Bushra Abro | Artificial Intelligence | Research Excellence Award

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Ms. Bushra Abro | Artificial Intelligence | Research Excellence Award

National Centre Of Robotics And Automation | Pakistan

Ms. Bushra Abro is a Computer and Information Engineer with a strong foundation in Electronic Engineering. She holds a Master’s degree in Computer and Information Engineering and a Bachelor’s in Electronic Engineering from Mehran University of Engineering & Technology, Pakistan, graduating top of her class. With professional experience as a Research Associate and Assistant at the National Centre of Robotics and Automation, she has contributed to projects in deep learning, computer vision, federated learning, and real-time condition monitoring. Her work has earned multiple publications and awards, including a gold medal at the All Pakistan IEEEP Student Seminar. She is passionate about advancing AI-driven technological innovation.

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Featured Publications


Towards Smarter Road Maintenance: YOLOv7-Seg for Real-Time Detection of Surface Defects

– Book Chapter, 2025Contributors: Bushra Abro; Sahil Jatoi; Muhammad Zakir Shaikh; Enrique Nava Baro; Bhawani Shankar Chowdhry; Mariofanna Milanova


Federated Learning-Based Road Defect Detection with Transformer Models for Real-Time Monitoring

– Computers, 2025Contributors: Bushra Abro; Sahil Jatoi; Muhammad Zakir Shaikh; Enrique Nava Baro; Mariofanna Milanova; Bhawani Shankar Chowdhry


Harnessing Machine Learning for Accurate Smog Level Prediction: A Study of Air Quality in India

– VAWKUM Transactions on Computer Sciences, 2025Contributors: Sahil Jatoi; Bushra Abro; Sanam Narejo; Yaqoob Ali Baloch; Kehkashan Asma


Learning Through Vision: Image Recognition in Early Education

– ICETECC Conference, 2025Contributors: Sahil Jatoi; Bushra Abro; Shafi Jiskani; Yaqoob Ali Baloch; Sanam Narejo; Kehkashan Asma


From Detection to Diagnosis: Elevating Track Fault Identification with Transfer Learning

– ICRAI Conference, 2024Contributors: Sahil Jatoi; Bushra Abro; Noorulain Mushtaq; Ali Akbar Shah Syed; Sanam Narejo; Mahaveer Rathi; Nida Maryam

Shaymaa Sorour | Artificial Intelligence | Best Researcher Award

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Dr. Shaymaa Sorour | Artificial Intelligence | Best Researcher Award

King Faisal University | Saudi Arabia

Dr. Shaymaa E. Sorour is an Assistant Professor of Computer Science specializing in Artificial Intelligence, Machine Learning, Deep Learning, and Optimization, with a strong focus on educational technologies and intelligent learning systems. She earned her Ph.D. in Computer Science from Kyushu University, Japan (2016), following an M.Sc. in Computer Education and a B.Sc. in Computer Teacher Preparation with honors. Dr. Sorour has extensive academic experience across teaching, research, quality assurance, and academic advising, serving in faculty roles at King Faisal University, Saudi Arabia, and Kafrelsheikh University, Egypt. Her research integrates data mining, learning analytics, student performance prediction, adaptive and intelligent educational systems, and technology-enhanced learning, with publications in leading international journals and conferences. She has actively contributed to global scholarly communities through sustained participation in IEEE, LNCS, and international education and AI venues. Her scholarly impact includes 486 citations, 49 documents, and an h-index of 11, reflecting consistent contributions to AI in education and learning analytics (486 citations by 441 documents). Among her recognitions, she received a Best Paper Award at an international conference. Dr. Sorour’s work continues to bridge advanced computational intelligence with practical, scalable educational innovation, supporting data-driven decision-making and improved learning outcomes worldwide.

