Assoc Prof Dr. Jerzy Domżał | SDN controllers | Best Researcher Award

Assoc Prof Dr. Jerzy Domżał | SDN controllers | Best Researcher Award

Assoc Prof Dr. Jerzy Domżał, AGH University of Krakow, Poland

Dr. Domżał is a distinguished academic in Telecommunications with a robust educational background, including a Masterā€™s, Ph.D., and Habilitation from AGH University of Krakow. As the Director of the Institute of Telecommunications since 2020, he has demonstrated significant leadership and expertise. His research, which addresses critical issues in optical networks and future internet technologies, is reflected in over 35 published articles, two patents, and three authored books. Dr. Domżał’s involvement in major European research projects and his numerous accolades, including scholarships from the Polish Minister of Science and Higher Education and a science award from POLITYKA magazine, underscore his contributions to advancing telecommunications infrastructure. His roles on various organizational committees further highlight his active engagement in the research community.

Professional Profile:

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Suitability for the Award

Dr. Jerzy Domżał is exceptionally suited for the Research for Best Researcher Award due to his extensive research experience, impactful contributions to the field of telecommunications, and leadership roles in both academic and professional settings. His work on network congestion control, optical networks, and flow-aware networks aligns well with the award’s criteria, showcasing his dedication to advancing telecommunications research.

Educational Background:

Dr. Domżałā€™s educational qualifications include a Masterā€™s degree, Ph.D., and Habilitation in Telecommunications from AGH University of Krakow, showcasing a strong academic foundation in his field.

Professional Experience and Leadership:

His career trajectory includes roles as Research Assistant, Assistant Professor, and Associate Professor at AGH University of Krakow. He has served as the Director of the Institute of Telecommunications since 2020, reflecting his leadership and expertise in the field.

Research Contributions and Projects:

Dr. Domżał has been involved in several significant European research projects (e.g., Nobel, SmoothIT, EuroNF, e-Photon/ONe(+), BONE), focusing on optical networks, traffic engineering, and future internet technologies. His research addresses critical issues like network congestion control and flow-based services, which are crucial for advancing telecommunications infrastructure.

Publications and Patents:

He has published over 35 articles in JCR-listed journals, contributed to two patents and seven patent applications, and authored three books. His work has been recognized with numerous citations, highlighting the impact and relevance of his research.

Awards and Recognitions:

Dr. Domżał has received several prestigious awards, including scholarships from the Polish Minister of Science and Higher Education, a grant from the National Centre for Research and Development, and a science award from POLITYKA magazine. These accolades reflect his outstanding contributions to the field.

Organizational and Committee Roles:

His roles as Co-chair for GLOBECOM symposia, Local Organizing Committee Chair for ITC’2012, and member of technical program committees for IEEE conferences demonstrate his active engagement in shaping the research landscape and contributing to the advancement of telecommunications.

Publication Top Notes:

  • Title: A Survey on Methods to Provide Multipath Transmission in Wired Packet Networks
    • Year: 2015
    • Cited by: 36
  • Title: New Congestion Control Mechanisms for Flow-Aware Networks
    • Year: 2008
    • Cited by: 27
  • Title: QoS-Aware Net Neutrality
    • Year: 2009
    • Cited by: 25
  • Title: A Survey on Methods to Provide Interdomain Multipath Transmissions
    • Year: 2016
    • Cited by: 24
  • Title: Flow-Aware Multi-Topology Adaptive Routing
    • Year: 2014
    • Cited by: 24

 

