Assist. Prof. Dr. Ali sayghe | Cyber-Physical Security and Sensnor | Best Researcher Award

Assist. Prof. Dr. Ali sayghe | Cyber-Physical Security and Sensnor | Best Researcher Award

Department of Electrical Engineering/ Yanbu Industril College | Saudi Arabia

Author Profile 

Orcid

Summary

Ali sayghe is an assistant professor and researcher specializing in control systems and cyber-physical security for power systems, with a strong academic background from florida state university, arizona state university, and the university of illinois at chicago. his career combines teaching at yanbu industrial college with innovative research on digital twins, intrusion detection, and the resilience of industrial power systems. blending linear and nonlinear control theory with machine learning, he addresses the evolving challenges of critical infrastructure. his work is widely recognized in academic cites and continues to shape advancements in secure and reliable energy systems.

Early academic pursuits

Ali Sayghe’s educational journey reflects a strong foundation in engineering and technology, beginning with an associate’s degree in telecommunications technology from the college of telecommunication and electronics. he advanced to earn a bachelor of science in electrical and electronic engineering technology with a specialization in telecommunications engineering from arizona state university, followed by a master of technology in electronic engineering technology from the same institution. his pursuit of excellence led him to doctoral research, first at the university of illinois at chicago and later completing a phd in control and cyber-physical security for power systems at florida state university. throughout these formative years, his academic pursuits laid the groundwork for his expertise in control systems, cyber-physical security, and critical infrastructure resilience.

Professional endeavors

Ali sayghe has served as an assistant professor at yanbu industrial college in yanbu al sinaiyah, al madinah, saudi arabia. he has been deeply engaged in teaching, mentoring, and guiding engineering students, bringing real-world applications into the classroom. his professional endeavors also encompass research collaborations in control systems and cyber-physical security for the power and energy industry, often integrating machine learning into advanced control designs. this combination of teaching and applied research underscores his commitment to both academia and industry relevance.

Contributions and research focus

Ali Sayghe’s research contributions center on the reliability, resilience, and security of industrial power systems. he has advanced work in digital twins, intrusion detection systems, and robust control strategies, addressing both linear and nonlinear frameworks. integrating control systems and cyber-physical security with modern machine learning techniques, his work ensures that power infrastructure remains protected against evolving threats. these contributions have been published in reputable scientific journals and conference proceedings, showcasing his role as an innovative researcher in this specialized domain.

Impact and influence

Through his dual role as educator and researcher, ali sayghe has significantly influenced the field of control systems and cyber-physical security for power systems. his ability to simplify complex engineering concepts for students has fostered a generation of engineers equipped to handle the challenges of modern power networks. in the research community, his studies on digital twins and industrial system security are shaping best practices for safeguarding critical infrastructure. his influence extends internationally, bridging the academic and industrial sectors.

Academic cites

Ali sayghe’s work has been cited in multiple research papers, highlighting the relevance and applicability of his findings. his academic cites reflect recognition from fellow scholars and practitioners working in control systems, cyber-physical security, and power system engineering. these citations are a testament to the practical value and originality of his research, especially in areas that combine control theory with cutting-edge machine learning approaches.

Legacy and future contributions

Ali sayghe’s legacy is rooted in his dedication to creating safer and more resilient power systems through innovative control and cyber-physical security strategies. looking forward, he aims to further expand the integration of digital twins, predictive analytics, and artificial intelligence into industrial applications. his vision includes fostering newcomer socialization within academic and research settings, ensuring that new researchers quickly adapt and contribute to the evolving landscape of control systems and cyber-physical security for power systems. his future contributions promise to shape both the educational framework and technological innovations in the energy sector.

Publications 

Title: Security Threats and Risk Exposure in Wireless Sensor Networks for Industrial Control Systems: A Case Study
Author(s): Ali Sayghe
Journal: SSRN

Title: Digital Twin-Driven Intrusion Detection for Industrial SCADA: A Cyber-Physical Case Study
Author(s): Ali Sayghe
Journal: Sensors

Title: Digital Twin-Driven Intrusion Detection for Industrial SCADA: A Cyber-Physical Case Study
Author(s): Ali Sayghe
Journal: Preprints

Title: A Survey of Machine Learning Methods for Detecting False Data Injection Attacks in Power Systems
Author(s): Ali Sayghe, Y. Hu, I. Zografopoulos, X. Liu, R.G. Dutta, Y. Jin, C. Konstantinou
Journal: arXiv

Title: Survey of Machine Learning Methods for Detecting False Data Injection Attacks in Power Systems
Author(s): Ali Sayghe, Y. Hu, I. Zografopoulos, X. Liu, R.G. Dutta, Y. Jin, C. Konstantinou
Journal: IET Smart Grid

Conclusion

Ali sayghe’s journey reflects a deep commitment to advancing control systems and cyber-physical security for power systems through both academic excellence and applied research. his influence spans from the classroom, where he mentors the next generation of engineers, to the global research community, where his contributions guide best practices for safeguarding energy infrastructure. by fostering newcomer socialization in research and promoting innovative solutions, his future work is set to further strengthen the safety, reliability, and adaptability of industrial power systems.