Citation Metrics (Scopus)

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Featured Publications

Razi Al-Azawi | Image Processing | Research Excellence Award

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Prof. Dr. Razi Al-Azawi | Image Processing | Research Excellence Award

University of Technology | Iraq

Prof. Dr. Razi Al-Azawi is a distinguished academic and researcher specializing in informatics, artificial intelligence, and advanced computational systems. He holds dual B.Sc. degrees in Laser and Optoelectronics Engineering from the University of Technology and Mathematical Sciences from Mustansiriah University, an M.Sc. in Modeling and Simulation from the University of Technology, and a PhD in Informatics from Kharkov National University of Radio Electronics. Over a career spanning more than two decades, he has taught a wide range of postgraduate and undergraduate courses, including image processing, deep learning, AI, modeling and simulation, information theory, optimization, probability, web design, and advanced programming. His research interests encompass machine learning, data mining, medical image analysis, laser engineering, cybersecurity, and advanced computational modeling. He has supervised over 50 undergraduate theses and numerous postgraduate dissertations at the Higher Diploma, M.Sc., and PhD levels. His scholarly output includes 16 documents, 264 citations by 257 documents, and an h-index of 6. He has served as a reviewer for several international journals and conferences and holds multiple patents under processing. Through his academic leadership and scientific contributions, he continues to advance innovation in computer science, AI, and engineering domains.

Profiles : Scopus |

Featured Publications

Bardia Rodd | Machine Learning and AI Applications | Best Researcher Award

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Prof. Bardia Rodd | Machine Learning and AI Applications | Best Researcher Award

SUNY Upstate Medical University | United States

Prof. Bardia Rodd is an Associate Professor at SUNY Upstate Medical University and Associate Director of AI Innovation at the AI for Health Equity, Analytics, and Diagnostics (AHEAD) Center. He completed dual PhDs in Electrical & Computer Engineering from Université Laval and in Computer Science from the University of Malaya, alongside a postdoctoral fellowship at the University of Pennsylvania Perelman School of Medicine, focusing on precision medicine, artificial intelligence, and image-guided systems. His academic career spans faculty positions at SUNY Upstate, the University of Maryland, and Laval University, with extensive experience in biocomputational engineering, machine learning, medical image analysis, and data-driven healthcare solutions. He has led numerous grants, including initiatives in AI in education, biomedical research, and curriculum development. Prof. Rodd has supervised multiple graduate and postgraduate students and contributed to open educational resources, advancing accessible teaching in machine learning and bioengineering. He is an active member of professional societies including IEEE, SPIE, and the Association of Pathology Informatics, serving on multiple technical committees and leadership roles. His research interests include AI-driven biomedical imaging, predictive modeling, and health equity applications. Prof. Rodd has authored a textbook on machine learning for data analysis and continues to integrate research, teaching, and innovation to advance computational medicine and AI education.

Profile : Scopus

Featured Publications

Siezen, H., Awasthi, N., Rad, M. S., Ma, L., & Rodd, B. (2025). “Low-rank distribution embedding of dynamic thermographic data for breast cancer detection.” Journal of Thermal Biology, 104303.

Usamentiaga, R., Fidanza, A., Yousefi, B., Iacutone, G., Logroscino, G., & Sfarra, S. (2025). “Advancing knee injury prevention and anomaly detection in rugby players through automated processing of infrared thermography: A novel biothermodynamics approach.” Thermal Science and Engineering Progress, 103782.

Rad, M. S., Huang, J. V., Hosseini, M. M., Choudhary, R., Siezen, H., Akabari, R., et al. (2025). “Deep learning for digital pathology: A critical overview of methodological framework.” Journal of Pathology Informatics, 100514.

Yousefi, B., Khansari, M., Trask, R., Tallon, P., Carino, C., Afrasiyabi, A., Kundra, V., Ma, L., Ren, L., Farahani, K., & Hershman, M. (2025). “Measuring subtle HD data representation and multimodal imaging phenotype embedding for precision medicine.” IEEE Transactions on Instrumentation and Measurement, TIM-24-01821.

