Mohammad Alauthman | Detection | Excellence in Research

Posted on by ScienceFather

Assist Prof Dr. Mohammad Alauthman | Detection | Excellence in Research

Assistant Professor at Information Security Department, University of Petra, Jordan

Dr. Mohammad Alauthman is an accomplished academic with a focus on cybersecurity and network security. Currently serving as an Assistant Professor at Petra University in Amman, Jordan, since 2020, Mohammad teaches a variety of courses in the Department of Information Security, including topics such as SOC analyst, Ethical Hacking, and Digital Forensics Investigation. Prior to this role, Mohammad was an Assistant Professor at Zarqa University from 2016 to 2020, where they taught courses in computer science, including Advanced Information and Networks Security and Introduction to Cybersecurity. Mohammad’s research interests lie in the application of artificial intelligence to cybersecurity, particularly in areas such as botnet detection, DDoS detection, and spam email detection. They have received grants for several research projects, demonstrating their dedication to advancing knowledge in their field. Mohammad’s academic background and teaching experience make them a valuable asset to the academic community, contributing to both research and education in the field of cybersecurity.

Profile

Education

Dr. Mohammad Alauthman is an Assistant Professor with a strong background in computer science and a specialization in network security. They earned their Ph.D. in Computer Science from Northumbria University at Newcastle, UK, in 2016, with a focus on Network Security. Their doctoral thesis, titled “An Efficient Approach to Online Bot Detection Based on a Reinforcement Learning Technique,” demonstrates their expertise in this field. Prior to their Ph.D., Mohammad completed a Master’s degree in Computer Science from Amman Arab University, Jordan, in 2005, and a Bachelor’s degree in Computer Science from Hashemite University, Jordan, in 2002. Mohammad’s academic journey has equipped them with a comprehensive understanding of computer science principles, particularly in the realm of network security.

Experience:

Dr. Mohammad Alauthman has a wealth of experience in academia, holding key positions at various institutions. Since 2021, they have served as the Chairman of the Information Security department at the Faculty of Information Technology, University of Petra, Amman, Jordan. Mohammad has also been a Full-time Assistant Professor in the Department of Information Security at the same university since 2020. Prior to their current role, Mohammad was the Chairman of the Internet Technology department and an Assistant Professor at the Faculty of Information Technology, Zarqa University, Jordan, from 2018 to 2020. Before that, they were a Full-time Assistant Professor in the Computer Science Department at Zarqa University from 2016 to 2018. Mohammad’s academic career also includes positions as a Lecturer in the Department of Computer Science and Information at Majmmah University, Saudi Arabia, from 2008 to 2012, and as a Lecturer at Al-Balqa Applied University, Jordan, from 2007 to 2008. These roles have provided Mohammad with a diverse range of experiences in academia, contributing to their expertise in computer science and information security.

Research Interest:

Dr. Mohammad Alauthman’s research interests are primarily focused on cybersecurity and network security, with a particular emphasis on cross-layered solutions for intrusion detection systems. Their central research revolves around the use of artificial intelligence for early botnet detection, DDoS detection, spam email detection, Internet of Things (IoT) security, and network traffic classification. In addition to their work in cybersecurity, Mohammad also has research interests in healthcare, specifically in the areas of skin cancer detection, diabetic retinopathy, and pain intensity assessment, utilizing deep learning techniques. Their research projects are interdisciplinary and aimed at addressing real-life problems, reflecting their commitment to advancing knowledge and solving practical challenges in these fields.

Grants:

Dr. Mohammad Alauthman has received several grants to support their research in cybersecurity and network security. In 2022, they were awarded a grant from the Dean of Scientific Research at the University of Petra (UoP) for a project titled “Forecasting Citation Counts Using Deep Recurrent Neural Network Techniques.” In 2021, Mohammad received a grant from Al-Balqa Applied University for a project focused on “Darknet Traffic Identification Using Max Voting Algorithms.” Prior to that, in 2019, they received another grant from Al-Balqa Applied University for their work on “Fast Flux Botnet Catcher Approach (FFBCA).” At Zarqa University (ZU), Mohammad received grants from the Dean of Scientific Research for two projects. In 2017, they received a grant for a project titled “P2P Bot Detection Using Deep Learning with Traffic Reduction Schema.” In 2018, Mohammad received a grant for a project titled “Botnet Spam Email Detection Using Deep Recurrent Neural Network.” These grants highlight Mohammad’s dedication to advancing research in cybersecurity and network security, focusing on innovative approaches to detect and mitigate threats.

