Chin-Ling Chen | Cryptography | Outstanding Scientist Award

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Prof Dr. Chin-Ling Chen | Cryptography | Outstanding Scientist Award

Professor at Chaoyang University of Technology, Taiwan

Summary:

Prof. Dr. Chin-Ling Chen is a prominent researcher and academic known for his expertise in blockchain technology, cryptography, authentication, and network security. He has authored over 170 articles in prestigious SCI/SSCI international journals and holds 12 patents in Taiwan. From 2006 to 2015, he was recognized as a distinguished researcher at Chaoyang University of Technology, where he currently serves as a faculty member. Prof. Chen has actively contributed to the academic community by reviewing over 450 journal articles and serving on the editorial boards of several journals, including PLOS ONE and the International Journal on Artificial Intelligence Tools. His significant research contributions have advanced the fields of computer security, privacy, and digital signatures, positioning him as a leading figure in his areas of study.

Profile:

Education:

Prof. Dr. Chin-Ling Chen holds a distinguished educational background that has laid the foundation for his extensive research career. He earned his Bachelor’s degree in Computer Science and Information Engineering from National Changhua University of Education in Taiwan. He then pursued his Master’s degree in Computer Science from National Tsing Hua University, further enhancing his expertise in the field. Prof. Chen completed his Ph.D. in Computer Science and Engineering at National Chung Cheng University, where he focused on cutting-edge topics such as cryptography and network security. His strong academic training has significantly contributed to his prolific output and innovative research contributions in various domains, including blockchain technology, authentication, and wireless sensor networks.

Professional Experience:

Prof. Dr. Chin-Ling Chen has an extensive professional background in academia and research, primarily at Chaoyang University of Technology, where he has served as a faculty member and researcher. His career spans several years, during which he has made significant contributions to the fields of blockchain, cryptography, authentication, and network security. Prof. Chen has been recognized as a distinguished researcher annually from 2006 to 2015, highlighting his commitment to excellence in research and education. In addition to his teaching responsibilities, he has actively participated in peer review processes, evaluating over 450 articles for various SCI/SSCI journals. His editorial roles include memberships on the editorial boards of respected journals such as PLOS ONE and the International Journal on Artificial Intelligence Tools, reflecting his influence and leadership within the academic community.

Research Interests:

Prof. Dr. Chin-Ling Chen’s research interests encompass a broad range of topics in computer science and security, focusing on areas such as blockchain technology, cryptography, authentication, and network security. His work addresses critical issues in computer security and privacy, exploring innovative solutions for web services, mobile commerce (M-Commerce), and e-commerce applications. Prof. Chen also investigates digital signatures, radio frequency identification (RFID) systems, wireless sensor networks, and vehicular ad hoc networks. With over 170 publications in esteemed SCI/SSCI international journals, his contributions to these fields are significant, complemented by 12 patents in Taiwan. His research not only advances theoretical knowledge but also has practical implications, enhancing the security and privacy of modern technological systems.

Skills:

Prof. Dr. Chin-Ling Chen possesses a diverse skill set that is highly relevant to his research in computer science and security. He is proficient in blockchain technology and cryptographic techniques, enabling him to develop secure systems and applications. His expertise in authentication methods and network security allows him to address complex challenges related to data protection and privacy. Prof. Chen is also skilled in designing and implementing secure web services and e-commerce platforms, ensuring safe transactions and user confidentiality. Additionally, he has significant experience in radio frequency identification (RFID) technology and wireless sensor networks, contributing to advancements in IoT and vehicular ad hoc networks. His extensive background in research methodology and peer review further enhances his ability to contribute to the academic community and drive innovation in the field.

Conclution:

Prof. Dr. Chin-Ling Chen’s significant contributions to research, along with his extensive publication record and innovative patents, position him as a leading scientist in his field. His ongoing dedication to advancing technology and security makes him a highly deserving candidate for the Research for Outstanding Scientist Award.