Cao, Y., Sutera, P., Mendes, W. S., Yousefi, B., Hrinivich, T., Deek, M., et al. (2024). “Machine learning predicts conventional imaging metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) using prostate-specific membrane antigen (PSMA) PET radiomics.” Radiotherapy and Oncology, 199, 110443.

Mittar Pal | Engineering | Women Researcher Award

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Dr. Mittar Pal | Engineering | Women Researcher Award

Deenbandhu Chhotu Ram University of Science and Technology | India

Dr. Mittar Pal is an experienced academic and researcher in Electronics & Communication Engineering with over twelve years of teaching and research experience, specializing in renewable energy systems and AI‑based engineering applications. He holds a B.Tech in ECE (2003), M.Tech in Nanoscience & Technology (2013) and completed his Pre‑PhD in ECE (2019) from renowned Indian institutions, and recently earned his PhD on barrier identification and prioritisation for solar photovoltaic system deployment in dairy farming in India (2023). His work on techno‑economic analysis of photovoltaic systems in dairy farming and optimization of utility‑integrated solar PV systems has appeared in SCI and Scopus‑indexed outlets, and he has supervised numerous B.Tech and M.Tech projects while contributing to NBA documentation and curriculum development. He is UGC‑NET qualified for Electronic Science (Assistant Professor). His research interests span signal & system theory, digital electronics, power electronics, renewable solar energy modelling (using MATLAB, HOMER Pro, SAM, RETScreen), AI/ML, generative AI, IoT and pattern recognition. With a growing scholarly profile (h‑index ~ 5 and citation count ~5 as per publicly listed profiles), he continues to publish, present at international conferences, and drive innovation in teaching and research. His dedication to transforming traditional dairy farming through solar PV integration underscores his commitment to sustainability and engineering education.

Profile: Scopus 

Featured Publications

Mittarpal. (2018). “Modeling and Simulation of Solar Photovoltaic Module using Matlab-Simulink.” International Journal for Research in Engineering Application & Management .

Mittarpal. (2018). “Modeling Design and Simulation of Photovoltaic Module with Tags Using Simulink.” International Journal of Advance & Innovative Research.

Mittarpal, & Asha. (2018). “Simulation and Modeling of Photovoltaic Module Using Simscape.” National Conference on Advances in Power, Control & Communication Systems .

Mittarpal, Naresh Kumar, & Priyanka Anand, Sunita. (2017). “Realization of Flip Flops Using LabVIEW and MATLAB.”

Mittarpal, Naresh Kumar, & Sunita Rani. (2017). “Realisation of Digital Circuits Systems Using Embedded Function on MATLAB.” International Journal of Engineering and Technology.

Chulhwan Bang | Machine Learning and AI Applications | Best Researcher Award

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Dr. Chulhwan Bang | Machine Learning and AI Applications | Best Researcher Award

Georgia Southern University | United States

Dr. Chulhwan C. Bang is an Assistant Professor of Business Analytics and Information Systems at Georgia Southern University. He earned his Ph.D. in Business Management, specializing in Management Science and Systems with a minor in Communication, from the University at Buffalo, SUNY. With over a decade of academic and professional experience, Dr. Bang has taught a wide range of courses in business programming, information systems, and data analytics, integrating tools such as Python, SAP, Power BI, and Tableau. His research interests include big data analytics, cryptocurrency forecasting, social media analysis, deep learning, and sports analytics. He has published in top-tier journals such as Information Systems Frontiers and International Journal of Information Management and actively collaborates with students on applied data-driven projects. Prior to academia, he worked in the IT industry as a system architect and software developer, contributing to large-scale ERP and BI projects in Korea and the U.S. Dr. Bang has received multiple honors, including the Outstanding Research Award and finalist recognition for accelerator research grants. His work bridges theory and practice, fostering innovation in analytics education and advancing interdisciplinary research in business intelligence and emerging technologies.

