Assoc Prof Dr. Saeed Emami | Network Optimization | Best Researcher Award

Assoc Prof Dr. Saeed Emami | Network Optimization | Best Researcher Award

Prof Dr. Saeed Emami, Babol Noshirvani University of Technology, Iran

Dr. Saeed Emami is an Associate Professor in the Department of Industrial Engineering at Babol Noshirvani University of Technology, Iran. He received his Ph.D. in Industrial Engineering from Isfahan University of Technology in 2015, focusing on order acceptance and scheduling problems in make-to-order systems. With a strong background in optimization and uncertainty, his research interests span various areas, including robust optimization, production planning, facility planning, and supply chain management. As Vice-Chancellor of the Faculty of Materials and Industrial Engineering since January 2020, he plays a key role in academic leadership. With a wealth of teaching experience in engineering courses, he also serves as a supervisor and advisor for numerous master’s theses, addressing diverse topics such as healthcare scheduling, cloud manufacturing, and green supply chain planning. Emami’s contributions extend to the development and application of metaheuristic algorithms, simulation, and multi-criteria decision-making in industrial engineering.

šŸŒ Professional Profiles :Ā 

Google Scholar

Scopus

Orcid

šŸŽ“Ā Education:

    • Ph.D. in Industrial Engineering, Isfahan University of Technology, Iran (2015)
    • M.S. in Industrial Engineering, Isfahan University of Technology, Iran (2008)
    • B.S. in Industrial Engineering, Isfahan University of Technology, Iran (2004)

šŸ“š Teaching Experience:

  • Courses at Babol Noshirvani University of Technology since 2010
    • Engineering Economy, Probability theory, Statistics
    • Computer Applications in Industrial Engineering, Production planning
    • Linear algebra, Simulation, Decision analysis
    • Inventory control, Decision making in healthcare systems
    • Computer simulation, modeling, and optimization, Combinatorial optimization

šŸ­ Work Experience:

  • Current Position: Associate Professor at Babol Noshirvani University of Technology (since Sep 2015)
  • Supervisor of Master Theses: Diverse topics in Industrial Engineering, including nurse scheduling in the Covid-19 pandemic and integrated production and distribution planning in a green closed-loop supply chain.
  • Advisor of Master Theses: Covering areas like home health care service planning, flexible flow shop scheduling, order acceptance in make-to-order systems, and more.

šŸ§  Research Interests:

Dr. Saeed Emami, an accomplished Associate Professor at Babol Noshirvani University of Technology, is deeply immersed in the realms of industrial engineering. His intellectual pursuits span a diverse spectrum, from the intricacies of optimization and robust techniques to the art of decomposition algorithms like Benders and Lagrangian relaxation. With a keen focus on production planning, scheduling, and facility planning, he navigates the complexities of supply chain management, employing metaheuristic algorithms such as Nested Partition and Genetic approaches. Dr. Emami’s academic canvas is further enriched by his exploration of simulation methodologies and the nuanced landscape of multi-criteria decision making. šŸŒšŸ“Š

šŸ“šĀ Publication Impact and Citations :Ā 

Scopus Metrics:

  • šŸ“Ā Publications: 19 documents indexed in Scopus.
  • šŸ“ŠĀ Citations: A total of 345 citations for his publications, reflecting the widespread impact and recognition of Dr. Saeed Emamiā€™s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 471 šŸ“–
    • h-index: 9 šŸ“Š
    • i10-index: 9 šŸ”
  • Since 2018:
    • Citations: 417 šŸ“–
    • h-index: 8 šŸ“Š
    • i10-index: 8 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. Multi-objective Fuzzy Robust Optimization Approach to Sustainable Closed-Loop Supply Chain Network Design
    • Authors: S Nayeri, MM Paydar, E Asadi-Gangeraj, S Emami
    • Published Year: 2020
    • Journal: Computers & Industrial Engineering
    • Cited By: 141
  2. Managing a new multi-objective model for the dynamic facility layout problem
    • Authors: S Emami, AS Nookabadi
    • Published Year: 2013
    • Journal: International Journal of Advanced Manufacturing Technology
    • Cited By: 82
  3. Wheat sustainable supply chain network design with forecasted demand by simulation
    • Authors: F Motevalli-Taher, MM Paydar, S Emami
    • Published Year: 2020
    • Journal: Computers and Electronics in Agriculture
    • Cited By: 55
  4. A Benders decomposition approach for order acceptance and scheduling problem: a robust optimization approach
    • Authors: S Emami, G Moslehi, M Sabbagh
    • Published Year: 2017
    • Journal: Computational and Applied Mathematics
    • Cited By: 37
  5. Metaheuristic algorithms to allocate and schedule of the rescue units in the natural disaster with fatigue effect
    • Authors: S Nayeri, E Asadi-Gangraj, S Emami
    • Published Year: 2019
    • Journal: Neural Computing and Applications
    • Cited By: 30

