Lidan Wang | Chaotic Cryptography | Best Researcher Award

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Prof. Lidan Wang | Chaotic Cryptography | Best Researcher Award

Supervisor at Southwest University, China

Summary:

Prof. Lidan Wang is a distinguished professor and doctoral supervisor in the College of Artificial Intelligence at Southwest University in Chongqing, China. She earned her B.E. degree in Automatic Control from Nanjing University of Science and Technology in 1999 and her Ph.D. in Computer Software and Theory from Chongqing University in 2008. Furthering her academic journey, she completed post-doctoral research at Chongqing University in 2012. Prof. Wang’s research focuses on artificial intelligence, particularly in the areas of artificial neural networks, neural morphological systems, memristor devices and systems, chaotic systems, and nonlinear circuit design. She has led over 20 significant research projects, including those funded by the National Key R&D Program and the National Natural Science Foundation of China.

 

Profile:

Education:

Prof. Lidan Wang earned her Bachelor of Science degree in Electrical Engineering from Nanjing University of Science and Technology, China, in 1996. She pursued her Master’s degree and Ph.D. in Electrical Engineering at Chongqing University, China, completing her Ph.D. in 2008. Additionally, Prof. Wang conducted post-doctoral research at Chongqing University from 2012 to 2014, further advancing her expertise in the field of artificial intelligence and neural networks.

Professional Experience:

Prof. Lidan Wang began her academic career as an Associate Professor at Southwest University, Chongqing, China, serving from 2008 to 2012. She was promoted to Professor in 2013, a position she continues to hold. In addition to her role at Southwest University, Prof. Wang has gained international experience through various visiting professorships, including at Imperial College London, Nanyang Technological University, Texas A&M University at Qatar, and the University of Tasmania. Her leadership extends beyond teaching and research, as she currently serves as the deputy director of the Chongqing Key Laboratory of Brain-like Computing and Intelligent Control, Secretary General of the Chongqing Artificial Intelligence Society, and Director of the Chongqing Young Science and Technology Leaders Association.

Research Interests:

Prof. Lidan Wang’s research interests lie primarily in the realm of artificial intelligence, with a strong focus on artificial neural networks and neural morphological systems. Her work explores memristor devices and systems, chaotic systems, and nonlinear circuit design. Prof. Wang is particularly engaged in advancing the understanding and application of these technologies, aiming to develop innovative solutions and systems that integrate these complex components. Her research contributes significantly to the fields of artificial intelligence and neural network technologies.

Skills:

Prof. Lidan Wang possesses advanced skills in artificial intelligence, encompassing artificial neural networks and neural morphological systems. She is proficient in the design and implementation of memristor devices and systems, as well as in the analysis and development of chaotic systems and nonlinear circuits. Her expertise extends to leading and managing research projects, having successfully undertaken numerous high-profile projects including National Key R&D Program subprojects and various funding initiatives. Additionally, Prof. Wang has a strong background in patent development and academic publishing, contributing to her distinguished reputation in the scientific community.

Conclution:

Given her exceptional research contributions, extensive publication record, numerous awards, and significant leadership roles, Prof. Lidan Wang is a highly deserving candidate for the Best Researcher Award. Her work not only advances the field of artificial intelligence but also inspires and influences the global research community.

Publication Tob Noted:

Memristor-based cellular nonlinear/neural network: design, analysis, and applications

  • Authors: S. Duan, X. Hu, Z. Dong, L. Wang, P. Mazumder
  • Journal: IEEE Transactions on Neural Networks and Learning Systems
  • Volume: 26, Issue 6
  • Pages: 1202-1213
  • Year: 2014
  • Citations: 297

Electronic nose feature extraction methods: A review

  • Authors: J. Yan, X. Guo, S. Duan, P. Jia, L. Wang, C. Peng, S. Zhang
  • Journal: Sensors
  • Volume: 15, Issue 11
  • Pages: 27804-27831
  • Year: 2015
  • Citations: 296

Exponential stability of complex-valued memristive recurrent neural networks

  • Authors: H. Wang, S. Duan, T. Huang, L. Wang, C. Li
  • Journal: IEEE Transactions on Neural Networks and Learning Systems
  • Volume: 28, Issue 3
  • Pages: 766-771
  • Year: 2016
  • Citations: 159