Publication Top Noted:

Conformation of EPC Class 1 Generation 2 standards RFID system with mutual authentication and privacy protection

  • Cited By: 159
  • Year: 2009
  • Journal: Engineering Applications of Artificial Intelligence, 22(8), 1284-1291

An efficient user authentication and user anonymity scheme with provable security for IoT-based medical care system

  • Cited By: 137
  • Year: 2017
  • Journal: Sensors, 17(7), 1482

An extended chaotic maps-based key agreement protocol with user anonymity

  • Cited By: 114
  • Year: 2012
  • Journal: Nonlinear Dynamics, 69, 79-87

Mobile device integration of a fingerprint biometric remote authentication scheme

  • Cited By: 93
  • Year: 2012
  • Journal: International Journal of Communication Systems, 25(5), 585-597

An intelligent and secure health monitoring scheme using IoT sensor based on cloud computing

  • Cited By: 81
  • Year: 2017
  • Journal: Journal of Sensors, 2017(1), 3734764

A privacy authentication scheme based on cloud for medical environment

  • Cited By: 77
  • Year: 2014
  • Journal: Journal of Medical Systems, 38, 1-16

The design of a secure anonymous internet voting system

  • Cited By: 76
  • Year: 2004
  • Journal: Computers & Security, 23(4), 330-337

A traceable and privacy-preserving authentication for UAV communication control system

  • Cited By: 71
  • Year: 2020
  • Journal: Electronics, 9(1), 62

A secure medical data exchange protocol based on cloud environment

  • Cited By: 68
  • Year: 2014
  • Journal: Journal of Medical Systems, 38, 1-12

Collaborative learning by teaching: A pedagogy between learner-centered and learner-driven

  • Cited By: 59
  • Year: 2019
  • Journal: Sustainability, 11(4), 1174

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

 

Dana Lakshmi | Cryptography | Women Researcher Award

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Dr. Dana Lakshmi | Cryptography | Women Researcher Award

Associate Professor at Dhanalakshmi Srinivasan University, India

Summary:

Dana Lakshmi is driven by a passion for excellence in her field, fueled by dedication to hard work, continuous research, and honing her skills. Her professional objective is to contribute significantly to an esteemed institute, leveraging her knowledge and talents to foster its growth and development. With a commitment to academic and professional advancement, Dana strives to make meaningful contributions through her expertise and ongoing pursuit of excellence in her chosen field.

Profile:

Education:

Dr. Dana Lakshmi holds an impressive academic background with a Ph.D. in Power System from Kalasalingam University, awarded in September 2017. Her doctoral research focused on “Reactive Power Optimization and Pricing in Regulated and Deregulated Power System using Differential Evolution.” Prior to her Ph.D., she completed her Master’s degree in Power System from Thiagarajar College of Engineering, affiliated with Anna University, in April 2006, achieving First Class with Distinction and a remarkable CGPA of 9.09. Dr. Lakshmi began her academic journey with a Bachelor’s degree in Electrical and Electronics Engineering from Thiagarajar College of Engineering, Madurai Kamaraj University, graduating in April 2003 with First Class honors and securing 78.35%. In her earlier academic years, Dana Lakshmi demonstrated exceptional academic prowess, attaining First Class with Distinction in both XII (Higher Secondary) from the Higher Secondary Board of Tamil Nadu in 1999 with 88.67%, and X (Matriculation) from the Matriculation Board of Tamil Nadu in 1997 with 84.27%. Her educational achievements underscore her dedication and commitment to excellence in the field of Electrical and Electronics Engineering, positioning her as a highly qualified professional in the realm of power systems and engineering.

Professional Experience

Dr. Dana Lakshmi has accumulated extensive experience in academia, specializing in Electrical and Electronics Engineering. She served as an Associate Professor in the Department of Electrical and Electronics Engineering at GMR Institute of Technology, Rajam, Andhra Pradesh, from May 29, 2018, to July 31, 2023, totaling 5 years and 2 months. Prior to this, she held the position of Assistant Professor at Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, from July 28, 2017, to May 5, 2018, contributing for 9 months. Her academic journey also includes a tenure as Assistant Professor at AAA College of Engineering and Technology from June 16, 2015, to April 29, 2017, spanning 1 year and 10 months. She started her career at Kalasalingam University, where she served as an Assistant Professor from July 16, 2007, to May 30, 2015, accumulating 7 years and 10 months of experience. Earlier in her career, she contributed as a part-time lecturer at Thiagarajar College of Engineering, Madurai, from December 22, 2003, to August 10, 2004, for a period of 7 months.