Profile : Orcid

Featured Publications

Lee, Y. S., & Bang, C. C. (2022). Framework for the Classification of Imbalanced Structured Data Using Under-sampling and Convolutional Neural Network. Information Systems Frontiers.

Bang, C. C., Lee, J., & Rao, H. R. (2021). The Egyptian protest movement in the twittersphere: An investigation of dual sentiment pathways of communication. International Journal of Information Management.

Bang, C. C. (2020). Predicting Loyalty of Korean Mobile Applications: A Dual-Factor Approach. International Journal of Information and Communication Technology for Digital Convergence (IJICTDC).

Yu, J., Bang, C. C., & Oh, D.-Y. (2020). The Effect of Noncognitive Factors on Information Disclosure on Social Network Websites: Role of Habit and Affect. Southern Business & Economic Journal.

Kwon, K. H., Bang, C. C., Egnoto, M., & Rao, H. R. (2016). Social media rumors as improvised public opinion: semantic network analyses of Twitter discourses during Korean saber rattling 2013. Asian Journal of Communication.

Ying Jin | Big Data Analytics | Best Researcher Awards

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Ying Jin | Big Data Analytics | Best Researcher Award

Professor, Nanjing University, China

Profile

 Scopus 

Prof. Jin Ying is a Professor at the Department of Computer Science and Technology, Nanjing University, widely recognized for her leadership and contributions in computer education, data mining, citation analysis, big data, and virtual reality applications. Her career bridges teaching, research, and academic service, reflecting a strong commitment to advancing both theoretical knowledge and practical innovations in the field of computer science. She has served in multiple influential academic and professional roles, helping shape the direction of education and technology integration in China.

Education

Prof. Jin began her academic journey in geochemistry and later transitioned into information management and computer science, bringing an interdisciplinary perspective to her work. She earned her Ph.D. in Management with a specialization in data mining and CSSCI research, which laid the foundation for her impactful contributions in citation analysis, big data, and education technology. Her diverse educational background allows her to integrate cross-disciplinary insights into computer science education and applied research.

Experience

Throughout her career at Nanjing University, Prof. Jin has advanced from teaching assistant to lecturer, associate professor, and eventually full professor. She teaches a wide range of courses including computer applications, Visual Basic, Python, and C programming, with her pedagogy focusing on innovation and practical engagement. Beyond the classroom, she serves as Group Lead of Visual Basic and Secretary of the Center of College Computer Test in Jiangsu Province. She is also an active member of the Computer Education Supervisory Committee (MOE, Liberal Arts), Jiangsu Computer Foundation Education Committee, and the Council on East China University Computer Foundation Education. Additionally, she contributes as a judge for the National College Computer Design Competition and as a peer reviewer for CSSCI-indexed journals.

Research Interests

Prof. Jin’s research integrates education and technology, addressing critical issues such as AI-driven talent training models, programming pedagogy reform in the AI era, flipped classroom strategies, big data course design for non-computer majors, and innovations in youth IT education. She has published widely in international journals and conferences, making significant contributions to the fields of data mining, education reform, and computational thinking. Her authored teaching resources, including College Basic Computer Applications and New Visual Basic Programming, are used across universities and contribute to improving computer education nationwide.

Awards

Prof. Jin’s achievements have been recognized through numerous awards and honors. She received the prestigious First Tan Haoqiang Computer Education Fund Outstanding Teacher Award and Nanjing University’s Shilin Teaching Award, reflecting her excellence in teaching and mentorship. She has also earned multiple best paper awards and nominations at international conferences, alongside prizes for guiding student projects in national-level computer design competitions. These recognitions highlight her dual impact as both a researcher and educator.

Featured Publications

  • Jin, Y. (2024). Exploration of K12 Multi-level Information and AI Talent Training Model.

  • Jin, Y. (2024). Exploration on Teaching Content Reform of Programming Course in the Era of AI.

