Dongsong Zhang | Mobile health | Best Researcher Award

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 Dr.Dongsong Zhang |Mobile health|Best Researcher Award

 Dr.  Dongsong Zhang UNC Charlotte,United States.

 

Dr. Dongsong Zhang is a Professor in the Department of Business Information Systems and Operations Management at the University of North Carolina at Charlotte. He earned his Ph.D. in Management Information Systems from the University of Arizona. Dr. Zhang’s research interests include mobile and intelligent health systems, human-computer interaction, and business analytics. He has published extensively in top-tier journals and conferences, contributing significantly to the fields of information systems and health informatics.

Publication Profile

scopus

Education :

Dr. Dongsong Zhang earned his Ph.D. in Management Information Systems from The Eller College of Management at the University of Arizona in 2002. He also holds an M.S. in Natural Language Processing from the Institute of Psychology, Chinese Academy of Sciences (1995) and a B.S. in Electrical & Computer Engineering from the Branch Campus of Peking University, Beijing, China (1990).

Experience :

Dr. Zhang has extensive experience in academia and research leadership. He is currently the Interim Executive Director of the School of Data Science at the University of North Carolina at Charlotte (UNCC). Previously, he served as the Director of Research at the same school (2020-2024). Since 2018, he has been the Belk Endowed Chair Professor in Business Analytics at the Belk College of Business and a Professor (Courtesy) in Computer Science at UNCC.Prior to joining UNCC, Dr. Zhang was a Full Professor (2014-2018), Associate Professor (2007-2014), and Assistant Professor (2002-2007) in the Department of Information Systems at the University of Maryland, Baltimore County (UMBC). His early career includes research roles at the Center for the Management of Information, University of Arizona (1997-2002), and the Institute of Psychology, Chinese Academy of Sciences (1990-1996).

Research Focus :

Dr. Zhang’s research revolves around data-driven decision-making and intelligent systems, with a particular focus on:AI and Machine Learning for Business IntelligenceFake News Detection & Online Misinformation AnalysisCybersecurity, Phishing Detection, and Behavioral AnalyticsNatural Language Processing in Social Media & Public HealthHuman-Computer Interaction (HCI) & Adaptive SystemsHis projects explore how emerging technologies can be leveraged to improve cybersecurity, healthcare, and business intelligence.

 

Awards:

Dr. Zhang has received significant funding from prestigious organizations, including the National Science Foundation (NSF), National Institutes of Health (NIH), Department of Defense (DoD), and Centers for Disease Control and Prevention (CDC). Some of his notable grants include:NSF-funded research on mobile user authentication and cybersecurity ($718,185)NIH-funded projects on game mechanics for healthcare improvement ($1.2 million)CDC-funded study on homicide classification using NLP and AI ($167,365)Multiple National Natural Science Foundation of China (NSFC) projects on AI-driven business and health analytics ($2.35 million total)In addition to research grants, Dr. Zhang has been recognized with several awards for excellence in research, teaching, and leadership, solidifying his reputation as a leading scholar in data science and business analytics.

Publication :

  • Yan, Z., Peng, F., & Zhang, D. (2025). DECEN: A Deep Learning Model Enhanced by Depressive Emotions for Depression Detection from Social Media Content. Decision Support Systems. Accepted for publication on Feb. 8, 2025.

  • Zhang, D., Shan, G., Lee, M., Zhou, L., & Fu, Z. (2025). MT-GPD: A Multimodal Deep Transfer Learning Model Enhanced by Auxiliary Mechanisms for Cross-domain Online Fake News Detection. Production and Operation Management. Accepted for publication in Jan. 2025.

  • Yu, L., Gong, W., Zhang, D., & Ding, Y. (2025). From Interaction to Prediction: A Multi-Interactive Attention-based Approach to Product Rating Prediction. INFORMS Journal on Computing. Forthcoming.

  • Zhang, D., Zhou, L., Tao, J., Zhu, T., & Gao, G. (2025). KETCH: A Knowledge-Enhanced Transformer-based Approach to Suicidal Ideation Detection from Social Media Content. Information Systems Research (ISR). Published online on May 31, 2024.

  • Peng, F., Zhang, D., & Yan, Z. (2024). Digital Phenotyping-based Depression Detection in the Presence of Comorbidity: An Uncertainty Reasoning Approach. Journal of Management Information Systems (FT 30), 41(4), 931-957.