Research Skills:

Dana Lakshmi is a skilled researcher with expertise in conducting comprehensive literature reviews, designing experiments, and analyzing data to uncover insights in their field. They possess proficiency in various research methodologies and laboratory techniques, utilizing specialized software tools effectively. Communication is a strength, as seen in their ability to articulate complex ideas through academic papers and presentations. Dana’s analytical acumen allows them to critically evaluate findings and propose innovative solutions. They excel in collaborative environments, engaging with peers and students to foster productive research outcomes. Strong time management ensures they meet project deadlines and prioritize effectively. Adaptability to new methodologies and emerging trends underscores their commitment to advancing academic knowledge and making impactful contributions to their field.

Publications:

A decentralized framework for enhancing security in power systems through blockchain technology and trading system

  • Authors: V. Thiruppathy Kesavan, D. Danalakshmi, R. Gopi, R. Venkatesan
  • Journal: Energy Sources, Part A: Recovery, Utilization, and Environmental Effects
  • Publication Date: 2024-12-31
  • DOI: 10.1080/15567036.2024.2318010

Intrusion detection and mitigation of attacks in microgrid using enhanced deep belief network

  • Authors: Danalakshmi Durairaj, Thiruppathy Kesavan Venkatasamy, Abolfazl Mehbodniya, Syed Umar, Tanweer Alam
  • Journal: Energy Sources, Part A: Recovery, Utilization, and Environmental Effects
  • Publication Date: 2024-12-31
  • DOI: 10.1080/15567036.2021.2023237

Intelligent Intrusion Detection System for VANET Using Machine Learning and Deep Learning Approaches

  • Authors: Karthiga, B., Durairaj, Danalakshmi, Nawaz, Nishad, Venkatasamy, Thiruppathy Kesavan, Ramasamy, Gopi, Hariharasudan, A.
  • Journal: Wireless Communications and Mobile Computing
  • Publication Date: 2022
  • DOI: 10.1155/2022/5069104
  • WOSUID: WOS:000876518300002

Random forest based power sustainability and cost optimization in smart grid

  • Authors: Danalakshmi Durairaj, Łukasz Wróblewski, A. Sheela, A. Hariharasudan, Mariusz Urbański
  • Journal: Production Engineering Archives
  • Publication Date: 2022-03-01
  • DOI: 10.30657/pea.2022.28.10

Forecasting of Energy Demands for Smart Home Applications

  • Authors: Dhowmya Bhatt, Danalakshmi D, A. Hariharasudan, Marcin Lis, Marlena Grabowska
  • Journal: Energies
  • Publication Date: 2021-02-17
  • DOI: 10.3390/en14041045

Reactive Power Optimization and Price Management in Microgrid Enabled with Blockchain

  • Authors: Danalakshmi D., Gopi R., A. Hariharasudan, Iwona Otola, Yuriy Bilan
  • Journal: Energies
  • Publication Date: 2020-11-24
  • DOI: 10.3390/en13236179

Generator reactive power pricing for practical utility system using power flow tracing method

  • Authors: Danalakshmi Durairaj
  • Journal: International Journal of Engineering & Technology
  • Publication Date: 2018

Reactive Power Payment for Generator with Wind Farm Incorporating Voltage Stability Index for Practical Power System

  • Authors: Danalakshmi Durairaj
  • Journal: World Applied Sciences Journal
  • Publication Date: 2017

Reactive power pricing using cloud service considering wind energy

  • Authors: Danalakshmi, D., Kannan, S., Thiruppathy Kesavan, V.
  • Journal: Cluster Computing
  • Publication Date: 2017
  • DOI: 10.1007/s10586-017-0896-2
  • EID: 2-s2.0-85019611313

Market based pricing for reactive power service in restructured practical power system

  • Authors: Danalakshmi, D., Kannan, S.
  • Journal: International Journal of Applied Engineering Research
  • Publication Date: 2015
  • EID: 2-s2.0-84942436326

 

 

Muhammad Sajjad | Cryptography | Best Researcher Award

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Dr. Muhammad Sajjad, Cryptography, Best Researcher Award

Doctorate at Quaid-I-Azam University Islamabad, Pakistan, Pakistan

Dr. Muhammad Sajjad is a mathematician specializing in data transmission, data security, coding theory, and cryptography. He earned his Ph.D. and M.Phil in Mathematics from Quaid-I-Azam University in Islamabad, Pakistan, focusing on coding and cryptographic schemes over vector algebra residue classes and higher-length cyclic codes over quaternion integers, respectively. He also holds an M.Sc in Mathematics and a B.Sc in Mathematics and Physics from Islamia University Bahawalpur. Dr. Sajjad has a wealth of experience in research and teaching, making significant contributions to the field of mathematics.

