Complete Methodology”
    • Author: R Knauf
    • Publication: Shaker
    • Citations: 21 (2000)
    • Summary: This book provides a comprehensive methodology for the validation of rule-based systems, detailing systematic approaches to ensure the reliability and accuracy of these systems.

 

 

Sivayazi Kappagantula | Autonomous intelligent systems | Best Researcher Award

Posted on by ScienceFather

Mr. Sivayazi Kappagantula | Autonomous intelligent systems | Best Researcher Award

Mr. Sivayazi Kappagantula, MIT Manipal, India

Dr. Sivayazi Kappagantula is an accomplished Roboticist, experienced in Software, Defense, and Aerospace industries. With expertise in ROS, Python, and SolidWorks, he has excelled in teaching and research roles, notably at Manipal Institute of Technology and Defence Institute of Advanced Technology. His doctoral focus at Vellore Institute of Technology delves into autonomous robotics and reinforcement learning. Dr. Kappagantula’s contributions include designing biomimetic robots and pioneering motion planning algorithms for unmanned vehicles. Recognized for his patents and publications, he continues to shape the field through workshops, conferences, and guided student projects. ๐Ÿค–๐Ÿ“š

 

Publication Profile

Google Scholar

๐Ÿ“š Education

Undertaking doctoral studies at Vellore Institute of Technology, Sivayazi delves into the complexities of motion planning in autonomous robotics, focusing on reinforcement learning and path planning. His master’s thesis explored the control algorithm of a biomimetic robot fish for underwater exploration.

Professional Experience

Sivayazi Kappagantula boasts a rich background in Robotics, having contributed significantly across various sectors including academia, defense, and software industries. Currently serving as an Assistant Professor at Manipal Institute of Technology, Udupi, he supervises academic projects, publishes papers, and conducts robotics lab sessions.

Research Focus

Sivayazi Kappagantula’s research primarily centers around robotics and autonomous systems, with a particular emphasis on developing innovative solutions for obstacle avoidance, navigation, and control in various domains. His work spans diverse applications, including unmanned aerial vehicles (UAVs), biomimetic robot fish, and sea surface vehicles. By leveraging advanced techniques such as fuzzy logic algorithms and reinforcement learning, he aims to enhance the autonomy, efficiency, and adaptability of robotic systems. Through his contributions, Sivayazi endeavors to advance the field of robotics and address real-world challenges in areas like defense, agriculture, and environmental monitoring. ๐ŸŒ

 

Publication Top Notes