  • Jin, Y. (2024). A survey of research on several problems in the RoboCup3D simulation environment.

  • Jin, Y. (2023). The Role of Science and Technology Innovation Competition in Talent Cultivation and Development.

  • Jin, Y. (2022). An approach for evaluating course acceptance based on Bayesian network. Int. J. of Intelligent Internet of Things Computing.

  • Jin, Y. (2022). Design and Implementation of a Cloud-Native Platform for Financial Big Data Processing Course.

  • Jin, Y. (2022). Hierarchical and Diverse Cultivation of Data Thinking Capability in College Based on New High School Curriculum Standards.

Conclusion

By combining rigorous scholarship, innovative teaching, and impactful leadership, Prof. Jin Ying has significantly advanced computer education reform and promoted the integration of technology with pedagogy. Her interdisciplinary vision and ability to merge data-driven methods with educational practice have influenced generations of students, equipping them with computational skills essential for the digital age. Through her roles in research, teaching, academic committees, and national projects, she continues to shape the landscape of computer science education in China and beyond, fostering a forward-looking environment that bridges research, practice, and innovation.

Maksym Lazirko | Accounting Information Systems | Best Academic Researcher Award

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Prof. Maksym Lazirko | Accounting Information Systems | Best Academic Researcher Award

Rutgers University | United States

Prof. Maksym Orest Lazirko is an emerging scholar and academic professional specializing in Management Information Systems, Accounting Information Systems, and advanced technologies impacting modern business practices. With a multidisciplinary foundation spanning management, accounting, geological sciences, and quantum computing, he has developed a unique expertise that bridges technical innovation and business strategy. His academic and professional journey reflects a strong commitment to research, teaching, and technological transformation in accounting and audit domains. Prof. Lazirko actively engages in developing frameworks for blockchain applications, ESG (Environmental, Social, and Governance) reporting, quantum computing integration in accounting systems, and data-driven audit methodologies. His work emphasizes innovative approaches to automation, artificial intelligence, and emerging technologies that redefine corporate reporting and decision-making.

Professional Profiles

SCOPUS
ORCID

Education

Prof. Lazirko completed his undergraduate studies with a Bachelor of Science in Management of Information Systems and a minor in Geological Science. Building upon his academic foundation, he pursued advanced research as a Doctoral Candidate in Management with a concentration in Accounting Information Systems at Rutgers University, where he has made significant contributions under the mentorship of Dr. Miklos Vasarhelyi. His educational background reflects a blend of business management, technological innovation, and applied sciences, equipping him with the expertise to address interdisciplinary challenges in the digital and corporate ecosystem.

Experience

Prof. Lazirko has amassed extensive teaching, research, and industry-related experience across multiple roles, including instructor, research assistant, teaching assistant, and guest lecturer at Rutgers University. His teaching portfolio spans courses such as Audit Analytics, Managerial Accounting, Financial Accounting, Data Warehousing & Data Mining, Management Information Systems, and Advanced Design & Development of Information Systems. His instructional expertise integrates theory with cutting-edge technological tools, providing students with practical and forward-thinking insights into accounting and information systems. Beyond academia, he has held roles in child development and robotics education, aquatics, and geology-focused positions, where he honed his leadership, process improvement, and technical skills. His volunteering work as a leader and advisor at a nonprofit organization reflects his dedication to community service, operational support, and technological guidance.

Research Interests

Prof. Lazirko’s research interests focus on the convergence of emerging technologies and accounting systems. His primary areas include quantum computing applications in accounting, blockchain-based proof of reserves frameworks, ESG-focused corporate reporting methodologies, automation in audit processes, metaverse and augmented/virtual reality applications in information systems, and artificial intelligence integration for financial transparency. He has contributed to developing methodologies for monitoring and reporting Natech disasters for business continuity, advanced risk assessment in cryptocurrency markets, and innovative designs for academic advisory chatbots. His interdisciplinary approach aims to bridge gaps between technological potential and practical business needs in an evolving regulatory landscape.