Teaching Experience:

Dr. Mohammad Alauthman has been serving as an Assistant Professor at Petra University in the Department of Information Security, Faculty of Information Technology, Amman, Jordan, since 2020. In this role, they teach a range of courses covering topics such as SOC analyst, Ethical Hacking, Intrusion Detection System, Digital Forensics Investigation, Database Security, E-commerce Environment Security, Information and Network Security, Wireless Networks, and Introduction to Data Communication & Networking. Prior to joining Petra University, Mohammad was an Assistant Professor at Zarqa University in the Department of Computer Science, Faculty of Information Technology, Zarqa, Jordan, from 2016 to 2020. During their tenure at Zarqa University, Mohammad taught courses including Advanced Information and Networks Security (Master Level), Introduction to Cybersecurity, Introduction to Machine Learning, Networks, Artificial Intelligence, Special Languages in CS II (Python), Information Retrieval, Programming Language I (Java), Concepts of Programming Languages, Research Methodology and Ethics, and Advanced Programming Language (C#). These positions highlight Mohammad’s expertise in teaching a wide range of topics related to computer science and information security.

Publications:

  1. IoT transaction processing through cooperative concurrency control on fog–cloud computing environment
    • Authors: A Al-Qerem, M Alauthman, A Almomani, BB Gupta
    • Citations: 244
    • Year: 2019
  2. An efficient reinforcement learning-based Botnet detection approach
    • Authors: M Alauthman, N Aslam, M Al-Kasassbeh, S Khan, A Al-Qerem, KKR Choo
    • Citations: 131
    • Year: 2020
  3. A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks
    • Authors: M Alauthaman, N Aslam, L Zhang, R Alasem, MA Hossain
    • Citations: 129
    • Year: 2018
  4. Phishing Website Detection With Semantic Features Based on Machine Learning Classifiers: A Comparative Study
    • Authors: A Almomani, M Alauthman, MT Shatnawi, M Alweshah, A Alrosan
    • Citations: 120
    • Year: 2022
  5. DNS rule-based schema to botnet detection
    • Authors: K Alieyan, A Almomani, M Anbar, M Alauthman, R Abdullah, BB Gupta
    • Citations: 113
    • Year: 2021
  6. Machine Learning-driven optimization for SVM-based intrusion detection system in vehicular ad hoc networks
    • Authors: A Alsarhan, M Alauthman, E Alshdaifat, AR Al-Ghuwairi, A Al-Dubai
    • Citations: 49
    • Year: 2023
  7. Feature selection using a machine learning to classify a malware
    • Authors: M Al-Kasassbeh, S Mohammed, M Alauthman, A Almomani
    • Citations: 49
    • Year: 2020
  8. An online intrusion detection system to cloud computing based on NeuCube algorithms
    • Authors: A Almomani, M Alauthman, F Albalas, O Dorgham, A Obeidat
    • Citations: 43
    • Year: 2018
  9. Machine learning for phishing detection and mitigation
    • Authors: M Alauthman, A Almomani, M Alweshah, W Alomoush, K Alieyan
    • Citations: 28*
    • Year: 2019
  10. Botnet Spam E-Mail Detection Using Deep Recurrent Neural Network
    • Authors: M ALAUTHMAN
    • Citations: 26
    • Year: 2020

 

Jingquan Li | Records | Best Researcher Award

Posted on by ScienceFather

Dr. Jingquan Li | Records | Best Researcher Award

Associate Professor at Hofstra University, United States

Dr. Jingquan Li is a distinguished academic with a broad range of expertise in computer science, business administration, and information technology. Dr. Li’s academic journey includes a Doctor of Philosophy in Business Administration with a supporting area in Computer Science (Artificial Intelligence and Data Science) from the University of Illinois at Urbana-Champaign, a Master of Science in Manufacturing Management from the College of Business and Innovation at the University of Toledo, and a Bachelor of Engineering in Computer Engineering from Xi’an Jiaotong University. With over a decade of experience in academia, Dr. Li has held various teaching positions, including Associate Professor at Hofstra University, Tenured Associate Professor at Texas A&M University-San Antonio, and Assistant Professor at both Texas A&M University-San Antonio and Texas A&M University-Kingsville. Dr. Li’s teaching portfolio includes a diverse range of courses such as Information Systems in Organizations, Business Analytics, and Data Mining and Text Mining.

Profile:

Education

Dr. Jingquan Li holds a Doctor of Philosophy in Business Administration with a supporting area in Computer Science (Artificial Intelligence and Data Science) from the University of Illinois at Urbana-Champaign, earned in 2004. Prior to this, Dr. Li completed a Master of Science in Manufacturing Management at the College of Business and Innovation, University of Toledo, in 1997. Dr. Li’s academic journey began with a Bachelor of Engineering in Computer Engineering from the School of Electronic and Information Engineering at Xi’an Jiaotong University, obtained in 1987. Dr. Li’s educational background reflects a strong foundation in both business administration and computer science, with a focus on information systems, artificial intelligence, and data science.

Work Experience:

Dr. Jingquan Li has an extensive academic and professional background. Since September 2017, Dr. Li has served as an Associate Professor at Hofstra University in New York. Prior to joining Hofstra, from September 2010 to August 2017, Dr. Li held the position of Tenured Associate Professor at Texas A&M University-San Antonio in Texas. Before achieving tenure, Dr. Li was an Assistant Professor at Texas A&M University-San Antonio from September 2009 to August 2010 and at Texas A&M University-Kingsville from September 2004 to August 2009. Dr. Li’s academic positions are complemented by substantial professional experience as a Computer Engineer at the North China Institute of Computing Technology in Beijing, China, from 1987 to 1995. This combined background has equipped Dr. Li with a comprehensive understanding of both academia and industry, enriching their teaching and research endeavors.