Profile:

Education:

  • Ph.D. in Mathematics (2020-2024) from Quaid-I-Azam University, Islamabad, Pakistan, with a focus on data transmission and data security using coding and cryptographic schemes over the residue classes of vector algebra.
  • M.Phil in Mathematics (2018-2020) from Quaid-I-Azam University, Islamabad, Pakistan, specializing in encoding and decoding of higher-length cyclic codes over quaternion integers.
  • M.Sc in Mathematics (2016-2018) from Islamia University Bahawalpur, Punjab, Pakistan.
  • B.Sc in Mathematics and Physics (2014-2016) from Islamia University Bahawalpur, Punjab, Pakistan.

Professional Experience:

Dr. Muhammad Sajjad has an extensive professional background in mathematics and academia. He has spent five years conducting research at Quaid-I-Azam University in Islamabad, Pakistan, focusing on various aspects of coding theory, cryptography, and data security. Currently, Dr. Sajjad serves as a Mathematics faculty member at Quaid-i-Azam University, where he imparts knowledge and expertise in areas such as Cryptography, Coding Theory, Linear Algebra, Rings and Fields, and Number Theory. In addition to his role at Quaid-i-Azam University, Dr. Sajjad has enriched his teaching experience as a visiting faculty member at prestigious institutions such as the National University of Modern Languages (NUML) and Bahria University, both located in Islamabad, Pakistan. He has also contributed his mathematical expertise as a faculty member at FG Sir Syed College in Rawalpindi, Pakistan. Throughout his professional journey, Dr. Sajjad has not only conducted impactful research but has also dedicated himself to educating and mentoring students, shaping the future of mathematics and related fields in Pakistan.

Research Interest:

Dr. Muhammad Sajjad’s research interests encompass a broad spectrum of mathematical and engineering disciplines. His expertise lies in the realms of data transmission, data security, coding theory, and cryptography. Within mathematics, Dr. Sajjad delves into areas such as vector algebra, commutative algebra, non-commutative algebra, and non-associative algebra. His exploration of number theory extends to developing novel cryptographic schemes and error-correcting codes in coding theory, contributing significantly to data security and communication reliability. Dr. Sajjad’s research endeavors are characterized by a deep understanding of algebraic structures and their applications in practical domains like information security and data transmission. His work often involves innovative approaches to encoding and decoding methods, particularly in the context of higher-length cyclic codes over quaternion integers. This intersection of theoretical mathematics and real-world applications underscores Dr. Sajjad’s commitment to advancing both fundamental mathematical knowledge and its practical implementations in data science and engineering.

Publication Top Noted:

“A comparative study of nonlinear fractional Schrödinger equation in optics”

  • Authors: S Irshad, M Shakeel, A Bibi, M Sajjad, KS Nisar
  • Journal: Modern Physics Letters B
  • Volume/Issue: 37 (05)
  • Cited By: 13
  • Year: 2023

“Quaternion Integers Based Higher Length Cyclic Codes and Their Decoding Algorithm”

  • Authors: M Sajjad, T Shah, MM Hazzazi, AR Alharbi, I Hussain
  • Journal: Computers, Materials & Continua
  • Volume/Issue: 73 (1)
  • Cited By: 7
  • Year: 2022

“Designing Pair of Nonlinear Components of a Block Cipher over Gaussian Integers”

  • Authors: M Sajjad, T Shah, RJ Serna
  • Journal: Computers, Materials & Continua
  • Volume/Issue: 75 (3)
  • Cited By: 6
  • Year: 2023

“Fundamental Results of Cyclic Codes over Octonion Integers and Their Decoding Algorithm”

  • Authors: M Sajjad, T Shah, RJ Serna, ZE Suárez Aguilar, OS Delgado
  • Journal: Computation
  • Volume/Issue: 10 (12)
  • Cited By: 3
  • Year: 2022

“Construction and decoding of BCH-codes over the Gaussian field”

  • Authors: M Sajjad, T Shah, M Alammari, H Alsaud
  • Journal: IEEE Access
  • Cited By: 2
  • Year: 2023

 

Abdallah Soualmi | Cryptography | Best Researcher Award

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Dr. Abdallah Soualmi, Cryptography, Best Researcher Award

Doctorate at University Ferhat abbas setif 1, Algeria

Dr. Abdallah Soualmi completed his education with a Bachelor’s degree in Computer Science in June 2014, followed by a Master’s degree in Networks and Distributed Systems in June 2016. He achieved a Ph.D. in Machine Learning in May 2021, specializing in the protection of medical content using watermarking and cryptography.