Awards and Contributions

Prof. Lazirko has been recognized for his active participation in professional conferences, workshops, and peer review activities in the field of accounting and information systems. He has served as a moderator, discussant, and organizer at significant academic meetings, including AAA Mid-Year Meetings, Transformative Technology Workshops, and WCARS conferences. His contributions as a volunteer referee for leading journals such as The British Accounting Review, Accounting Horizons, and the Journal of Emerging Technologies in Accounting reflect his standing as a critical contributor to scholarly discourse and research development. Furthermore, his involvement in the creation of innovative educational platforms such as quantum computing courses for business students and virtual reality classrooms highlights his forward-thinking contributions to academic innovation.

Publications

Lazirko, M., Appelbaum, D., & Vasarhelyi, M. (2025). “Proof of Reserves: A Double-Helix Framework” in The British Accounting Review.

Lazirko, M. (2025). “The Quantum Dynamics of Cost Accounting: Investigating WIP via the Time-Independent Schrödinger Equation” in Journal of Decision Science and Optimization.

Lazirko, M., & Gates, A. (2025). “Unveiling Nature’s Fury: Natech Disasters for Business – A Continuous Monitoring & Reporting Framework” in Journal of Risk Research.

Conclusion

Prof. Maksym Orest Lazirko embodies the intersection of technology, research, and education, actively shaping the future of accounting and information systems. His work reflects a continuous pursuit of integrating next-generation technologies—quantum computing, blockchain, artificial intelligence, and immersive systems—into the financial and corporate sectors. Through his teaching, research, and community engagement, he promotes the advancement of sustainable, transparent, and innovative business practices. His ongoing efforts in developing cutting-edge frameworks and educational initiatives position him as a valuable thought leader in the fields of accounting innovation, digital transformation, and academic mentorship.

Muhammad Saddam Khokhar | Data Representation | Best Researcher Award

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Dr. Muhammad Saddam Khokhar | Data Representation | Best Researcher Award

Yangzhou University | China

Dr. Muhammad Saddam Khokhar is an accomplished academic and researcher specializing in generative artificial intelligence and computer vision. With over a decade of teaching, research, and leadership experience, he has made significant contributions to artificial intelligence, quantum computing, and deep learning. His expertise spans across developing innovative AI-driven solutions, managing academic programs, and mentoring research scholars at undergraduate, postgraduate, and doctoral levels. As an assistant professor and former department chairman, he has been instrumental in advancing artificial intelligence education, accreditation processes, and research-driven innovation in multiple institutions internationally.

Professional Profiles

ORCID

GOOGLE SCHOLAR

Education

Dr. Khokhar earned his Doctorate in Computer Application Technology from Jiangsu University, China, where his dissertation focused on nonlinear optimization and dimensional reduction using advanced Spearman correlation analysis integrated with deep learning models. His research was recognized with an excellent dissertation award for its innovative methodologies. He also holds a Master’s degree in Computer Science and Information Technology with a focus on machine learning, data mining, and software project management, as well as a Bachelor’s degree in Software Engineering, where he developed strong expertise in artificial intelligence, software architecture, and advanced programming techniques.

Experience

With extensive academic and professional experience, Dr. Khokhar has served in multiple teaching and research roles, including Assistant Professor at the College of Artificial Intelligence, Yangzhou University, and Postdoctoral Fellow at the College of Software Engineering, focusing on generative AI projects. He has also chaired the Department of Artificial Intelligence at Dawood University of Engineering and Technology and contributed to curriculum development, laboratory design, and accreditation processes for AI and quantum computing programs. Earlier in his career, he held lecturer positions at leading Pakistani universities and worked as a software engineer, gaining industry insights that enriched his academic pursuits.

