Kexue Sun | Graph Data Structures | Best Researcher Award 

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Prof. Kexue Sun | Graph Data Structures | Best Researcher Award 

Nanjing University of Posts and Communications | China

Prof. Kexue Sun is a distinguished Professor at the School of Electronic and Optical Engineering and the School of Flexible Electronics (Future Technologies), Nanjing University of Posts and Telecommunications (NJUPT). He earned his Ph.D. in Acoustics from the School of Physics, Nanjing University (2012–2018), an M.E. in Software Engineering from the Beijing University of Posts and Telecommunications (2004–2006), and a B.E. in Electronic Information Engineering from the Artillery Academy of the Chinese People's Liberation Army, Hefei (1998–2002). Prof. Sun has served NJUPT in various academic roles, including Lecturer (2007–2013), Associate Professor (2013–2020), and currently as Professor since 2020, with international experience as a Visiting Scholar at the Chinese University of Hong Kong (2018–2019). He is an active member of IEEE, a technical expert for high-tech enterprises in Jiangsu Province, and a review expert for the Degree and Graduate Education Development Center of the Ministry of Education, while also serving on the Specialized Committee on Biomedical Information Detection and Processing of the Jiangsu Society of Biomedical Engineering. His research spans Electronic Technology, FPGA Applications, Electrical and Electronic Experiments, Optoelectronic Information Materials, and Acoustic Devices. Prof. Sun has participated in over ten national and enterprise research projects, co-authored one monograph and seven textbooks, published more than 100 academic papers, and holds over 20 authorized Chinese invention patents. Additionally, he has made significant contributions to higher education research and teaching reform, leading more than ten national and provincial projects, publishing over 20 papers in this field, and earning prestigious honors such as the Teaching Model Award, the First Prize for Teaching Achievements at NJUPT, and the Special Prize for Teaching Achievements of Jiangsu Province.

Profiles: Orcid ID

Featured Publications

"Pressure Vessel Design Problem Using Improved Gray Wolf Optimizer Based on Cauchy Distribution"

"Heart Sound Classification Network Based on Convolution and Transformer"

"Optimization of Indoor Luminaire Layout for General Lighting Scheme Using Improved Particle Swarm Optimization"

Fahimeh Dabaghi Zarandi | Community Detection | Women Researcher Award

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Assist. Prof. Dr. Fahimeh Dabaghi Zarandi | Community Detection | Women Researcher Award

Assistant Professor, at Vali-e-Asr University of Rafsanjan, Iran📖

Dr. Fahimeh Dabaghi-Zarandi is an accomplished researcher and academic in software engineering, specializing in data mining, green communication, and IoT. With a Ph.D. from the Iran University of Science and Technology, she brings a rich academic background and a passion for leveraging technology to address complex problems. As an Assistant Professor at Vali-e-Asr University, she continues to inspire students and contribute to the field through innovative research and collaboration.

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Education Background🎓

Dr. Fahimeh Dabaghi-Zarandi holds a Ph.D. in Software Engineering from the Iran University of Science and Technology, Tehran, Iran, which she completed in September 2018. She earned her Master’s degree in Software Engineering from the prestigious Sharif University of Technology, Tehran, Iran, in August 2010, and her Bachelor’s degree in the same field from Ferdowsi University of Mashhad, Iran, in August 2008. Her academic journey reflects a consistent focus on software engineering, laying a strong foundation for her expertise in data mining, graph processing, and Internet of Things applications.

Professional Experience🌱

Dr. Fahimeh Dabaghi-Zarandi is an Assistant Professor at the Department of Engineering, Vali-e-Asr University of Rafsanjan, where she contributes to the advancement of computer engineering through teaching and research. She has actively participated in several national conferences on topics such as data mining and computational geometry, including the 16th CSI Computer Conference in Tehran (2011) and the Winter School on Computational Geometry at Amirkabir University (2009). Her involvement in these events reflects her commitment to staying at the forefront of developments in computer science and engineering.

Research Interests🔬

Dr. Dabaghi-Zarandi’s research focuses on:

  • Green Communication: Enhancing energy efficiency in communication systems.
  • Community Detection: Identifying clusters and patterns in large networks.
  • Data Mining: Extracting meaningful insights from large datasets.
  • Graph Processing: Algorithms and applications for analyzing graph structures.
  • Internet of Things (IoT): Developing intelligent solutions for interconnected systems.

Author Metrics 

Dr. Dabaghi-Zarandi’s publications have made significant contributions to her fields of interest, with her work cited by researchers worldwide. Her expertise in graph processing and community detection has been recognized in peer-reviewed journals and conferences, where she has shared her findings on the applications of data mining and IoT in sustainable technology

Publications Top Notes 📄

1. A survey on green routing protocols using sleep-scheduling in wired networks

  • Authors: F. Dabaghi, Z. Movahedi, R. Langar
  • Journal: Journal of Network and Computer Applications
  • Volume: 77
  • Pages: 106-122
  • Year: 2017
  • Citations: 47
  • Abstract: This paper provides a detailed survey of green routing protocols in wired networks, focusing on energy-saving methods achieved through sleep-scheduling mechanisms. The study reviews various techniques and evaluates their effectiveness, contributing valuable insights to the field of green networking.

2. Community detection in complex networks based on an improved random algorithm using local and global network information

  • Authors: F. Dabaghi-Zarandi, P. KamaliPour
  • Journal: Journal of Network and Computer Applications
  • Volume: 206
  • Article: 103492
  • Year: 2022
  • Citations: 11
  • Abstract: This work presents an enhanced random algorithm for community detection in complex networks. By integrating both local and global network information, the proposed method achieves higher accuracy and robustness compared to traditional approaches.

3. An energy‐efficient algorithm based on sleep‐scheduling in IP backbone networks

  • Authors: F. Dabaghi-Zarandi, Z. Movahedi
  • Journal: International Journal of Communication Systems
  • Volume: 30, Issue 13
  • Article: e3276
  • Year: 2017
  • Citations: 11
  • Abstract: This paper introduces an energy-efficient algorithm for IP backbone networks leveraging sleep-scheduling techniques. The algorithm optimizes energy consumption while maintaining network performance.

4. A dynamic traffic-aware energy-efficient algorithm based on sleep-scheduling for autonomous systems

  • Authors: F. Dabaghi-Zarandi, Z. Movahedi
  • Journal: Computing
  • Volume: 100, Issue 6
  • Pages: 645-665
  • Year: 2018
  • Citations: 7
  • Abstract: The study proposes a dynamic traffic-aware algorithm that enhances energy efficiency in autonomous systems by incorporating adaptive sleep-scheduling.

5. Local traffic-aware green algorithm based on sleep-scheduling in autonomous networks

  • Authors: F. Dabaghi-Zarandi
  • Journal: Simulation Modelling Practice and Theory
  • Volume: 114
  • Article: 102418
  • Year: 2022
  • Citations: 2
  • Abstract: This paper introduces a localized green algorithm tailored for autonomous networks. By integrating sleep-scheduling and traffic awareness, the proposed approach reduces energy consumption without compromising network performance.

Conclusion

Dr. Fahimeh Dabaghi-Zarandi is a highly deserving nominee for the Women Researcher Award due to her pioneering research in green communication, community detection, and energy-efficient algorithms. Her contributions address global challenges such as energy conservation and sustainable technology, making her work both impactful and timely.

With a clear trajectory of excellence and continuous innovation, Dr. Dabaghi-Zarandi exemplifies the qualities of a distinguished researcher. Addressing the identified areas for improvement would further amplify her achievements, but her existing body of work strongly supports her candidacy for this award.