  • Yu, L., Xing, W., & Zhang, D. (2024). Live Streaming Channel Recommendation Based on Viewers’ Interaction Behavior: A Hypergraph Approach. Decision Support Systems, 184.

  • Chen, S., Yin, S., Guo, Y., Ge, Y., Janies, D., Dulin, M., Brown, C., Robinson, P., & Zhang, D. (2023). Content and Sentiment Infoveillance (CSI): A Critical Component for Modeling Modern Epidemics. Frontiers in Public Health, 11, 1111661. https://doi.org/10.3389/fpubh.2023.1111661. PMID: 3700.

 

Conclusion 

Dr. Zhang is highly suitable for the Best Researcher Award due to his groundbreaking contributions, leadership, and research excellence. While he already has an exceptional track record, increased engagement in industry partnerships, societal impact initiatives, and additional global recognitions could further solidify his position as a world-leading researcher.

 

 

 

Mohamed Yacin Sikkandar | Biomedical Engineering | Best Researcher Award

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Assoc Prof Dr .Mohamed Yacin Sikkandar | Biomedical Engineering | Best Researcher Award

Assoc Prof Dr.Mohamed Yacin Sikkandar,Majmaah University,Saudi Arabia

Assoc. Prof. Dr. Mohamed Yacin Sikkandar is a distinguished academic affiliated with Majmaah University. With expertise in [mention area of expertise, e.g., computer science, literature, etc.], he has made significant contributions to both research and education. Dr. Sikkandar holds the position of Associate Professor, where he actively engages in teaching, research, and academic leadership. His dedication to advancing knowledge and nurturing young minds has earned him recognition within the academic community

Professional Profiles:

Scopus

Qualification:

Graduated from the prestigious Indian Institute of Technology Madras with a Doctorate in Biomedical Engineering.Holds a Master’s degree in Biomedical Engineering from the same institute.Completed Bachelor’s in Instrumentation & Control Engineering from Madurai Kamaraj University, India.

Professional Experience:

Currently serves as an Associate Professor in the Department of Medical Equipment Technology at Majmaah University, Saudi Arabia.Previously held positions as Professor and Head of Department in Biomedical Engineering at Rajalakshmi Engineering College and as Assistant Professor and Head of Department in Instrumentation & Control Engineering at Sethu Institute of Technology.

Research Contributions:

Dr. Sikkandar has been actively involved in various funded research projects, focusing on areas such as finite element analysis, biomedical instrumentation, and medical imaging.Notable projects include studies on scoliotic progression, biomedical rehabilitation methods, and automatic segmentation techniques.

Professional Memberships and Awards :

Holds senior memberships in prestigious societies such as the IEEE Engineering in Medicine and Biology Society and the American Society of Mechanical Engineers.Received awards including UGC Travel Grant Award and International Fellowship on Health Technology Assessment.

Publications:

1.Hidden Markov Model based Predicting of Alzheimer’s Disease with graph cut segmentation using MR Diffusion Tensor Imaging (DTI)Sikkandar, M.Y., Begum, S.S., Algamdi, M.S., …Almutairi, A.F., Almutairi, M.S.^This link is disabled., 2024, 46(2), pp. 4277–4289

2.Sandpiper Optimization Algorithm with Region Growing Based Robust Retinal Blood Vessel Segmentation ApproachAlMohimeed, I., Sikkandar, M.Y., Mohanarathinam, A., …Karim, F.K., Mostafa, S.MThis link is disabled., 2024

3.Optimal Deep Learning-Based Recognition Model for EEG Enabled Brain-Computer Interfaces Using Motor-ImageryRajalakshmi, S., Almohimeed, I., Sikkandar, M.Y., Sabarunisha Begum, S.This link is disabled., 2023, 23(6), pp. 248–253

4.Employing Deep-Learning Approach for the Early Detection of Mild Cognitive Impairment Transitions through the Analysis of Digital Biomarkers
5.Finite Element Analysis Of Customized Knee Implants By Varying Loads During Flexion-Extension Movement
6.Computation of Vascular Parameters: Implementing Methodology and Performance Analysis
7.Numerical investigation of hemodynamic pattern in carotid artery dynamic aneurysm on bifurcation region for early clinical decision making
8.Diabetic Foot Assessment and Care: Barriers and Facilitators in a Cross-Sectional Study in Bangalore, India