Prof. Xiaodi Liu | Cloud model Awards | Best Researcher Award

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Prof. Xiaodi Liu | Cloud model Awards | Best Researcher Award

Prof. Xiaodi Liu, Anhui University of Technology, China

Dr. Xiaodi Liu is a distinguished Professor in the Department of Data Science at the School of Microelectronics & Data Science, Anhui University of Technology. His research interests span across big data, decision analysis, emergency management, complex system modeling, and social networks. Dr. Liu teaches courses such as Decision Analysis, Fuzzy Mathematics, Linear Algebra, and Advanced Mathematics. He has secured multiple prestigious grants, including those from the National Social Science Foundation of China, National Natural Science Foundation of China, and the Humanities and Social Sciences Foundation of the Ministry of Education of China. His dedication to research and teaching significantly contributes to advancements in data science.

Professional Profile:

Orcid
Scopus

šŸŽ“Ā Education

Prof. Xiaodi Liu completed his Ph.D. in Economics and Management at Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, CN, from 2012 to 2015. His research focuses on areas within economics and management, reflecting his commitment to advancing knowledge in these fields.

šŸ‘Øā€šŸ« Employment

Prof. Xiaodi Liu is currently employed at Anhui University of Technology in Ma’anshan, China, where he serves in the School of Mathematics & Physics. His professional focus encompasses research and teaching within the academic realm, contributing to the advancement of mathematical and physical sciences at his institution.

šŸ†Ā Research Interests

Prof. Xiaodi Liu is a dedicated researcher with a diverse array of interests spanning big data, decision analysis, emergency management, complex system modeling, and social networks. With a robust academic background and extensive research experience, Prof. Liu contributes significantly to advancing knowledge in these critical areas, aiming to enhance understanding and improve practices in complex systems and societal challenges.

Publication Top Notes:

  • Title: Large group emergency decision-making with bi-directional trust in social networks: A probabilistic hesitant fuzzy integrated cloud approach
    • Year: 2024
    • Cited By: 4
  • Title: Analysis of distance measures in intuitionistic fuzzy set theory: A line integral perspective
    • Year: 2023
    • Cited By: 5
  • Title: A two-stage multi-attribute group consensus model based on distributed linguistic assessment information from the perspective of fairness concern
    • Year: 2023
    • Cited By: 1
  • Title: Two-rank multi-attribute group decision-making with linguistic distribution assessments: An optimization-based integrated approach
    • Year: 2023
    • Cited By: 3
  • Title: Large group decision-making based on interval rough integrated cloud model
    • Year: 2023
    • Cited By: 8

 

 

Mrs. Geetha Rani | Cloud Network Award | Best Researcher Award

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Mrs. Geetha Rani | Cloud Network Award | Best Researcher Award

Mrs. Geetha Rani, Gitam University, India

šŸŒŸ Mrs. Geetha Rani, hailing from Gitam University, India, is a distinguished academic with a Ph.D. in Computer Science and Engineering. Her doctoral thesis, “Ensuring Data Storage Security in Cloud Computing using Cryptographic Mechanisms,” underscores her expertise in the realm of cybersecurity. With an MBA in Human Resources and a plethora of certifications from platforms like NPTEL and Coursera, she continually enriches her knowledge base. Mrs. Geetha Rani’s prowess extends beyond academia; she’s renowned for her contributions to NBA and NAAC criteria work, alongside curriculum supervision for autonomous syllabi. Her career embodies a harmonious blend of teaching, research, and administrative excellence. šŸŽ“

Professional Profile:

Google scholar

Orcid

Educational Background šŸŽ“

  • Ph.D. (Computer Science and Engineering) – Gitam University, Nagandenahalli, Bengaluru (Submitted Thesis: “Ensuring Data Storage Security in Cloud Computing using Cryptographic Mechanisms”)
  • MBA (Human Resources) – Acharya Nagarjuna University, Guntur (2011-2013)

Research and Publications šŸ“

Mrs. Geetha Rani has guided numerous research projects and published articles in international journals and conferences. Her research focuses on data storage security in cloud computing using cryptographic mechanisms.