Teaching Interest:

Dr. Jingquan Li’s teaching portfolio encompasses a wide array of courses focused on computer concepts and software tools in business. These include courses such as Information Systems in Organizations, Business Analytics, Database Management, Systems Analysis and Design, Big Data Management, Data Mining and Text Mining, Data Visualization, Machine Learning and Deep Learning, Enterprise Systems, Telecommunications and Networking, Information Security and Privacy, Cyber Security, Programming Languages, and Health Informatics. Dr. Li’s expertise in these areas is underpinned by their academic background and professional experience, making them a versatile and knowledgeable educator in the field of computer science and business administration.

Research Interest:

Dr. Jingquan Li’s expertise extends across a broad spectrum of specialized topics within the realm of computer science and business administration. Dr. Li’s proficiency includes Information Security and Privacy, Cybersecurity, Business Analytics, Big Data Management, Data Mining and Text Mining, Online Social Networks, Health Information Technology, AI Ethics, public health management and policy, and the Economics of Information Sharing. This diverse range of subjects underscores Dr. Li’s comprehensive understanding of the intersection between technology and business, making them a valuable resource in academia and beyond.

Research and Grants:

Dr. Jingquan Li has secured a diverse range of grants and research funding throughout their career, demonstrating a strong commitment to advancing knowledge in various fields. These include upcoming projects such as “The Health Benefits and Social Effects of Exercise Games” funded by the Agency for Health Research and Quality, as well as past endeavors like “Ensuring Privacy of Personal Health Records (PHRs): A Health Record Trust Architecture” funded by the Texas Area 41 Institute, where Dr. Li served as the Principal Investigator. Other notable projects led by Dr. Li include “Students’ and Faculty’s Perceptions of Hybrid Courses: A Comparative Study,” which received funding from the Texas A&M University-San Antonio Research Award in 2009-2010. Additionally, Dr. Li has been involved in projects such as “Privacy-Enhancing Data Mining” at Texas A&M University-Kingsville in 2007 and “Business Measurement for Fraud Detection with Privacy Protection” funded by KPMG LLP and the KPMG Foundation in 2004. Dr. Li’s collaborative efforts have also been recognized, as seen in projects like “On the Development and Quantification of Privacy-Enhancing Data Mining Methods” and “Supply Chain Management: A Multi-Agent Approach,” both of which were Research Board Award recipients at the University of Illinois, where Dr. Li served as a Co-Principal Investigator with Michael Shaw as the Principal Investigator. Another notable collaboration was with Motorola Inc. on “Information Technology for Managing Global Supply Chain Networks,” which was funded through the Motorola Manufacturing Systems Research Grant in 1999.

Awards and Honors:

Dr. Jingquan Li has been recognized with several prestigious awards and honors for their outstanding contributions to teaching and scholarship. In 2010, Dr. Li received the College of Business Faculty Excellence in Teaching Award from Texas A&M University-San Antonio, acknowledging their exceptional skills in educating students. Additionally, Dr. Li was twice honored with the College of Business Faculty Excellence in Scholarship Award, in both 2010 and 2009, highlighting their significant contributions to research and academic scholarship. Dr. Li’s dedication to excellence in academia is further underscored by the Seymour Sudman Award, which they received in 1999 and 1998. This award recognizes individuals who have demonstrated excellence in research methodology and survey statistics, reflecting Dr. Li’s commitment to advancing knowledge in their field. Furthermore, Dr. Li was the recipient of the College of Commerce Fellowship at the University of Illinois at Urbana-Champaign in 1998, further highlighting their academic prowess and dedication to scholarly pursuits.

 

Anwesha Sarkar | Public Health |Best Researcher Award |

Posted on by ScienceFather

Ms. Anwesha Sarkar, Public Health, Best Researcher Award

Ms. anwesha Sarkar at Indian Institute of Technology Patna, India

Anwesha Sarkar is a Ph.D. candidate in the Social Sciences Lab at the Indian Institute of Technology Patna. She holds a Master of Science degree in Geography from the University of Calcutta and a Bachelor of Science degree in Geography from Presidency University, Kolkata. Anwesha’s research interests lie in the intersection of geography, social sciences, and public health, with a focus on understanding the impact of neighborhood environments on women’s health. She has presented her work at various international conferences and workshops and has published papers in reputable journals. Anwesha is also a recipient of prestigious fellowships and grants, including a Ph.D. fellowship from the University Grants Commission (UGC). She is skilled in statistical analysis, GIS techniques, and various data analysis software.

Education:
  • Ph.D. Candidate in Social Sciences Lab, Indian Institute of Technology Patna (July 2021 – Present)
  • Master of Science in Geography, University of Calcutta, Kolkata, India (07/2017 to 08/2019), CGPA 4.41/6.00
  • Bachelor of Science in Geography, Presidency University, Kolkata, India (07/2014 to 06/2017), CGPA 7.51/10.00
  • Senior Secondary Examination, Bhavans Gangabux Kanoria Vidyamandir, Kolkata, India (2014), Percentage 91.75
  • Secondary Examination, Kendriya Vidyalaya No 2, Kolkata, India (2012), CGPA 10.0/10.0 .