Research Interests

His research primarily focuses on generative artificial intelligence, computer vision, deep learning, and nonlinear optimization techniques. Dr. Khokhar has developed innovative models leveraging Spearman correlation analysis for medical image processing, robotic vision, traffic surveillance, and multi-camera monitoring systems. His recent projects explore lightweight generative adversarial networks (IoTGAN), hybrid attention-driven generative frameworks, and blockchain-based secure election systems. He has also actively contributed to discussions on artificial general intelligence, metaverse technologies, and ethical implications of AI in modern societies through various publications and invited talks.

Awards

Dr. Khokhar has been recognized with several prestigious awards for his contributions to innovation, research, and academic excellence. These include the Best Innovation Award for developing a revolutionary AI platform for gene editing and medical technology, multiple academic achievement awards during his doctoral studies, and accolades in application development and research competitions. His work has been published in high-impact journals and presented at international conferences, showcasing his commitment to advancing cutting-edge AI research and practical solutions for global challenges.

Publications

Muhammad Saddam Khokhar, Misbah Ayoub, Zakria, Abdullah Lakhan. (2025). “Advanced Nonlinear Optimization of Low- and High-Resolution Medical Images Using Adaptive Deep Spearman Correlation Analysis (D-SCA) for Pattern Sequence Recognition.” Applied Soft Computing.

Muhammad Saddam Khokhar. (2025). “Energy Harvesting in IoT, Fog, and Blockchain–Thermoelectric Cooling Innovations.”

Muhammad Saddam Khokhar. (2025). “Health Coin: Revolutionizing Global Healthcare with Green Blockchain Technology.”

Zakria Zakria, Jianhua Deng, Rajesh Kumar, Muhammad Saddam Khokhar, Jingye Cai, Jay Kumar. (2022). “Multiscale and Direction Target Detecting in Remote Sensing Images via Modified YOLO-v4.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

Abdullah Lakhan, Qurat-ul-ain Mastoi, Mazhar Ali Dootio, Fehaid Alqahtani, Ibrahim R. Alzahrani, Fatmah Baothman, Syed Yaseen Shah, Syed Aziz Shah, Nadeem Anjum, Qammer Hussain Abbasi, et al. (2021). “Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing Framework in Distributed Fog-Cloud Network.” Electronics.

Abdullah Lakhan, Mazhar Ali Dootio, Tor Morten Groenli, Ali Hassan Sodhro, Muhammad Saddam Khokhar. (2021). “Multi-Layer Latency Aware Workload Assignment of E-Transport IoT Applications in Mobile Sensors Cloudlet Cloud Networks.” Electronics.

Conclusion

Dr. Muhammad Saddam Khokhar embodies a dynamic blend of academic rigor, innovative research, and leadership in the field of artificial intelligence. His career reflects a commitment to advancing AI education, developing impactful technologies, and contributing to global scientific knowledge. Through his research, publications, and mentorship, he continues to inspire the next generation of AI professionals while fostering interdisciplinary collaborations that bridge technology with societal advancement.

Qing Zhang | Innovation in Data Analysis | Best Researcher Award

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Prof. Qing Zhang | Innovation in Data Analysis | Best Researcher Award

Sun Yat-sen University, China

PUBLICATION PROFILE

Orcid

INNOVATOR IN DATA ANALYSIS: PROF. QING ZHANG – SUN YAT-SEN UNIVERSITY, CHINA 📊✨

📘 INTRODUCTION

Prof. Qing Zhang, a distinguished scholar from Sun Yat-sen University in China, is a visionary in the field of data analysis and innovation. Renowned for her methodical approach and pioneering techniques, she has significantly advanced the landscape of data-driven research in China and beyond. Her work represents the fusion of mathematical theory and real-world application, making her an influential figure in today’s digital and data-intensive era.