Certifications šŸ“œ

She has completed various certifications and online courses from platforms like NPTEL and Coursera, enhancing her knowledge and skills in her field.

Achievements and Expertise šŸŒŸ

Mrs. Geetha Rani is well-known for her contributions to NBA and NAAC criteria work and curriculum supervision for autonomous syllabi. She has consistently demonstrated excellence in teaching, research, and academic administration throughout her career.

Publication Top Notes:

  1. Using GitHub and Grafana Tools: Data Visualization (DATA VIZ) in Big Data
    • Published in: Computer Vision and Robotics: Proceedings of CVR 2022
    • Year: 2023
    • Summary: This paper explores the use of GitHub and Grafana tools for data visualization in big data contexts.
  2. A Survey of Recent Cloud Computing Data Security and Privacy Disputes and Defending Strategies
    • Published in: CSCT
    • Year: 2022
    • Summary: This survey addresses recent disputes in cloud computing data security and privacy, along with strategies for defense.
  3. A Practical Approach of Recognizing and Detecting Traffic Signs using Deep Neural Network Model
    • Published in: 2022 Fourth International Conference on Emerging Research in Electronics
    • Year: 2022
    • Summary: The study presents a deep neural network model for recognizing and detecting traffic signs.
  4. To Increase Security and Privacy, the QAES Encryption Algorithm is used for Storage of Data for Cloud Computing
    • Published in: 2022 IEEE 19th India Council International Conference (INDICON)
    • Year: 2022
    • Summary: This paper discusses the use of the QAES encryption algorithm to enhance data security and privacy in cloud computing.
  5. Air Quality Predictor to Reduce Health Risks and Global Warming
    • Published in: 2023 2nd International Conference on Automation, Computing and Renewable
    • Year: 2023
    • Summary: The publication focuses on an air quality predictor aimed at reducing health risks and mitigating global warming effects.

 

 

 

 

 

Prof Dr. Zhuzhong Qian | Cloud Networking | Best Researcher Award

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Prof Dr. Zhuzhong Qian | Cloud Networking | Best Researcher Award

Prof Dr. Zhuzhong Qian, Nanjing University, China

Dr. Zhuzhong Qian stands as a distinguished professor at the Department of Computer Science, Nanjing University, contributing significantly to the realm of computer science. šŸŽ“ As a member of the National Key Laboratory of Software New Technology and deputy director of the Network and Distributed Computing Committee of the Jiangsu Computer Society, he plays a pivotal role in advancing research and collaboration. šŸŒ Driven by a commitment to excellence, he was selected for Jiangsu Province’s 333 High-level Talent Training Program and conducted impactful research visits in Japan and Canada in 2008 and 2009, respectively. šŸŒ Dr. Qian’s leadership extends to various research projects, funded by esteemed entities like the National Natural Science Foundation and Ministry of Education-China Mobile Science Research Fund, showcasing his prowess in securing and executing critical initiatives. šŸ’” His extensive involvement in national and provincial scientific research projects, coupled with industry collaborations with giants like Huawei and Tencent, underscores his influence in bridging academia and industry. šŸ¤ Dr. Qian’s prolific research, with over 100 papers published in prestigious journals and conferences, has earned him several best paper awards and nominations. šŸ† His impact on student development is evident through the recognition of his doctoral students in the 2015 ACM China Outstanding Doctoral Dissertation Award and undergraduate students receiving the 2017 Jiangsu Province Outstanding Graduation Thesis First Prize. šŸ‘Øā€šŸ«šŸ”¬

šŸŽ“Ā Education :

Dr. Zhuzhong Qian is a distinguished individual with a Ph.D. degree in computer science from Nanjing University (NJU), earned in 2007. šŸŽ“ His academic journey reflects a commitment to excellence and a passion for advancing the field of computer science. Dr. Qian’s expertise undoubtedly contributes to the ever-evolving landscape of technology, making him a noteworthy figure in the realm of academia. šŸ‘Øā€šŸ’»šŸ”

šŸŒĀ Professional Profiles :

Scopus

Google Scholar

šŸ’» Teaching :