Dr. Yasir AlKubaisi | Efficient Networking | Best Researcher Award

Dr. Yasir AlKubaisi | Efficient Networking | Best Researcher Award

Dr. Yasir AlKubaisi, Dubai Academic Health Corporation, United Arab Emirates

Dr. Yasir AlKubaisi is a distinguished electrical engineer and sustainable energy expert currently serving at the Dubai Academic Health Corporation, UAE. With a Ph.D. in Electrical Engineering from University Putra Malaysia, his research has significantly advanced energy harvesting systems. He also holds an MSc in Computer Engineering and a BSc in Electrical and Computer Engineering from the University of Technology, Baghdad. Since 2009, Dr. AlKubaisi has been pivotal in implementing sustainable projects within Dubai’s healthcare sector, including the Sustainable Blood Donation Bus. His extensive skills in project management, data analysis, and system design are complemented by his proficiency in LEED standards and various technical tools like MATLAB and AutoCAD. Recognized with numerous awards, including the MDIP Best Researcher Award in 2024, Dr. AlKubaisi’s work focuses on sustainable energy, electrical and control engineering, and robotics and automation.

Professional Profile:

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šŸŽ“ Education:

PhD: Electrical Engineering, University Putra Malaysia (UPM), May 2020.,Dissertation: “Gravitational Energy Harvesting System Based on Multistage Braking Technique for Multilevel Elevator Car Parking Building.”,MSc: Computer Engineering, University of Technology, Baghdad, Iraq, May 2005.,BSc: Electrical and Computer Engineering, University of Technology, Baghdad, Iraq, June 1994

šŸ’¼ Work Experience:

Dubai Academic Health Corporation, Dubai, UAE (2009-present):,Sustainable Engineer, Corporate Environmental Health-Safety & Sustainability Dept.,Key projects include the Sustainable Blood Donation Bus and various energy-saving initiatives.,Dubai Health Authority, Dubai, UAE (2009-2017),Various roles in the Engineering Department, focusing on project management, sustainability, and quality control.,Higher Education Computer Center, Iraq (1994-2007):,Significant experience in overseeing design solutions and managing technical teams.

šŸŒ Skills:

  • trong project management and technical skills including data analysis, system design, and process improvement.
  • Proficient in LEED standards, ISO, and JCI requirements for healthcare buildings.
  • Skilled in MATLAB, MS Office Suite, AutoCAD, and 3D Max

šŸ† Awards & Recognition:

  • MDIP Best Researcher Award, International Research Awards on Sensing Technology, 2024
  • Reviewer Recognition, Elsevier “Journal of Cleaner Production”, 2023
  • Various Certificates of Appreciation from Dubai Health Authority for environmental and sustainability contributions.

šŸ” Research Focus:

Publication Top Note:

 

 

 

Prof. Xin Kang | Social Media & Networks | Best Researcher Award

Prof. Xin Kang | Social Media & Networks | Best Researcher Award

Prof. Xin Kang, Tokushima University, Japan

āœØ Dr. Xin Kang is a distinguished scholar in Information Science and Intelligent Systems, holding a PhD from Tokushima University, earned in 2013 under Prof. Fuji Ren’s guidance. His dissertation, “Analyzing the Complex Emotions and Emotion-Related Topics from Texts,” showcased his expertise in emotional nuances. Prior, he obtained a Master’s degree in Pattern Recognition and Intelligent Systems from Beijing University of Posts and Telecommunications in 2009. šŸŽ“ Dr. Kang, currently an Assistant Professor at Tokushima University, has a rich academic journey marked by commitment to unraveling language intricacies and emotions. His accolades include the 2020 Best Contribution Award and the 2019 Best Presentation Award. šŸ† With a focus on affective computing and neuro-symbolic AI, Dr. Kang’s research aligns with his passion for developing Trustworthy AI for mental healthcare. šŸ¤– His diverse work experience includes a postdoctoral fellowship at Tongji University, emphasizing his interdisciplinary expertise, and his dedication is evident in his impactful contributions to the dynamic intersection of artificial intelligence and affective computing. šŸ‘Øā€šŸ”¬

šŸŽ“Ā Education :