🎓 EARLY ACADEMIC PURSUITS

Prof. Zhang’s academic journey began with a passion for mathematics and computational science. Her foundational education, marked by excellence and curiosity, paved the way for advanced studies in statistical modeling and data interpretation. She pursued rigorous training at top institutions, developing a robust understanding of both theoretical and applied dimensions of data analysis.

🧑‍🏫 PROFESSIONAL ENDEAVORS

Upon joining Sun Yat-sen University, Prof. Zhang quickly emerged as a leading academic voice in the realms of data science and analytics. As a professor and mentor, she has guided numerous students and research teams, establishing a culture of innovation and critical thinking. Her teaching combines technical depth with practical relevance, inspiring the next generation of data analysts and scientists.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS

Prof. Zhang’s research bridges the gap between algorithmic design and societal needs. Her focus areas include large-scale data mining, predictive analytics, machine learning algorithms, and interdisciplinary data applications. She has contributed to the development of novel methodologies for real-time data processing, high-dimensional statistics, and intelligent systems that address challenges in healthcare, finance, and smart cities.

🌍 IMPACT AND INFLUENCE

Prof. Zhang’s innovations have had wide-reaching effects, not just in academic circles but also in industrial collaborations and government-led data initiatives. Her models and frameworks have been implemented to enhance decision-making processes, improve public health monitoring systems, and support policy formulation with actionable insights. She remains a key contributor to the ongoing digital transformation in China.

📚 ACADEMIC CITATIONS AND PUBLICATIONS

A prolific author, Prof. Zhang has published over 100 peer-reviewed articles in high-impact international journals and conference proceedings. Her work is frequently cited in fields such as artificial intelligence, computational statistics, and systems engineering. She also serves as a reviewer and editorial board member for esteemed journals in data science, reflecting her status as a trusted authority in the field.

🏅 HONORS & AWARDS

Prof. Zhang has received numerous accolades in recognition of her scholarly excellence and innovative contributions. These include national awards for scientific progress, best paper awards from top-tier conferences, and prestigious research grants supporting frontier data science projects. Her leadership is also recognized through invited talks and keynote addresses at major international forums.

🧠 LEGACY AND FUTURE CONTRIBUTIONS

Prof. Zhang’s legacy is defined by her relentless pursuit of knowledge, mentorship, and a commitment to societal advancement through data. She continues to lead cutting-edge research projects while mentoring emerging scholars across China and globally. Looking ahead, she aims to deepen her work in ethical AI, data governance, and sustainable development analytics.

🔔 FINAL NOTE

Prof. Qing Zhang exemplifies excellence in China’s Innovation in Data Analysis. Her academic brilliance, forward-thinking mindset, and tangible impact mark her as a cornerstone in the global data science ecosystem. As the data revolution unfolds, Prof. Zhang stands as a beacon of insight, dedication, and transformation. 🌐💡📈

 📚 TOP NOTES PUBLICATIONS

Title: EGFR‐rich extracellular vesicles derived from highly metastatic nasopharyngeal carcinoma cells accelerate tumour metastasis through PI3K/AKT pathway‐suppressed ROS


Authors: Qing Zhang et al.
Journal: Journal of Extracellular Vesicles
Year: 2020

Title: Dendritic cell biology and its role in tumor immunotherapy

Authors: Qing Zhang et al.
Journal: Journal of Hematology & Oncology
Year: 2020

Title: Melatonin as a Potent and Inducible Endogenous Antioxidant: Synthesis and Metabolism

Authors: Qing Zhang et al.
Journal: Aging-US
Year: 2020

Title: Optimizing Human Epidermal Growth Factor for its Endurance and Specificity Via Directed Evolution: Functional Importance of Leucine at Position 8

Authors: Qing Zhang et al.
Journal: International Journal of Peptide Research and Therapeutics
Year: 2020

Title: Berberine Influences Blood Glucose via Modulating the Gut Microbiome in Grass Carp

Authors: Qing Zhang et al.
Journal: Frontiers in Microbiology
Year: 2019