A novel memristive Hopfield neural network with application in associative memory

  • Authors: J. Yang, L. Wang, Y. Wang, T. Guo
  • Journal: Neurocomputing
  • Volume: 227
  • Pages: 142-148
  • Year: 2017
  • Citations: 158

Memristor model and its application for chaos generation

  • Authors: L. Wang, E. Drakakis, S. Duan, P. He, X. Liao
  • Journal: International Journal of Bifurcation and Chaos
  • Volume: 22, Issue 08
  • Article Number: 1250205
  • Year: 2012
  • Citations: 147

Volatile and nonvolatile memristive devices for neuromorphic computing

  • Authors: G. Zhou, Z. Wang, B. Sun, F. Zhou, L. Sun, H. Zhao, X. Hu, X. Peng, J. Yan, …
  • Journal: Advanced Electronic Materials
  • Volume: 8, Issue 7
  • Article Number: 2101127
  • Year: 2022
  • Citations: 129

Resistive switching memory integrated with amorphous carbon-based nanogenerators for self-powered device

  • Authors: G. Zhou, Z. Ren, L. Wang, J. Wu, B. Sun, A. Zhou, G. Zhang, S. Zheng, S. Duan, …
  • Journal: Nano Energy
  • Volume: 63
  • Article Number: 103793
  • Year: 2019
  • Citations: 126

Artificial and wearable albumen protein memristor arrays with integrated memory logic gate functionality

  • Authors: G. Zhou, Z. Ren, L. Wang, B. Sun, S. Duan, Q. Song
  • Journal: Materials Horizons
  • Volume: 6, Issue 9
  • Pages: 1877-1882
  • Year: 2019
  • Citations: 123

Capacitive effect: An original of the resistive switching memory

  • Authors: G. Zhou, Z. Ren, B. Sun, J. Wu, Z. Zou, S. Zheng, L. Wang, S. Duan, Q. Song
  • Journal: Nano Energy
  • Volume: 68
  • Article Number: 104386
  • Year: 2020
  • Citations: 118

 

Ahamed Ali S | Information Security | Best Researcher Award

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Dr. Ahamed Ali S, Information Security, Best Researcher Award

Doctorate at Easwari Engineering College, India

Dr. Ahamed Ali S is an accomplished academician and researcher in the field of Computer Science and Engineering (CSE). He holds a Ph.D. in CSE from Anna University, which he completed in 2019. Prior to his doctoral studies, he obtained his Master’s degree (M.E.) in CSE from Anna University, graduating with First Class with Distinction in 2005. Dr. Ahamed Ali S began his academic journey with a Bachelor’s degree (B.E.) in CSE from Bharathidasan University, where he achieved First Class honors in 1999.

With over 18 years of experience in academia, Dr. Ahamed Ali S has served in various capacities, including Assistant Professor roles at prestigious institutions such as SRM Easwari Engineering College and Velammal Engineering College in Chennai. He has also contributed as a Lecturer at Jerusalem Engineering College and Srinivasa Institute of Engineering and Technology. Throughout his career, he has taken on several responsibilities, including membership in professional bodies, participation in boards and advisory committees, and coordination of national conferences and events.

profile

Education

  • Ph.D. (CSE), Anna University, 2019 (Grade: NA)
  • M.E (CSE), Anna University, 2005 (First Class with Distinction)
  • B.E (CSE), Bharathidasan University, 1999 (First Class)
Professional Experience
Dr. Ahamed Ali S is a highly experienced academician and researcher with over 18 years of dedicated service in the field of Computer Science and Engineering (CSE). His professional journey includes significant roles at esteemed educational institutions in Chennai, India.

From March 2021 to the present, Dr. Ahamed Ali S has been serving as an Assistant Professor at SRM Easwari Engineering College, where he contributes to the academic and research activities in CSE. Prior to his current position, he held the position of Assistant Professor (Grade III) at Velammal Engineering College, Chennai, from July 2006 to February 2021, where he made notable contributions to the department.