Mr. Ahmad Faraz Ishaq – Crop Yield Modeling – Best Researcher Award 

Mr. Ahmad Faraz Ishaq - Crop Yield Modeling - Best Researcher Award 

Beihang University - Pakistan

Author Profile 

ORCID 

🎓 Early academic pursuits

Ahmad Faraz Ishaq laid the foundation for his academic journey with a strong passion for agronomy and its technological applications. he pursued an m.sc. (hons) in agronomy from the university of agriculture faisalabad, where he delved into crop growth optimization and sustainable agricultural practices. his early research focused on improving mungbean yield through optimized sowing dates and planting patterns, reflecting his keen interest in enhancing crop productivity. his academic excellence paved the way for his future endeavors in integrating geospatial technologies with agricultural research.

🌍 Professional endeavors

Ahmad Ishaq has built a distinguished career that seamlessly bridges agriculture and space technology. currently serving as a manager at suparco, he specializes in geo-spatial technologies for crop yield modeling, area estimation, and damage assessment caused by natural hazards. his expertise extends to monitoring crop health using ndvi and ndwi indices, ensuring precise and data-driven agricultural decisions. he also plays a crucial role in supporting agro-industries, particularly in sugarcane harvest monitoring. his professional journey reflects a deep commitment to leveraging space-based technologies for the advancement of precision agriculture.

🌿 Contributions and research focus

Ahmad has made groundbreaking contributions to agricultural research by integrating crop growth models, radiative transfer models, and machine learning to enhance crop trait estimation Crop Yield Modeling and yield prediction. his notable publications include "a synergistic framework for coupling crop growth, radiative transfer, and machine learning to estimate wheat crop traits in pakistan" and "a systematic review of radiative transfer models for crop yield prediction and crop traits." his research has introduced innovative methodologies that combine satellite data with machine learning to develop robust models for wheat yield prediction, significantly improving agricultural forecasting and resource management.

🏆 Accolades and recognition

Ahmad's contributions to agricultural research and precision farming have been widely acknowledged. his work has been published in prestigious journals like remote sensing, where he has co-authored influential studies on geospatial technologies for crop modeling. he has also contributed to practical agricultural knowledge, co-authoring articles in the international journal of Crop Yield Modeling agriculture and biology and publishing insights on wind break management in daily dawn. his ability to translate complex research into real-world applications has earned him recognition in both academic and professional circles.

👨‍💻 Impact and influence

Ahmad Ishaq's research has significantly influenced the field of precision agriculture, particularly in pakistan. his expertise in integrating space-based technologies with agronomy has provided farmers and policymakers with actionable insights for crop management. by employing machine learning and remote sensing data, he has enabled more accurate predictions of crop health Crop Yield Modeling and yield, reducing risks associated with climate change and natural disasters. his contributions have enhanced decision-making processes in the agricultural sector, making farming more efficient and sustainable.

🛠️ Legacy and future contributions

As he pursues a ph.d. in space technology and its application at beihang university, beijing, ahmad continues to push the boundaries of precision agriculture. his research aims to further integrate space-based innovations with agricultural practices, ensuring more sustainable and data-driven farming solutions. his legacy lies in his dedication to merging agronomy with cutting-edge technology, setting a precedent for future researchers and professionals in the field. through his continued efforts, he is shaping a future where precision agriculture plays a central role in global food security and environmental sustainability.

Notable Publications 

  • Title: Geospatial Robust Wheat Yield Prediction Using Machine Learning and Integrated Crop Growth Model and Time-Series Satellite Data
    Author(s): Rana Ahmad Faraz Ishaq, Guanhua Zhou, Guifei Jing, Syed Roshaan Ali Shah, Aamir Ali, Muhammad Imran, Hongzhi Jiang, Obaid-ur-Rehman
    Journal: Remote Sensing

  • Title: Assessing Above-Ground Biomass Dynamics and Carbon Sequestration Potential Using Machine Learning and Spaceborne LiDAR in Hilly Conifer Forests of Mansehra District, Pakistan
    Author(s): Muhammad Imran, Guanhua Zhou, Guifei Jing, Chongbin Xu, Yumin Tan, Rana Ahmad Faraz Ishaq, Muhammad Kamran Lodhi, Maimoona Yasinzai, Ubaid Akbar, Anwar Ali
    Journal: Forests

  • Title: A Systematic Review of Radiative Transfer Models for Crop Yield Prediction and Crop Traits Retrieval
    Author(s): Rana Ahmad Faraz Ishaq, Guanhua Zhou, Tian Chen, Yumin Tan, Guifei Jing, Hongzhi Jiang, Obaid-ur-Rehman
    Journal: Remote Sensing

