Mohammad Alauthman | Detection | Excellence in Research

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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

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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.

 

Iddrisu Salifu | Artificial Intelligence | Best Researcher Award

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Mr. Iddrisu Salifu, Artificial Intelligence, Best Researcher Award

 Iddrisu Salifu at University of Cape Coast, Ghana

Mr. Iddrisu Salifu is a multidisciplinary researcher with a keen focus on coastal zone management, cardiometabolic epidemiology, and economic development. He holds a Master of Philosophy in Integrated Coastal Zone Management and another in Economics, reflecting his diverse academic background. Currently serving as a Research Scientist at the Cardiometabolic Epidemiology Research Laboratory (CERL), University of Cape Coast, Mr. Salifu actively contributes to investigating epidemiological aspects of cardiometabolic diseases while overseeing data collection, analysis, and manuscript preparation efforts. Additionally, he serves as a Tutor at the Institute of Education Sandwich Programme, where he teaches undergraduate economics courses. With a wealth of experience in field research, Mr. Salifu has collaborated on various projects focusing on coastal resilience, fisheries management, and economic development, demonstrating his commitment to addressing pressing societal issues. His dedication to research and his interdisciplinary approach underscores his efforts to advance knowledge and contribute to sustainable development initiatives.

Education:

  • Master of Philosophy (MPhil) in Integrated Coastal Zone Management, Africa Centre of Excellence in Coastal Resilience (ACECoR), University of Cape Coast, 2020-2022.
  • Master of Philosophy (MPhil) in Economics, University of Cape Coast, Ghana, 2017-2019.
  • Bachelor of Arts (BA) in Economics and Geography, University of Cape Coast, 2011-2015.

Profile:

 

Work Experience:

  • Research Scientist: Cardiometabolic Epidemiology Research Laboratory (CERL), Department of Health, Physical Education and Recreation (HPER), University of Cape Coast, July 2023-Present.
  • Tutor: Institute of Education Sandwich Programme, University of Cape Coast, August 2022-Present.
  • Assistant Secretary: African Science Frontiers Initiative (ASFI) Ambassadors, June 2022-Present.
  • Graduate Research Fellow: Chamber for Tourism Industry Ghana (CTI Ghana), August 2020-Present.
  • Field Research Assistant in various projects.

Skills & Competencies:

  • Technical Skills: STATA, R, SPSS, SQL, Excel, Microsoft Word, PowerPoint, Jamovi, JASP.
  • Transferable Skills: Project Management, Teamwork, Leadership, Strategic Thinking, Research Skills, Time Management, Communication, Problem-Solving, Analytical, Innovative, and Creative Mindset.

Honours & Awards:

  • World Bank’s Africa Centre of Excellence Scholarship, December 2020-Present.
  • Sustainable Ocean Alliance (SOA) Microgrant Winner, 2021.
  • CDO’s Power to the Fisher’s Project Microgrant Winner, 2021.

Professional Experience:

Mr. Iddrisu Salifu has accumulated diverse professional experiences across research, academia, and project management. Currently, he serves as a Research Scientist at the Cardiometabolic Epidemiology Research Laboratory (CERL) within the Department of Health, Physical Education, and Recreation (HPER) at the University of Cape Coast. In this role, he plays a pivotal role in devising strategies and plans to investigate epidemiological aspects of cardiometabolic diseases. His responsibilities include overseeing data collection, analysis, and manuscript preparation efforts, as well as supporting research funding efforts by writing grant proposals to secure resources for research projects.

In addition to his research role, Mr. Salifu also contributes to academia as a Tutor at the Institute of Education Sandwich Programme, University of Cape Coast. Here, he teaches various courses in economics at the undergraduate level, leveraging his academic background and expertise to educate and mentor students.

Furthermore, Mr. Salifu has served as an Assistant Secretary for the African Science Frontiers Initiative (ASFI) Ambassadors, where he plays a crucial role in fostering excellence in Africa’s science through competence acquisition, capacity building, and career development initiatives. Additionally, he serves as a Graduate Research Fellow at the Chamber for Tourism Industry Ghana (CTI Ghana), where he is involved in deciding on research programs and methodologies in collaboration with colleagues.

With his extensive experience as a Field Research Assistant on various projects related to agriculture, economics, and education, Mr. Salifu has demonstrated his ability to organize, supervise, and assist in data collection efforts, contributing valuable insights to research initiatives.

Research Interests:

Mr. Iddrisu Salifu’s research interests lie at the intersection of various disciplines, primarily focusing on coastal zone management, cardiometabolic epidemiology, and economic development. He is particularly interested in exploring strategies for enhancing the resilience of coastal communities to environmental hazards and climate change impacts. Additionally, his research delves into the epidemiological aspects of cardiometabolic diseases, aiming to understand their prevalence, risk factors, and public health implications. Furthermore, Mr. Salifu is passionate about examining economic development policies and their effects on sustainable tourism, fisheries management, and environmental conservation. Through his work, he aims to contribute to evidence-based decision-making processes and foster socio-economic development that is both inclusive and environmentally sustainable.

publications:

Title: Monetary policy and macroeconomic indicators: A review of a developing country’s perspectives 2002–2017

  • Authors: SAE Mbilla, PA Atindaana, SG Gadzo, A Adeniyi, I Salifu
  • Journal: Cogent Economics & Finance
  • Volume: 9
  • Issue: 1
  • Pages: 1935530
  • Year: 2021

Title: Partner alcohol consumption and intimate partner violence against women in sexual unions in sub-Saharan Africa

  • Authors: RG Aboagye, BO Ahinkorah, CL Tengan, I Salifu, HY Acheampong
  • Journal: PLoS one
  • Volume: 17
  • Issue: 12
  • Pages: e0278196
  • Year: 2022

Title: Digital paradigm shift: Unraveling students’ intentions to embrace Tablet-based Learning through an extended UTAUT2 model

  • Authors: F Arthur, V Arkorful, I Salifu, S Abam Nortey
  • Journal: Cogent Social Sciences
  • Volume: 9
  • Issue: 2
  • Pages: 2277340
  • Year: 2023

Title: Effect of household water treatment on under-five diarrhoea in Ghana

  • Author: I Salifu
  • Institution: University of Cape Coast
  • Year: 2020

Title: Economics students’ behavioural intention and usage of ChatGPT in higher education: a hybrid structural equation modelling-artificial neural network approach

  • Authors: I Salifu, F Arthur, V Arkorful, S Abam Nortey, R Solomon Osei-Yaw
  • Journal: Cogent Social Sciences
  • Volume: 10
  • Issue: 1
  • Pages: 2300177
  • Year: 2024

Title: Economics students’ behavioural intention and usage of ChatGPT in higher education: a hybrid structural equation modelling-artificial neural network approach

  • Authors: RSOY Iddrisu Salifu, Francis Arthur, Valentina Arkorful, Sharon Abam Nortey
  • Journal: Cogent Social Sciences
  • Volume: 10
  • Issue: 1
  • Pages: 28
  • Year: Undisclosed

Jin Zhang | Big Data and Research Methods

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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