 

 

 

 

 

 

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 :

Google Scholar

Scopus

ORCID

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

 

 

 

 

Mrs. Mahdieh Ghasemlou | Network Optimization | Best Researcher Award

Mrs. Mahdieh Ghasemlou | Network Optimization | Best Researcher Award

Mrs. Mahdieh Ghasemlou, University of Birjand, Iran

šŸ‘©ā€šŸŽ“ Mrs. Mahdieh Ghasemlou is a Ph.D. student in Electrical Engineering-Communications Technology at the University of Birjand, Iran, embarking on a scholarly journey with a focus on “NOMA multi-user transceivers for 5G mobile communication networks.” šŸŒ Under the guidance of mentors Dr. Nasser Neda and Dr. Jalil Seifali Harsini, her dedication to advancing knowledge in electrical engineering is evident. šŸš€ Prior to her Ph.D., Mahdieh achieved a Master of Science in Electrical Engineering-Communications from the Islamic Azad University Tehran South branch in Tehran, Iran. šŸ“š Her academic commitment extends to cutting-edge areas like NOMA and 5G communication networks. šŸ’” As a devoted researcher, Mahdieh explores a diverse spectrum of wireless communications, including ultra-wideband (UWB) techniques for ranging and localization, signal processing innovations, and resource management strategies in NOMA systems. šŸ“” Her multifaceted expertise significantly contributes to the dynamic evolution of wireless technologies. šŸŒŸ

šŸŽ“Ā Education :Ā 

šŸŽ“ Mrs. Mahdieh Ghasemlou is currently on a scholarly pursuit as a Ph.D. student in Electrical Engineering-Communications Technology at the University of Birjand, Iran. šŸŒ Her doctoral thesis, titled “NOMA multi-user transceivers for 5G mobile communication networks,” is under the supervision of esteemed mentors Dr. Nasser Neda and Dr. Jalil Seifali Harsini. šŸ“š Prior to her Ph.D., Mahdieh earned a Master of Science in Electrical Engineering-Communications from the Islamic Azad University Tehran South branch in Tehran, Iran, in February 2013. šŸš€ Her academic journey reflects a deep commitment to advancing knowledge in the field of electrical engineering, particularly in cutting-edge areas like NOMA and 5G communication networks. šŸ“”šŸ’”

šŸŒ Professional Profiles :Ā 

Google Scholar

šŸ§  Research Interests šŸ”¬šŸŒ :

šŸ“” Mrs. Mahdieh Ghasemlou is a dedicated researcher with a broad spectrum of interests spanning the dynamic field of wireless communications. šŸŒ Her expertise encompasses ultra-wideband (UWB) communications, where she explores advanced techniques for ranging and localization. šŸ“¶šŸ’¬ Mahdieh’s proficiency extends to signal processing, delving into innovative approaches to enhance communication systems. šŸ’” Moreover, her research interests include NOMA systems (Non-Orthogonal Multiple Access), focusing on optimizing resource management strategies for improved efficiency and performance. šŸš€ With a diverse range of interests, Mahdieh contributes significantly to the evolving landscape of wireless technologies and signal processing. šŸŒŸ

Publications Top NotesĀ  :