Dr. Xin Kang, a distinguished scholar in the field of Information Science and Intelligent Systems, earned his PhD from Tokushima University in 2013 under the guidance of Prof. Fuji Ren. His dissertation, titled “Analyzing the Complex Emotions and Emotion-Related Topics from Texts,” showcased his expertise in delving into intricate emotional nuances within textual content. Prior to his doctoral studies, Dr. Kang obtained his Master’s degree in Pattern Recognition and Intelligent Systems from Beijing University of Posts and Telecommunications in 2009, supervised by Prof. Xiaojie Wang. His thesis, “Research of Chinese and Japanese Question Classification,” reflected his early contributions to understanding linguistic nuances across different languages. Dr. Kang’s academic journey has been marked by a commitment to unraveling the intricacies of language and emotions, making him a notable figure in the intersection of information science and emotional analysis. šŸŽ“šŸ“š

šŸŒĀ Professional Profiles :

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šŸ‘Øā€šŸ« Work Experience :

Prof. Xin Kang has established himself as a dedicated academic with a rich work history. Currently serving as an Assistant Professor at Tokushima University’s Institute of Technology and Science since 2015, he continues to contribute to the academic community through teaching and research. Prior to his current role, from 2014 to 2016, Prof. Kang held a Postdoctoral Fellowship at Tongji University in the Department of Electrical Engineering, showcasing his interdisciplinary expertise. In the year following the completion of his PhD, he served as a Foreign Researcher at Tokushima University’s Institute of Technology and Science in 2013-2014, further solidifying his ties with the institution. Prof. Kang’s diverse work experience reflects his commitment to both academic and practical aspects of his field, making him a valuable asset to the institutions he has been associated with. šŸ«šŸ”¬

šŸ† Awards and Honors :

Prof. Xin Kang, a distinguished figure in the field of natural language processing and knowledge engineering, has garnered numerous accolades throughout his illustrious career. šŸ† In 2020, he received the Best Contribution Award at the 15th International Conference on Natural Language Processing and Knowledge Engineering, showcasing his impactful contributions to the field. šŸŒ His expertise in text emotion classification was recognized in 2019 with the Best Presentation Award at the 4th International Symposium on Artificial Intelligence and Robotics. šŸŽ¤ Prof. Kang’s commitment to excellence extends to 2017 when he earned the Best Paper Award for his work on training Recurrent Neural Network Models at the 12th International Conference on Natural Language Processing and Knowledge Engineering. šŸ“„ Beyond these accolades, his global perspective was acknowledged in 2013 with the International Exchange Research Award from Tokushima University. šŸŒ Prof. Kang’s journey in academia began with the 2011 Best Paper Award at the 7th International Conference on Natural Language Processing and Knowledge Engineering. šŸ“š His academic prowess was further recognized with the Japanese Government Scholarship in 2009. šŸŽ“ Prof. Kang’s early achievements include an Honorable Mention in the Mathematical Contest in Modeling (MCM) in 2005 and being recognized as an Outstanding Student at Northeastern University the same year. šŸ… In 2004, he clinched the Second Prize in the China Undergraduate Mathematical Contest in Modeling, laying the foundation for a remarkable career marked by excellence and recognition. šŸ‘Øā€šŸ«āœØ

šŸ’» Research Experience :