Profile:

Research And Publication:

  • Published paper titled “A Comprehensive Trajectory Analyzing the Impact of Neighborhood on Women’s Health” in Health Care for Women International (2024).
  • Presented papers at various international conferences and workshops, including the International Conference on Social and Regional Resilience and the International Conference on Future Earth and Humanities.

Selected Cource And Workshops:

  • Attended workshops and courses on GIS tools and techniques, statistical data analysis using SPSS and R, qualitative techniques in geospatial sciences, and more.

Grant And Fellwship:

  • Awarded a Ph.D. fellowship by the UGC, with Junior Research Fellowship (07/2021 to 07/2023) and Senior Research Fellowship (08/2023 to 07/2026).
  • Qualified for the Junior Research Fellowship (UGC), India, in 2020, and the National Eligibility Test University Grants Commission (UGC), India, in 2019.

Internship:

  • Worked as a Recruitment Officer and Climate Counsellor at the International Centre for Culture & Education, contributing to the Green (R)evolution College Program and Global Certification Program.

Professional Membership:

  • Life member of the Indian Public Health Association (IPHA) since 08/2023.

Skills:

  • Proficient in statistical analysis (quantitative and mixed methods), cartographic techniques (remote sensing and GIS), and various data analysis software such as SPSS, STATA, R Programming, ArcMap, QGIS, Erdas Imagine, AutoCAD Map, and others.

Kalimuthu Marimuthu | Disease Prediction |Best Researcher Award

Posted on by ScienceFather

Dr.Kalimuthu Marimuthu,  Disease Prediction, Best Researcher Award

 Dr. Kalimuthu Marimuthu at Gitam University, India

Dr. Kalimuthu Marimuthu is a distinguished academician and researcher with over 18 years of experience in the field of information technology. He holds a Ph.D. in Information Technology from Anna University, Chennai, where he was recognized for his highly commendable research. Dr. Marimuthu’s expertise spans various areas including big data analytics, cloud computing, data mining, and soft computing. He has contributed significantly to the academic community through his numerous publications in both national and international journals and conferences. With a strong commitment to excellence in education and research, Dr. Marimuthu continues to inspire and mentor students and professionals in the field of information technology.

Education:

Dr. Kalimuthu Marimuthu is a highly accomplished individual with a strong educational background. He obtained his Ph.D. (Doctor of Philosophy) from Anna University, Chennai, in April 2017, where he was recognized for his highly commendable research. Prior to his Ph.D., he completed his M.Tech. (Master of Technology) in Information Technology at Bharath University, Chennai, in May 2005, achieving a First Class with Distinction with a remarkable score of 8.4 out of 10. Earlier in his academic journey, Dr. Marimuthu earned his MCA (Master of Computer Applications) from Madras University, Chennai, in April 2002, securing a First Class with a notable percentage score of 66. These educational achievements underscore his dedication to academic excellence and his expertise in the field of information technology.

Profile:

Professional Experience:

Dr. Kalimuthu Marimuthu boasts a rich and diverse professional background in the field of information technology. Commencing his career journey as a Lecturer at SNS College of Technology (Autonomous) in Coimbatore in June 2005, he progressively advanced to higher positions, including Senior Lecturer, Assistant Professor, and Associate Professor. Throughout his career, Dr. Marimuthu has held various academic leadership roles, serving as the Academic Coordinator for implementing the Choice Based Credit System (CBCS), NBA Coordinator for the department, and overseeing Board of Studies and Head of Department (HOD) responsibilities. His contributions extend to quality assurance and enhancement initiatives, where he has served as the NAAC Coordinator and IQAC In charge for his college. Furthermore, Dr. Marimuthu actively engages in conducting workshops, seminars, and faculty development programs, demonstrating his commitment to the continuous professional development of his peers. With a prolific publication record in both national and international journals, Dr. Marimuthu’s research interests encompass a broad spectrum of topics, ranging from multi-class facial emotion recognition to gastric cancer classification and intelligent vision camera systems. Presently, as an Associate Professor at GITAM University, Bengaluru, Dr. Marimuthu continues to inspire students and fellow academics alike through his exemplary teaching, groundbreaking research, and effective administrative leadership.

Research interests:

Dr. Kalimuthu Marimuthu’s research interests encompass a broad spectrum of topics within the field of information technology. His focus areas include multi-class facial emotion recognition and gastric cancer classification using innovative approaches such as hybrid deep learning models. Additionally, Dr. Marimuthu is deeply engaged in the development of intelligent vision camera systems and their integration into smartphone architectures. Furthermore, he has a keen interest in big data analytics, cloud computing, operating systems, data mining, and soft computing, exploring these domains to uncover novel insights and solutions. Through his diverse research interests, Dr. Marimuthu demonstrates a commitment to advancing knowledge and technology in the ever-evolving landscape of information technology.