Profile:

Education:

Dr. Abdallah Soualmi completed his Bachelor’s degree in Computer Science in June 2014, followed by a Master’s degree in Networks and Distributed Systems in June 2016. He achieved his Ph.D. in Machine Learning in May 2021, specializing in the protection of medical content using watermarking and cryptography.

Professional Experience:

Dr. Abdallah Soualmi’s professional experience spans academia and research, focusing on machine learning, data security, and cryptography. He began his career as a Research Fellow and Ph.D. Student at UFAS1 University, actively involved in cutting-edge research from September 30, 2016, to May 4, 2021. His work during this period contributed significantly to the fields of medical data security, cryptography, steganography, watermarking, data authenticity, authorship proofing, and data sharing monitoring. After completing his Ph.D., Dr. Soualmi transitioned to an academic role, initially as an Assistant Teacher at Cuillizi University from September 26, 2021, to September 26, 2022. He then progressed to become an Associate Lecturer at the same university, starting from September 26, 2022, until the present. In these roles, he has been instrumental in shaping the educational journey of students, imparting his knowledge in machine learning and computer science. Throughout his career, Dr. Soualmi has demonstrated a strong commitment to research excellence and academic development, with a focus on leveraging advanced technologies for enhancing data security and integrity. His contributions in both academia and research highlight his expertise and dedication to advancing the frontiers of machine learning and data protection.

Research Interest:

Dr. Abdallah Soualmi’s research interests are centered around machine learning, data security, and cryptography, with a particular focus on applications in medical data protection. He is passionate about exploring innovative approaches to ensure the security and integrity of sensitive medical information, employing techniques such as cryptography, steganography, watermarking, and data authenticity verification. Dr. Soualmi is also interested in data sharing monitoring mechanisms to enhance privacy and prevent unauthorized access to medical data. His research aims to contribute to the development of robust and reliable solutions for safeguarding healthcare information in an increasingly digital and interconnected world.

Publication Top Noted:

A new blind medical image watermarking based on weber descriptors and Arnold chaotic map

  • Authors: A Soualmi, A Alti, L Laouamer
  • Journal: Arabian Journal for Science and Engineering
  • Volume: 43
  • Issue: 12
  • Pages: 7893-7905
  • Citations: 43
  • Year: 2018

A novel blind medical image watermarking scheme based on Schur triangulation and chaotic sequence

  • Authors: A Soualmi, A Alti, L Laouamer
  • Journal: Concurrency and Computation: Practice and Experience
  • Volume: 34
  • Issue: 1
  • Pages: e6480
  • Citations: 20
  • Year: 2022

A novel blind watermarking approach for medical image authentication using MinEigen value features

  • Authors: A Soualmi, A Alti, L Laouamer
  • Journal: Multimedia Tools and Applications
  • Volume: 80
  • Issue: 2
  • Pages: 2279-2293
  • Citations: 17
  • Year: 2021

An imperceptible watermarking scheme for medical image tamper detection

  • Authors: A Soualmi, A Alti, L Laouamer
  • Journal: International Journal of Information Security and Privacy (IJISP)
  • Volume: 16
  • Issue: 1
  • Pages: 1-18
  • Citations: 16
  • Year: 2022

A blind image watermarking method for personal medical data security

  • Authors: A Soualmi, A Alti, L Laouamer
  • Conference: 2019 International Conference on Networking and Advanced Systems (ICNAS)
  • Pages: 1-5
  • Citations: 10
  • Year: 2019

 

 

Oluwafemi Oke | Cybersecurity And Cryptography | Best Researcher Award

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Mr. Oluwafemi Oke, Cybersecurity And Cryptography, Best Researcher Award

Oluwafemi Oke at Near East University, Cypus

Oke Oluwafemi is a highly motivated and skilled Ph.D. candidate in Artificial Intelligence with a strong desire for a remote position in machine learning. He has demonstrated success in leading research projects, developing AI algorithms, and implementing AI solutions across various industries. Oke possesses expertise in machine learning, natural language processing, and computer vision. His proficiency extends to languages such as Python, and frameworks including TensorFlow and PyTorch. He holds a Bachelor’s degree in Computer Engineering, a Master’s degree in Computer Science with a focus on Software Engineering, and is currently pursuing his Doctor of Philosophy in Computer Information Systems with a concentration in Artificial Intelligence.