1.Ā  An improved method for TOA estimation in TH-UWB system considering multipath effects and interference

Publication Source: JOURNAL OF INFORMATION SYSTEMS AND TELECOMMUNICATION (JIST) 2 (15), 23-29

Year: 2014, Cited By: 2

2.Ā  A New Method of TOA Estimation in TH_UWB Systems with Multipath Channel and in the Presence of interference

Publication Source: IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING 21, 1-6

Year: 2013, Cited By: 1

 

 

 

 

 

Network Dynamics Innovator Award

Network Dynamics Innovator Award

Introduction: Welcome to the Network Dynamics Innovator Award, where we celebrate the trailblazers in the ever-evolving realm of network technology. This prestigious award recognizes individuals who have demonstrated exceptional innovation, leadership, and impact in the field of network dynamics.

Eligibility: Open to professionals, researchers, and academics globally, the Network Dynamics Innovator Award is designed for individuals making significant contributions to the advancement of network technologies.

Age Limits, Qualification, and Publications: There are no age limits for this award. Qualifications include a proven track record of innovation in network dynamics, demonstrated through publications, patents, or substantial contributions to the field.

Requirements: Nominees must submit their bio, relevant abstract, supporting files, and any additional materials that showcase their impact on network dynamics.

Evaluation Criteria: A distinguished panel of experts will evaluate nominees based on the originality, impact, and scalability of their contributions to network dynamics. Innovations in research, implementation, or business applications will be key focal points.

Submission Guidelines: Ensure submissions include a comprehensive biography, an abstract highlighting key achievements, and relevant supporting files. Submissions can be made online through our dedicated platform.

Recognition: Recipients of the Network Dynamics Innovator Award will be prominently recognized in industry publications, at relevant conferences, and through our online platforms, enhancing their visibility and influence in the field.

Community Impact: This award not only acknowledges individual brilliance but also celebrates those whose innovations have positively impacted the broader network technology community, fostering collaboration and growth.

Biography: Nominees are encouraged to submit a comprehensive biography, outlining their journey, contributions, and vision for the future of network dynamics.

Network Innovator Excellence Award Introduction: Welcome to the Network Innovator Excellence Award, a prestigious accolade honoring trailblazers in the dynamic field of network protocols. This award celebrates those whose groundbreaking
Academic Leadership in Network Protocols Award Introduction: Welcome to the Academic Leadership in Network Protocols Award, an esteemed recognition that celebrates individuals who have demonstrated outstanding leadership and scholarly contributions
Industry Impact Award for Network Innovations Introduction: Welcome to the Industry Impact Award for Network Innovationsā€”a recognition that celebrates the profound influence of individuals or entities on the industry through
Business Trailblazer in Network Protocols Award Introduction: Welcome to the Business Trailblazer in Network Protocols Award, an esteemed recognition celebrating the visionaries and pioneers who have transformed the business landscape
Research and Innovation Achievement Award in Networking Introduction: Welcome to the Research and Innovation Achievement Award in Networkingā€”an esteemed recognition that applauds the outstanding contributions of individuals and teams who
Network Excellence Achievement Award Introduction: Welcome to the Network Excellence Achievement Awardā€”an accolade that celebrates individuals and entities for their outstanding achievements and contributions in the field of network excellence.
Innovation in Networking Award Introduction: Welcome to the Innovation in Networking Awardā€”an esteemed recognition that honors pioneers in the field who have demonstrated exceptional innovation and creativity in advancing networking
Protocol Pioneer Achievement Award Introduction: Welcome to the Protocol Pioneer Achievement Award, an esteemed recognition dedicated to individuals who have pioneered significant advancements in the field of protocols. This award
Academic Excellence in Network Protocol Studies Award Introduction: Welcome to the Academic Excellence in Network Protocol Studies Awardā€”an esteemed recognition that celebrates individuals who have demonstrated exceptional academic prowess in
Innovative Solutions in Network Industries Award Introduction: Welcome to the Innovative Solutions in Network Industries Awardā€”a prestigious recognition that celebrates individuals, companies, and organizations that have pioneered transformative solutions in