Publications:
  1. Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods
    • Authors: A. Mogadala, M. Kalimuthu, D. Klakow
    • Journal: Journal of Artificial Intelligence Research (JAIR)
    • Citations: 126
    • Year: 2021
  2. Fusion models for improved image captioning
    • Authors: M. Kalimuthu, A. Mogadala, M. Mosbach, D. Klakow
    • Conference: International Conference on Pattern Recognition (ICPR)
    • Citations: 17
    • Year: 2021
  3. Automatic conversion of dialectal Tamil text to standard written Tamil text using FSTs
    • Authors: K. Marimuthu, SL Devi
    • Conference: Proceedings of the 2014 Joint Meeting of SIGMORPHON and SIGFSM
    • Citations: 8
    • Year: 2014
  4. A Competitive Deep Neural Network Approach for the ImageCLEFmed Caption 2020 Task
    • Authors: M. Kalimuthu, F. Nunnari, D. Sonntag
    • Conference: ImageCLEF-2020
    • Citations: 7
    • Year: 2020
  5. Incremental domain adaptation for neural machine translation in low-resource settings
    • Authors: M. Kalimuthu, M. Barz, D. Sonntag
    • Conference: Association for Computational Linguistics (ACL)
    • Citations: 6
    • Year: 2019
  6. Named entity recognizer for Indian languages
    • Authors: SL Devi, CS Malarkodi, K. Marimuthu, C Chrompet
    • Conference: International Conference on Natural Language Processing (ICON)
    • Citations: 6
    • Year: 2013
  7. How human analyse lexical indicators of sentiments-a cognitive analysis using reaction-time
    • Authors: K. Marimuthu, SL Devi
    • Conference: Proceedings of the 2nd workshop on sentiment analysis where AI …
    • Citations: 4
    • Year: 2012
  8. Word boundary identifier as a catalyzer and performance booster for Tamil morphological analyzer
    • Authors: K. Marimuthu, K. Amudha, T. Bakiyavathi, SL Devi
    • Conference: Proceedings of 6th Language and Technology Conference, Human …
    • Citations: 2
    • Year: 2013
  9. Named entity recognizer for Indian languages (ICON NLP tool contest 2013)
    • Authors: SL Devi, CS Malarkodi, K. Marimuthu, C Chrompet
    • Conference: 10th International Conference on Natural Language Processing (ICON)
    • Citations: 1
    • Year: 2013

Rajesh Natarajan | Face Sketch Synthesis | Best Researcher Award

Posted on by ScienceFather

Rajesh Natarajan | Face Sketch Synthesis | Best Researcher Award

Dr Rajesh Natarajan University of Technology and Applied Sciences-Shinas, Oman

Rajesh N completed his Ph.D. in Computer Science from Bharathiar University, Master of Computer Application from Thiruvalluvar University and BSc Computer science from Madras University. He is currently working as a Lecturer at University of Technology and Applied Sciences-Shinas, Sultanate of Oman. His research interest includes Data Mining, Machine Learning, Big Data Analytics, Blockchain Technology, and Data Privacy and Security. He has presented articles in the National and International conferences also published articles in reputed indexed journals like SCI, WoS and SCOPUS.

Education:

He earned his Doctor of Philosophy in Computer Science from Bharathiar University in Coimbatore, Tamil Nadu, India, in 2020. Prior to that, he completed his Master of Computer Application degree at Thiruvalluvar University in Vellore, Tamil Nadu, India, in 2008. His academic journey began with a Bachelor of Computer Science degree from Madras University in Chennai, Tamil Nadu, India, in 2005. Throughout his educational career, he has demonstrated a keen interest and dedication to the field of computer science. With a solid foundation established through his bachelor’s degree, he pursued advanced studies, culminating in a master’s degree that provided him with comprehensive knowledge and skills in computer applications. His pursuit of a Ph.D. reflects his commitment to scholarly research and his desire to contribute to the advancement of knowledge in the field. Through his academic achievements and professional experiences, he has developed a deep understanding of computer science concepts and their practical applications. He continues to leverage his expertise to make meaningful contributions to both academia and the broader technology industry.

Profile:

Experience:

He has an extensive academic background, having served as a Lecturer in the Department of Information Technology at the University of Technology and Applied Science in Shinas, Sultanate of Oman, since October 14, 2014. Prior to this role, he held the position of Assistant Professor in the Department of Computer Application at Sir M. Visvesvaraya Institute of Technology in Bangalore, India, from February 2, 2009, to October 11, 2014. With over a decade of experience in academia, he has demonstrated a strong commitment to excellence in teaching and research. Throughout his career, he has been dedicated to fostering a dynamic and engaging learning environment for his students, empowering them with the knowledge and skills necessary to succeed in the field of information technology. His tenure as both a Lecturer and Assistant Professor underscores his passion for education and his ability to inspire and mentor the next generation of IT professionals. Through his teaching, research, and leadership, he continues to make significant contributions to the academic community, shaping the future of technology education.