Education:

Babcock University

  • Degree: Bachelor of Science in Computer Engineering
  • Duration: July 2016
  • Project: Radio Frequency Identification in Doors

Babcock University

  • Degree: Master of Science in Computer Science (Software Engineering)
  • Duration: August 2020
  • Thesis: Hybrid Intelligent Internet of Things (IOT) Systems for Automated Homes

Near East University

  • Program: Doctor of Philosophy (PhD)
  • Duration: March 2021 – Present

Profile:

Professional  Experience:

AI Engineer, Cadbury Plc, 2015

  • Developed and deployed AI-based solutions for clients in various industries.
  • Implemented machine learning algorithms for image and speech recognition, improving accuracy by 23%.

AI Consultant, Corporate Affairs Commission, 2017

  • Provided expert guidance and consulting services on AI implementation.
  • Conducted workshops on machine learning and deep learning.
  • Built and trained models for natural language processing and computer vision tasks.

Data Scientist, NEU Cardiac Centre, 2020

  • Developed a healthcare diagnostic tool using machine learning and image recognition, achieving 94% accuracy in identifying cancerous cells.
  • Conducted analysis of customer behavior using NLP on social media data, leading to a targeted marketing strategy and a 15% increase in conversions.

Machine Learning Engineer, Harvest, 2022

  • Led the development of a recommendation system using deep learning, increasing user engagement by 30% and sales by 25%.
  • Led a team to implement an autonomous vehicle navigation system, achieving 99.5% accuracy in real-world scenarios.

Research Interests:

Mr. Oluwafemi Oke has amassed a wealth of research experience across various domains of artificial intelligence (AI) and machine learning (ML). As a Research Assistant at Daxlinks in 2020, he focused on deep learning techniques within the realm of machine learning, contributing significantly to user engagement improvements by developing a novel approach that yielded a remarkable 45% increase in interaction accuracy. His tenure at GIFA INC in 2021 saw him collaborating on groundbreaking research projects exploring the intersection of AI and climate science, as well as devising a cutting-edge deep learning model for financial market forecasting, achieving an impressive 85% accuracy rate. Additionally, he played a pivotal role in enhancing language translation models using Transformer architectures, leading to a noteworthy 20% enhancement in translation accuracy, which garnered recognition within the academic community. Subsequently, as a Research Scientist at Near East University in 2022, Mr. Oke spearheaded the development of advanced algorithms for image and video analysis, resulting in the acquisition of several patents. Moreover, his contributions to research in natural language understanding culminated in multiple publications in prestigious conferences and journals. Notably, Mr. Oke led a team of researchers in the creation of an AI-based predictive maintenance system for industrial equipment, achieving a remarkable 67% reduction in downtime and a significant 97% increase in efficiency.

Publications:

Artificial Intelligence for Computer Vision: A Bibliometric Analysis

  • Year: 2023
  • Author(s): Oluwafemi Oke
  • Journal: [Journal Name] (Please insert the name of the journal where the paper was published.)
  • Volume: [Volume Number]
  • Issue: [Issue Number]
  • Pages: [Page Range]

Brain-Computer Interfaces: High-Tech Race to Merge Minds and Machines

  • Year: 2023
  • Author(s): Oluwafemi Oke
  • Journal: [Journal Name] (Please insert the name of the journal where the paper was published.)
  • Volume: [Volume Number]
  • Issue: [Issue Number]
  • Pages: [Page Range]

The Impact of Artificial Intelligence in Foreign Language Learning Using Learning Management Systems: A Systematic Literature Review

  • Year: 2023
  • Author(s): Oluwafemi Oke
  • Journal: [Journal Name] (Please insert the name of the journal where the paper was published.)
  • Volume: [Volume Number]
  • Issue: [Issue Number]
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