Prof. Xin Kang, an accomplished researcher, has made significant contributions in the realm of affective computing and neuro-symbolic AI at Ren Laboratory, Tokushima University, since 2015. šŸ§  His pioneering work includes a data-efficient learning approach that integrates symbolic knowledge into deep neural networks for accurate and explainable affective computing. šŸ¤– Prof. Kang’s expertise extends to early depression detection, where his Time-Aware Affective Memories model, featuring a unique learning target latency penalty, ranked first in the CLEF-2022 Early Detection of Depression Task. šŸŒŸ His impactful research spans diverse areas, from affective corpus construction using Optimal Transport Divergence-based sample selection to achieving top rankings in NTCIR-15 and NTCIR-16 Dialogue Evaluation Tasks with innovative approaches in affective dialogue generation and automatic dialogue quality evaluation. šŸ—£ļøšŸ“Š Furthermore, his work on user intent understanding in short texts, visual question answering in the medical domain, and affective state analysis in social network users showcases his versatility and excellence in various domains. šŸ“š Prof. Kang’s earlier research at Miao Laboratory, Tongji University, and Ren Laboratory delved into affective state analysis in social network users and suicidal risk evaluation based on affective computing, earning him accolades and publications in esteemed journals. šŸ“ˆ His continuous dedication is evident in his exploration of semi-supervised learning for affective state modeling in social network users, contributing to journals like IEEJ Transactions on Electrical and Electronic Engineering and Information Technology and Management. šŸŒšŸ‘Øā€šŸ”¬ Prof. Xin Kang’s research journey exemplifies innovation and impact in the dynamic intersection of artificial intelligence and affective computing. šŸ‘āœØ

šŸ§ Research Interests šŸ”¬šŸŒ :

Prof. Xin Kang is at the forefront of cutting-edge research, focusing on a diverse array of captivating topics within artificial intelligence. šŸ¤– His research interests span Trustworthy AI for mental healthcare, where he endeavors to create reliable and ethical solutions for enhancing mental well-being. šŸ’” Proficient in Affective Computing, he explores the intricate interplay between emotion and technology, fostering empathetic AI systems. šŸ§  The integration of Neuro-Symbolic AI and Deep Learning reflects his commitment to developing advanced models that combine symbolic reasoning with neural networks for enhanced performance and interpretability. šŸŒ Active Learning, Natural Language Processing, and Dialogue Systems constitute key areas where Prof. Kang excels, driving innovation in intelligent interactions and information processing. šŸ—£ļøšŸ“š His expertise extends to Probabilistic Graphical Models, showcasing a keen interest in robust probabilistic reasoning for AI applications. šŸ“Š Prof. Kang’s research also explores the dynamic landscape of Social Media and Networks, contributing to a deeper understanding of human interactions in digital spaces. šŸŒāš™ļø With a specific focus on Trustworthy AI for Mental Healthcare, Prof. Xin Kang’s research journey is a testament to his commitment to advancing AI for societal well-being and mental health. šŸ‘Øā€šŸ”¬

šŸ“šĀ Publication Impact and Citations :

Scopus Metrics:

  • šŸ“Ā Publications: 76 documents indexed in Scopus.
  • šŸ“ŠĀ Citations: A total of 461 citations for his publications, reflecting the widespread impact and recognition of Dr. Xin Kangā€™s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 707 šŸ“–
    • h-index: 14 šŸ“Š
    • i10-index: 19 šŸ”
  • Since 2018:
    • Citations: 581 šŸ“–
    • h-index: 13 šŸ“Š
    • i10-index: 14 šŸ”

šŸ‘Øā€šŸ« A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. šŸŒšŸ”¬

Publications Top NotesĀ  :

1.Ā  Examining accumulated emotional traits in suicide blogs with an emotion topic modelĀ 

Published in IEEE Journal of Biomedical and Health Informatics

Published Year : 2015, Cited by 83

2.Ā  Surface defect detection of steel strips based on classification priority YOLOv3-dense networkĀ 

Published in Ironmaking & Steelmaking

Published Year : 2021, Cited by 60

3.Ā  Object detection based on SSD-ResNetĀ 

Published in 2019 IEEE 6th International Conference on Cloud Computing and Intelligence

Published Year : 2019, Cited by 55

4.Ā  Exploring latent semantic information for textual emotion recognition in blog articles

Published in IEEE/CAA Journal of Automatica Sinica

Published Year : 2017, Cited by 45

5.Ā  Employing hierarchical Bayesian networks in simple and complex emotion topic analysisĀ 

Published in Computer Speech & Language

Published Year : 2013, Cited by 43