Publications:

  1. Blended ensemble learning prediction model for strengthening diagnosis and treatment of chronic diabetes disease Cited By : 42, Published By : 2022
  2. A Novel Framework on Security and Energy Enhancement Based on Internet of Medical Things for Healthcare 5.0 Cited By : 38, Published By : 2023
  3. Paddy plant disease recognition, risk analysis, and classification using deep convolution neuro-fuzzy network Cited By : 33, Published By : 2022
  4. Modified Self-Adaptive Bayesian algorithm for smart heart disease prediction in IoT system Cited By : 29, Published By : 2022
  5. Survey on privacy preserving data mining techniques using recent algorithms Cited By : 29, Published By : 2016
  6. A comparative performance analysis of machine learning approaches for the early prediction of diabetes disease Cited By : 19, Published By : 2022
  7. Association rules and deep learning for cryptographic algorithm in privacy preserving data mining Cited By : 17, Published By : 2019
  8. Survey on Malicious URL Detection Techniques Cited By : 12, Published By : 2022
  9. Secure Modern Wireless Communication Network Based on Blockchain Technology Cited By : 9, Published By : 2023
  10. Blinder Oaxaca and Wilk Neutrosophic Fuzzy Set-based IoT Sensor Communication for Remote Healthcare Analysis Cited By : 9, Published By : 2022

Yazan Abu Huson | AI and Blockchain | Best Researcher Award

Posted on by ScienceFather

Yazan Abu Huson | AI and Blockchain | Best Researcher Award

Mr Yazan Abu Huson University of Valencia, Spain

He is Yazan Abdelamjid Ahmad Abu Huson, a 28-year-old PhD student specializing in the Department of Accounting and Corporate Finance at the University of Valencia in Spain. With a master’s and bachelor’s degree in accounting, he is deeply immersed in the world of finance and academia. Beyond his academic pursuits, Yazan has been recognized for his exceptional talents and contributions. In 2019, he was honored with the Excellence Award for being the Most Influential Youth in the Hashemite Kingdom of Jordan. Additionally, he achieved the first rank in Jordan during the Jordanian Youth Voice Debate in 2018 and received the Honor Shield for Best Debater in the Debate Championship at Yarmouk University’s Faculty of Economics and Administrative Sciences in 2017. Yazan is also a certified Trainer of Trainers (TOT), HR professional, and Debate Trainer for the Arabius Academy for Consulting and Training. Currently, he serves as the Head of the Training and Development Department at the Esterdad Center for Civil Society Development, where he continues to make significant contributions to the development and growth of individuals and organizations.

Education:

He obtained his Master’s degree in Accounting from Al al-Bayt University, Jordan, where he excelled with a final grade of 85.5. His thesis focused on “The Expected Effect of Applying the National Billing System in Reducing Tax Evasion from the Perspective of the Auditors of the Income and Sales Tax Department in Jordan.” Prior to this, he completed his Bachelor’s degree in Accounting at Yarmouk University, Jordan, achieving a final grade of 80.9. In addition to his academic achievements, he participated in the National Young Leaders Program facilitated by Friedrich Ebert Stiftung in 2019. Furthermore, he enriched his knowledge with a course in Political Science offered by The Knowledge Stations for Consultation and Training in Amman, Jordan, in 2020. Throughout his academic and professional journey, he has demonstrated a commitment to excellence and a passion for continuous learning and development.

Profile:

Experience:

In Irbid, Jordan, since 2018, he has served as an Accounting Supervisor at the Esterdad Center for Civil Society Development, overseeing financial operations with meticulous attention to detail. Simultaneously, he has held the position of Public Accountant, ensuring compliance and accuracy in financial reporting. Located on University Street, 21110, Irbid, Jordan, he has contributed to the efficient functioning of the Education Department within the center. Additionally, since 2018, he has been actively engaged as an H.R.M, Trainer of Trainers (TOT), and Debate Trainer at Arapus for Business Consulting and Training in Irbid, Jordan. In this capacity, he imparts his expertise in human resource management, trains future trainers, and hones debating skills, further solidifying his reputation as a multifaceted professional dedicated to organizational development and individual growth.

Publications:

  1. The effects of COVID-19 on conditional accounting conservatism in developing countries: evidence from Jordan‏ Cited By : 8, Published By : 2022
  2. A bibliometric review of information technology, artificial intelligence, and blockchain on auditing Cited By : 4, Published By : 2023
  3. EMPIRICAL INVESTIGATION INTO THE INTEGRATION OF CLOUD-BASED ARTIFICIAL INTELLIGENCE IN AUDITING‏ Published By : 2024
  4. Connecting legal compliance and financial integrity: A bibliometric survey of accounting practices in the corporate supply chain‏ Published By : 2024
  5. A bibliometric review of job satisfaction and organizational commitment in businesses area literatures‏

 

Qussai Yaseen | Android Malware Detection | Outstanding Scientist Award

Posted on by ScienceFather

Qussai Yaseen | Android Malware Detection | Outstanding Scientist Award

Assoc Prof Dr Qussai Yaseen Ajman University, United Arab Emirates

He is a cybersecurity expert with a focus on malware detection, network security, and insider threats. With numerous publications in areas such as network security, insider threat mitigation, IoT security, machine learning applied to cybersecurity (security analytics), and spam filtering, he has established himself as a thought leader in the field. Additionally, he actively contributes to the academic community as a chair, TPC (Technical Program Committee) member, and reviewer for various events, conferences, and journals in cybersecurity and other information technology domains. His expertise and contributions play a vital role in advancing knowledge and practices in cybersecurity, making him a respected figure in both academia and industry.