Dr. Zhuzhong Qian’s dedication to education is evident through the diverse range of courses he has taught, showcasing his expertise in computer science. šŸ“š Over the years, he has guided students through courses such as Algorithms Design and Analysis, demonstrating his commitment to fostering a deep understanding of complex computational concepts. šŸ’» His involvement in the Elite Program of Computer Science since 2011, teaching Problem Solving, reflects a commitment to nurturing the intellectual growth of aspiring computer scientists. šŸŒ Additionally, Dr. Qian’s recent contributions include courses like Distributed Systems and Computational Thinking in the fall of 2021, demonstrating his adaptability in addressing contemporary challenges in the field. šŸš€ Despite the NJU Online Judge being under maintenance, it underscores his engagement in practical platforms for hands-on learning. šŸ› ļø Dr. Zhuzhong Qian’s teaching portfolio reflects not only his comprehensive knowledge but also his passion for shaping the next generation of computer science professionals. šŸ‘Øā€šŸ«

šŸ§ Research Interests šŸ”¬šŸŒ :

Dr. Zhuzhong Qian’s research interests revolve around cutting-edge domains, with a focus on Distributed Systems, Cloud Computing, and Edge Computing. šŸŒ His exploration of Distributed Systems delves into the intricacies of networked computing, aiming to enhance the efficiency and reliability of interconnected systems. ā˜ļø In the realm of Cloud Computing, Dr. Qian contributes to the evolution of scalable and accessible computing resources, optimizing the utilization of cloud-based technologies. šŸš€ Furthermore, his interest in Edge Computing reflects a commitment to pushing the boundaries of computation, bringing processing closer to data sources for improved real-time responsiveness. šŸŒŸ Dr. Zhuzhong Qian’s research endeavors not only align with the forefront of technological advancements but also hold the promise of shaping the future landscape of distributed and decentralized computing systems. šŸ‘Øā€šŸ’»

šŸ“šĀ Publication Impact and Citations :

Scopus Metrics:

  • šŸ“Ā Publications: 169 documents indexed in Scopus.
  • šŸ“ŠĀ Citations: A total of 1,785 citations for his publications, reflecting the widespread impact and recognition of Dr. Zhuzhong Qian’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 2628 šŸ“–
    • h-index: 25Ā  šŸ“Š
    • i10-index: 60 šŸ”
  • Since 2018:
    • Citations: 1476 šŸ“–
    • h-index: 21 šŸ“Š
    • i10-index: 35 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  Energy efficient virtual machine placement algorithm with balanced and improved resource utilization in a data center

Journal: Mathematical and Computer Modelling, 2013

Cited by: 238

2.Ā  Joint configuration adaptation and bandwidth allocation for edge-based real-time video analytics

Journal: IEEE INFOCOM 2020-IEEE Conference on Computer Communications, 2020

Cited by: 147

3.Ā  Virtual network embedding with opportunistic resource sharing

Journal: IEEE Transactions on Parallel and Distributed Systems, 2013

Cited by: 133

4.Ā  An opportunistic resource sharing and topology-aware mapping framework for virtual networks

Journal: 2012 Proceedings IEEE INFOCOM

Cited by: 113

5.Ā  P3: Joint optimization of charger placement and power allocation for wireless power transfer

Journal: 2015 IEEE Conference on Computer Communications (INFOCOM)

Cited by: 101

 

 

 

 

Mr. Alessandro Ottino | Cloud Networking

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Mr. Alessandro Ottino : Leading Researcher in Cloud Networking

Mr. Alessandro Ottino, University College London, United Kingdom

šŸŽ“ Mr. Alessandro Ottino, Currently pursuing a Microsoft-funded Ph.D. at University College London (UCL) in optical systems and technologies for distributed deep learning. Focused on developing innovative optical topologies and technologies to enable effective training of large-scale deep neural networks with over 1 trillion parameters across thousands of accelerators in data centers.

šŸ’¼ Previously worked as a Post-graduate Teaching Assistant (PGTA) at UCL’s Electrical and Electronic Engineering (EEE) department from January to March 2020-2021. Engaged in teaching undergraduate modules in digital design (FPGA and embedded systems programming), Java, Object-Oriented Programming, and served as a guest lecturer in “Networks and Technologies for Distributed Deep Learning (DDL)” for the “Cloud and Edge Computing” MSc course.