Earlier in his career, Dr. Ahamed Ali S served as a Lecturer at Jerusalem Engineering College for 1 year and 6 months (from December 2004 to June 2006) and at Srinivasa Institute of Engineering and Technology for 2 years and 7 months (from December 2000 to July 2003). Throughout his tenure in academia, he has been actively involved in various administrative and academic responsibilities, including:

  • Serving as a member of the Placement Committee
  • Coordinating the National Board of Accreditation (NBA) Department
  • Overseeing NAAC Criteria V as Incharge
  • Fulfilling duties as the NIRF Coordinator
  • Acting as a Proctor
  • Serving as the Autonomous Coordinator for the department
  • Membership in the Course File Committee
  • Overseeing feedback mechanisms
  • Coordination as the LFC coordinator for Tech Mahindra

In addition to his academic roles, Dr. Ahamed Ali S is affiliated with professional bodies such as the International Association of Engineers (ID: 216052) and the Internet Society (ID: 194027). He actively contributes to the academic community as a reviewer for reputable journals like KSII Transactions on Internet and Information Systems and as a Technical Committee Member in various national conferences.

Dr. Ahamed Ali S is committed to his professional development and has obtained several certifications in cutting-edge technologies and educational methodologies, including Cloud Computing, Python for Data Science, NBA Accreditation, Software Testing, and Java Programming. He is certified by NITTR, Chennai, and ZANDIG TQM Solutions Pvt Ltd, Bangalore, and has completed the Cisco Networking Academy’s CCNA Exploration: Network Fundamentals course.

Research Interest

Dr. Ahamed Ali S’s research interests span a broad spectrum within the field of Computer Science and Engineering (CSE). With over 18 years of experience, his scholarly pursuits encompass several key areas of inquiry. Primarily, he delves into Artificial Intelligence (AI) and Machine Learning (ML), exploring the development and application of algorithms in natural language processing, computer vision, pattern recognition, and predictive analytics. Additionally, he investigates Data Science and Big Data Analytics, focusing on methodologies for analyzing large datasets across various domains. Dr. Ahamed Ali S is also engaged in research related to Internet of Things (IoT) and Sensor Networks, examining design principles, communication protocols, and energy-efficient solutions. Furthermore, his interests extend to cybersecurity, privacy-preserving technologies, and cryptography, addressing emerging challenges in safeguarding digital assets and sensitive information. Moreover, he explores advanced topics in deep learning, neural networks, computer vision, and image processing, aiming to enhance performance and interpretability for diverse applications. Dr. Ahamed Ali S’s research endeavors also encompass edge computing, distributed systems, blockchain technology, cloud computing, software engineering, and development methodologies. Through his interdisciplinary approach, he seeks to advance knowledge and contribute to the development of innovative solutions with real-world impact.

Publications 

Developing multi-path routing protocol in MANET using hybrid SM-CSBO based on novel multi-objective function

  • Journal: International Journal of Communication Systems
  • Year: 2023
  • DOI: 10.1002/DAC.5404
  • WOSUID: WOS:000896772000001
  • Contributors: Deepa Jeyaraj, Justindhas Yesudhasan, Ahamed Ali Samsu Aliar

Intelligent energy efficient vehicle automation system with sensible edge processing protocol in Internet of Vehicles using hybrid optimization strategy

  • Journal: Wireless Networks
  • Year: 2023
  • DOI: 10.1007/s11276-022-03204-5
  • Contributors: Deepa Jeyaraj, Ahamed Ali Samsu Aliar, Hemamalini S.

An Automated Detection of DDoS Attack in Cloud Using Optimized Weighted Fused Features and Hybrid DBN-GRU Architecture

  • Journal: Cybernetics and Systems
  • Year: 2022
  • DOI: 10.1080/01969722.2022.2157603
  • WOSUID: WOS:000914201500001
  • Contributors: Ahamed Ali Samsu Aliar, Moorthy Agoramoorthy, Y. Justindhas

Effective intrusion detection system for IoT using optimized capsule autoencoder model

  • Journal: Concurrency and Computation: Practice and Experience
  • Year: 2022
  • DOI: 10.1002/cpe.6918
  • EID: 2-s2.0-85126000835
  • Contributors: C.U. Om Kumar, J. Durairaj, S.A. Ahamed Ali, Y. Justindhas, S. Marappan

Survey on Autonomous Vehicles using Artificial Intelligence

  • Conference: 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC)
  • Year: 2022
  • DOI: 10.1109/icesc54411.2022.9885422
  • Contributors: Ahamed Ali Samsu Aliar