Education:

He pursued his academic journey with dedication, earning his BSc. in Computer Science from Yarmouk University in Irbid, Jordan, from September 1998 to June 2002. Continuing his education, he completed his MSc. in Computer Science at Jordan University of Science and Technology in Irbid, Jordan, from September 2003 to June 2006. Building on his master’s degree, he went on to achieve a Ph.D. in Cybersecurity from the University of Arkansas in Fayetteville, AR, USA, between August 2008 and May 2012. His doctoral dissertation, titled “Mitigating Insider Threat in Relational Database Systems,” was conducted under the guidance of Prof. Brajendra Panda.

Profile:

Experience:

He has played a prominent role in curriculum development within the field of cybersecurity, serving as the Head of the Cybersecurity Program Committee at both Ajman University, UAE, in 2023, and Jordan University of Science and Technology, Jordan, in 2020. Additionally, he has contributed as a cybersecurity expert, serving as a member of the HEAC Committee for the Cybersecurity Accreditation Program at Petra University, Jordan, in 2020, and at Yarmouk University, Jordan, in 2019. Furthermore, he has showcased his expertise as a guest editor for the Special Issue on Big Data and Applications in the Cloud for the International Journal of Cloud Applications and Computing (IJCAC) in Volume 7: 4 Issues (2017). Through these leadership and editorial roles, he has demonstrated his commitment to advancing cybersecurity education and research on a global scale.

Awards and Honors:

He has a rich history of academic engagements, including serving as a Visiting Professor at the University of West Attica in Greece through the Erasmus+ Program in September 2018 and at the University of Piraeus, also in Greece, under the Erasmus+ Program in September 2017. Additionally, he contributed as a Visiting Researcher at the University of Minho in Portugal through the ERASMUS MUNDUS program from May to June 2017. Earlier in his career, he held a Graduate Assistantship at the University of Arkansas, USA, from August 2008 to May 2012, where he furthered his studies in cybersecurity. His academic achievements have been recognized with prestigious awards, including the Earl Beling Doctoral Fellowship from the College of Engineering at the University of Arkansas in 2011 and a Bachelor Education Fellowship at Yarmouk University in Jordan from 1998 to 2002.

Publications:

  1. An Android Malware Detection Approach Based on Static Feature Analysis Using Machine Learning Algorithms Cited By : 16, Published By : 2022
  2. A Novel Machine Learning Approach for Android Malware Detection Based on the Co-Existence of Features Cited By : 9, Published By : 2024
  3. A Comparative Analysis of Machine Learning Algorithms for Android Malware Detection Cited By : 8, Published By : 2023
  4. The Effect of the Ransomware Dataset Age on the Detection Accuracy of Machine Learning Models Cited By : 3, Published By : 2023
  5. A Context-Aware Android Malware Detection Approach Using Machine Learning  Cited By : 6, Published By : 2022
  6. A CNN and Image-Based Approach for Malware Analysis Cited By : 2, Published By : 2022
  7. Spam Email Detection Using Deep Learning Techniques Cited By : 93, Published By : 2021
  8. ReDroidDet: Android Malware Detection Based on Recurrent Neural Network Cited By : 28, Published By : 2021
  9. Machine learning for traffic analysis: a review Cited By : 50, Published By : 2020
  10. Detecting Spam Email with Machine Learning Optimized with Harris Hawks optimizer (HHO) Algorithm Cited By : 20, Published By : 2022

Jin Zhang | Big Data and Research Methods

Posted on by ScienceFather
Prof Dr. Jin Zhang : Leading Researcher in Big Data and Research Methods

University of Wisconsin-Milwaukee, United States.

Congratulations, Prof Dr. Jin Zhang, on winning the esteemed Best Researcher Award from ResearchW! Your dedication, innovative research, and scholarly contributions have truly made a significant impact in your field. Your commitment to advancing knowledge and pushing the boundaries of research is commendable. Here’s to your continued success in shaping the future of academia and making invaluable contributions to your field. Well done!