  • Title: Contextual Band Addition and Multi-Look Inferencing to Improve Semantic Segmentation Model Performance on Satellite Images
    Author(s): Syed Roshaan Ali Shah, Obaid-Ur-Rehman, Yasir Shabbir, Rana Ahmad Faraz Ishaq
    Journal: Journal of Spatial Science

  • Title: Trans-Boundary Spatio-Temporal Analysis of Sentinel 5P Tropospheric Nitrogen Dioxide and Total Carbon Monoxide Columns Over Punjab and Haryana Regions with COVID-19 Lockdown Impact
    Author(s): Yasir Shabbir, Guanhua Zhou, Obaid-ur-Rehman, Syed Roshaan Ali Shah, Rana Ahmad Faraz Ishaq
    Journal: Environmental Monitoring and Assessment

Mr. Petar Donev – Remote Sensing – Best Researcher Award

Mr. Petar Donev - Remote Sensing - Best Researcher Award

Hohai University - China 

Author Profile 

SCOPUS

ORCID

🌟 Early academic pursuits

Petar Donev's academic journey began with a deep interest in geodesy and geosciences. he earned his bachelor’s degree in geodesy from ss. “cyril and methodius” university in skopje, north macedonia, completing a thesis on analyzing lidar data using open-source gis software. his dedication to understanding cartographic systems and digital geospatial data laid the groundwork for his future contributions. furthering his academic growth, he pursued a master’s degree in cartography and gis at hohai university, china, where his research focused on estimating and mapping forest above-ground biomass using lidar data and multispectral satellite imagery. his educational foundation culminated in his ongoing doctoral studies at hohai university, where he specializes in mapping forest agb using multisource data in mountainous regions.

📚 Professional endeavors

Petar began his career in geodesy as a surveying technician, contributing to land and building surveys. later, as a geodetic engineer at the agency for real estate and cadaster in north macedonia, he worked on creating digital cadastral maps using advanced software. his teaching skills were honed at sggs “zdravko cvetkovski” high school, where he imparted knowledge on geoscience. his academic journey also includes a pedagogical certification from ss. “cyril and methodius” university, reflecting his commitment to both geodesy and education.

🌍 Contributions and research focus

petar’s research primarily revolves around mapping forest above-ground biomass using innovative technologies like lidar and multispectral satellite imagery. his Remote Sensing doctoral work explores agb mapping in mountainous regions, reflecting his focus on sustainable land management and environmental conservation. his expertise extends to leveraging gis tools for hydrology and forest dynamics, bridging the gap between geospatial technology and ecological insights.

🏆 Accolades and recognition

petar's academic and professional journey is marked by his achievements in geodesy and gis. earning a master’s degree and progressing to a doctoral candidate at Remote Sensing prestigious institutions like hohai university highlights his dedication and excellence. his successful completion of a mini-mba program from ibmi, berlin, underscores his multidisciplinary approach and leadership aspirations.

🌟 Impact and influence

petar has contributed significantly to advancing geospatial research, particularly in the areas of agb mapping and digital cadastral systems. his work not only aids in sustainable forestry and land management but also demonstrates the practical applications of lidar and gis technologies in real-world scenarios. his teaching Remote Sensing experience further amplifies his influence, inspiring future professionals in geoscience and geodesy.

🔗 Legacy and future contributions

with a focus on integrating multisource data and advanced technologies, petar aims to refine methodologies for agb estimation and digital mapping. his research Remote Sensing promises to provide vital insights for environmental planning and disaster mitigation in mountainous and forested regions. as he continues to innovate, petar’s legacy will inspire the geospatial community to harness technology for sustainable development.

Notable Publications 

  1. Title: Cross-modal fusion approach with multispectral, LiDAR, and SAR data for forest canopy height mapping in mountainous region
    Authors: Petar Donev, Hong Wang, Shuhong Qin, Xiuneng Li, Meng Zhang, Sisi Liu, Xin Wang
    Journal: Physics and Chemistry of the Earth, Parts A/B/C
  2. Title: Enhancing Landsat image-based aboveground biomass estimation of black locust with scale bias-corrected LiDAR AGB map and stratified sampling
    Authors: Shuhong Qin, Hong Wang, Xiuneng Li, Jay Gao, Jiaxin Jin, Yongtao Li, Jinbo Lu, Pengyu Meng, Jing Sun, Zhenglin Song, et al.
    Journal: Geo-spatial Information Science
  3. Title: Estimating the Forest Above-Ground Biomass Based on Extracted LiDAR metrics and Predicted Diameter at Breast Height
    Authors: Petar Donev, Hong Wang, Shuhong Qin, Pengyu Meng, Jinbo Lu
    Journal: Journal of Geodesy and Geoinformation Science