šŸ’» Proficient in various software tools including Vivado, Quartus, Modelsim, Multisim, Lumerical, Alteryx, Tableau, and the Microsoft Office Suite. Passionate about pushing the boundaries of optical systems to enhance the capabilities of deep learning in distributed environments. šŸŒšŸ”¬

Professional Profiles : šŸŒ

Scopus

Linkedin

Google Scholar

šŸ† Awards :Ā 

šŸ† In March 2020, He was honored with the IEEE Best Undergraduate Project in Telecommunications for showcasing excellence and innovation in the field. This recognition underscored her dedication to pushing the boundaries of technology.

šŸŽ“ August 2019 brought the prestigious Dean’s List acknowledgment for outstanding academic achievements in the Electrical and Electronic Engineering (EEE) department at UCL. This recognition reflected her commitment to academic excellence and contributions to the field.

šŸ… In May 2019, He was awarded the First Cullen Prize for the Best Undergraduate Project in the EEE department at UCL. The project, focusing on “Artificial Intelligence Techniques for FPGA-Driven Interconnects,” highlighted her proficiency in integrating AI with hardware solutions.

šŸ”Ā Research Focus:

šŸŒ Distributed Systems

šŸŒ Optical Networks

šŸ”¬ Machine Learning

šŸ“šĀ Publication Impact and Citations :Ā 

Scopus Metrics:

  • šŸ“Ā Publications: 12 documents indexed in Scopus.
  • šŸ“ŠĀ Citations: A total of 19 citations for his publications, reflecting the widespread impact and recognition of Mr. Alessandro Ottinoā€™s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 44 šŸ“–
    • h-index: 4 šŸ“Š
    • i10-index: 1 šŸ”
  • Since 2018:
    • Citations: 44 šŸ“–
    • h-index: 4 šŸ“Š
    • i10-index: 4 šŸ”

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

Publications ( Top Note ) :

1.Ā  Time-domain learned digital back-propagation

Journal/Conference: 2020 IEEE Workshop on Signal Processing Systems (SiPS)

Published Year: 2020, Cited By: 10

2.Ā  Optimization of 125-m Heterogeneous Multi-Core Fibre Design Using Artificial Intelligence

Journal/Conference: IEEE Journal of Selected Topics in Quantum Electronics

Published Year: 2021, Cited By: 8

3.Ā  Traffic tolerance of nanosecond scheduling on optical circuit switched data center network

Journal/Conference: 2022 Optical Fiber Communications Conference and Exhibition (OFC)

Published Year:2022,Ā  Cited By: 6

4.Ā  Design optimization of uncoupled six-core fibers in standard cladding diameter using artificial intelligence

Journal/Conference: Optical Fiber Communication Conference

Published Year: 2021, Cited By: 4

5.Ā  RAMP: a flat nanosecond optical network and MPI operations for distributed deep learning systems

Journal/Conference: Optical Switching and Networking

Published Year: 2024,Cited By: 3

6.Ā  Design and transmission analysis of trench-assisted multi-core fibre in standard cladding diameter

Journal/Conference: Optics Express

Published Year: 2022,Cited By: 3

7.Ā  Experimental demonstration of learned time-domain digital back-propagation

Journal/Conference: arXiv preprint arXiv:1912.12197

Published Year: 2019,Cited By: 3

8.Ā  Optimal and Low Complexity Control of SOA-Based Optical Switching with Particle Swarm Optimisation

Journal/Conference: European Conference and Exhibition on Optical Communication

Published Year: 2022,Cited By: 2

9.Ā  Experimental Analysis on Variations and Accuracy of Crosstalk in Trench-Assisted Multi-core Fibers

Journal/Conference: arXiv preprint arXiv:2008.08034

Published Year: 2020,Cited By: 2

10.Ā  Genetic algorithm optimization of multi-core fibre transmission links based on silicon photonic transceivers

Journal/Conference: 2019 Optical Fiber Communications Conference and Exhibition (OFC)

Published Year: 2019, Cited By: 2