Profile: Scopus

Education:
  • University of Pittsburgh, School of Information Sciences  Ph.D.
  • Wuhan University, Department of Information Science M.S.
  • Wuhan University, Department of Information Science B.S.
Employment and Working Experience:
  • University of Wisconsin-Milwaukee, School of Information Studies Professor, 2010-
  • University of Wisconsin-Milwaukee, School of Information Studies Associate Professor, 2004-2010
Honors and Awards:
  • ASIS&T Distinguished Member (2021)
  •  Outstanding Paper Award The Utah Academy of Sciences, Arts & Letters  (2015)
  • Emerald Outstanding Reviewer Award (2013)
Computer Experience:
  • Programming languages: SQL, Visual Basic, SPSS, Visual C++ (MFC) and Java.
Professional Societies:
  • American Society for Information Science and technology- 1999 ACM member
  • The ASIS&T Awards & Honors Committee, 2001
  • The ASIST Research Award Committee, 2002
  • ASIST Wisconsin Chapter treasure, 2000-2003
  • ASIST Wisconsin Chapter Chair, 2004-2005
Publications:

Journal papers:

  • Zhao, Y.M., Wu, M. R., and Zhang, J. (2023). Identifying the Driving Factors of Word Co-occurrence: A Perspective of Semantic Relations. Scientometrics, 128, pp. 6471–6494.
  • Zhang, J. and Chen, J.Y. (202X). Investigation of Library Job Demands and Requirements through the Lens of the Job Market.  The Journal of Library Administration, XX(X), XX-XX. Accepted.
  • Zhang, J. and Chen, J.Y. (202X). Skill Analysis of Library and Information Science Professionals. The Journal of Librarianship & Information Science, XX(X), XX-XX. Accepted.
  • Zhang, J., Le, T.W., and Chen, J.Y. (2023). Investigation of Essential Skills for Data Analysts: An Analysis Based on LinkedIn. The Journal of Global Information Management, 31(1), 1-21.
  • Zhu, Y.F.  and Zhang, J. (20XX). An optimization analysis of the subject directory system on the MedlinePlus portal – an investigation of children related health topics. Knowledge Organization, X(X), pp XX-XX. Accepted.
  • Wang, Y.Y. and Zhang, J. (2023). A Study on User-Oriented Subjects of Child Abuse on Wikipedia: A Temporal Analysis of Wikipedia History Versions and Traffic Data”, Journal of Medical Internet Research, 25, e43901.
  • Zhang, J., Wolfram, D., and Ma, F.C. (2023). The Impact of Big Data on Research Methods in Information Science.  Data and Information Management, 7(2), pp. 100038.
  • Chen, Y., Lin, H., Zhang, J., and Zhao, Y. (XXXX). Online Health Information Consumers’ Learning across Health-Related Search Tasks from the Perspective of Retrieval Platform Switching. Journal of Information Science, Accepted.
  • Zhao, Y. & Zhang, J. (2023). Social Networks and Analytics. In J. Wang (Ed.), Encyclopedia of Data Science and Machine Learning (pp. 2528-2538). IGI Global. https://doi.org/10.4018/978-1-7998-9220-5.ch152.
  • Zhao, Y.M., Wu, L.R., Zhang, J., Le, T.W. (2021). How Questions’ Characteristics Affect Their Answer Outcome in Social Question and Answer Websites. The Journal of Global Information Management, 29(6), pp 1-21.
  • Omwando B., and Zhang, J. (2021). Analysis of Malaria Information on a Social Media Platform, HCI International 2021, Lecture Notes in Computer Science, 12796, 298-316.

Selected conference papers:

  • Wang, Y.Y, and Zhang, J. (2024) A Study on Health Consumers’ Emotional Responses to Asthma-Related Videos on YouTube, iConference 2024 – Wisdom, Well-being, Win-win Virtual Academic Program: 15-18 April, 2024. Onsite Academic Program in Changchun, China: 22-26 April, 2024.
  • Bozkurt, S., Hong, Y., Goddard, M., Kahn, E. C., and Zhang, J. (2024). Advancing Patient-Centered Radiology Reporting Through AI: Best practices for Utilizing Natural Language Processing with Patient Friendly Terminologies, ISKO 2024 Conference,  March 20-22, 2024, Wuhan, China.
  • Omwando B., and Zhang, J. (2021). Analysis of Malaria Information on a Social Media Platform, HCI International 2021, Lecture Notes in Computer Science, volume 35, 12796.
  • Zhao, Y., Chen, Y., Zhang, J., Dong, Q., Cao, G., & Zhang, Z. (2019). How did people feel during the Zika virus breakout? A sentiment analysis of Zika virus related posts on Yahoo! Answers. Proceedings of the Association for Information Science and Technology, 56(1), 849–851.

Books / Book Chapters:

  • Zhang, J. (2009). Chapter “The challenges, opportunities, and futures of information retrieval visualization”, in the book Information Resources Plan and Knowledge Science Advances, (pp. 219-240).  Wuhan University Press.
  • Zhang, J. (2008). Visualization for Information Retrieval, Springer.
  • Zhang, J. (2005). Chapter “Information Retrieval for Visualization” in the book Knowledge Technique and Application,  Science and Technology Documentation Publisher, pp. 431-460.

May your efforts cultivate a future where the skies are not only filled with innovation but are also fortified against the challenges that technological progress may bring.

Wishing you continued success in your endeavors to secure the future of Big Data and Research Methods.

Award Manager,
Cybersecurity Awards,
International Research Awards on Cybersecurity and Cryptography,
cybersecurity@researchw.com