Huan Zhao | Machine Learning | Best Researcher Award

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Assoc. Prof. Dr . Huan Zhao | Machine Learning | Best Researcher Award

Associate Professor, School of Aeronautics, Northwestern Polytechnical University, China

Huan Zhao is an associate professor at the School of Aeronautics, Northwestern Polytechnical University (NPU), China. He specializes in aerodynamics, multidisciplinary design optimization, uncertainty quantification, and machine learning, focusing on CFD simulation, AI-based global optimization, and surrogate modeling. He is also the executive deputy director of the Institute of Digital Intelligence for Flight Mechanics and Aerodynamic Design (IDIFMAD). Zhao has made significant contributions to the fields of aerodynamic shape optimization, high-dimensional global optimization, and uncertainty-based robust design. He holds several patents and has authored many high-impact publications. 🌐✈️

Publication Profile

Education

Huan Zhao completed his Ph.D. in Fluid Dynamics at Northwestern Polytechnical University (NPU) in 2020, following a B.Eng. in Aircraft Design and Engineering from the same university in 2014. 📚🎓

Experience

Zhao served as a tenure-track assistant professor at Sun Yat-sen University (SYSU) before joining NPU as a tenure-track associate professor in 2023. He has directed and participated in numerous research projects focusing on aerodynamic design optimization, high-speed rotor airfoil design, and surrogate-assisted design techniques. He is a principal investigator (PI) for multiple projects funded by the National Natural Science Foundation of China (NSFC). 👨‍🏫🔬

Awards and Honors

Huan Zhao has received several awards and honors, including recognition as part of the “Hundred Talents Plan” Young Academic Backbone at SYSU and multiple patents for his innovative contributions to aerodynamic design. 🏆🎖️

Research Focus

Zhao’s research interests lie in aerodynamics, including multi-fidelity polynomial chaos-Kriging models, aerodynamic shape optimization, and uncertainty quantification. His work has contributed significantly to the design and optimization of high-lift airfoils, laminar flow airfoils, and robust design methods under uncertainty. His expertise also includes machine learning, AI-based global optimization, and the application of surrogate models in complex design scenarios. 🔍🧑‍💻

Conclusion

Huan Zhao’s innovative work has had a profound impact on the field of aerodynamics and optimization. His research has not only advanced the understanding of aerodynamic design but has also led to practical improvements in the development of high-performance aircraft and related technologies. He continues to drive forward cutting-edge research in aerodynamics and multidisciplinary design optimization. 🚀🌍

Publications

An efficient adaptive forward–backward selection method for sparse polynomial chaos expansion, Computer Methods in Applied Mechanics and Engineering, 2019.

Review of robust aerodynamic design optimization for air vehicles, Archives of Computational Methods in Engineering, 2019.

Effective robust design of high lift NLF airfoil under multi-parameter uncertainty, Aerospace Science and Technology, 2017.

Adaptive multi-fidelity sparse polynomial chaos-Kriging metamodeling for global approximation of aerodynamic data, Structural and Multidisciplinary Optimization, 2021.

Uncertainty-based design optimization of NLF airfoil for high altitude long endurance unmanned air vehicles, Engineering Computations, 2019.

 Efficient aerodynamic analysis and optimization under uncertainty using multi-fidelity polynomial chaos-Kriging surrogate model, Computers & Fluids, 2022.

Research on efficient robust aerodynamic design optimization method of high-speed and high-lift NLF airfoil, Acta Aeronautica et Astronautica Sinica, 2021.

Research on Novel High-Dimensional Surrogate Model-Based Aerodynamic Shape Design Optimization, Acta Aeronautica et Astronautica Sinica, 2022.

Research on novel multi-fidelity surrogate model assisted many-objective global optimization method, Acta Aeronautica et Astronautica Sinica, 2022.

Adaptive multi-fidelity polynomial chaos-Kriging model-based efficient aerodynamic design optimization method, Chinese Journal of Theoretical and Applied Mechanics, 2023.

 

sajjad qureshi | Artificial Intelligence Award | Computer Vision Contribution Award

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Dr. sajjad qureshi | artificial intelligence award | Computer Vision Contribution Award

deputy Director (IT), multan electric power company, Pakistan

📘 Dr. Sajjad Hussain Qureshi is a seasoned professional with over 21 years of experience in Information Technology. Currently serving as the Deputy Director (IT) at Multan Electric Power Company for the past two decades, Dr. Qureshi has established expertise in system analysis and design, machine learning, cybersecurity, IT auditing, and project management. His multidisciplinary educational background, including a Ph.D. in Computer Science, Ph.D. in Agriculture, and an MBA in Human Resource Management, has enabled him to excel in IT-based quality assurance, data analysis, and human resource management. He is passionate about utilizing cutting-edge technologies to create impactful solutions in diverse domains.

Publication Profile

ORCID

Education

🎓 Dr. Qureshi holds a Ph.D. in Computer Science, a Ph.D. in Agriculture, and an MBA in Human Resource Management. His diverse academic achievements reflect his commitment to integrating IT with interdisciplinary knowledge for impactful research and practical solutions.

Experience

💼 Dr. Qureshi has an extensive career spanning over 21 years in the IT field. For the last 20 years, he has been a cornerstone of the Multan Electric Power Company, where he serves as the Deputy Director (IT). His experience covers IT infrastructure development, LAN networks, client/server environments, cybersecurity, and customer billing systems. He also excels in IT-based quality assurance and control, project management, and data management.

Research Interests

🔍 Dr. Qureshi’s research interests lie at the intersection of machine learning, deep learning, cybersecurity, data management, and agriculture technology. He is particularly interested in applying advanced computational techniques to solve real-world problems, such as disease detection in crops and classification of linguistic data.

Awards

🏆 Dr. Qureshi has been recognized for his contributions to IT and interdisciplinary research, achieving notable academic and professional milestones. His work continues to inspire innovation and collaboration across diverse fields.

Publications

Classification of English Words into Grammatical Notations Using Deep Learning Technique (2024)
Imran, M., Qureshi, S. H., Qureshi, A. H., & Almusharraf, N.
Published in Information, 15(12), 801.
DOI: 10.3390/info15120801

Rational Study Of The Use Of Computer-Aided Softwares By The Composers (2024)
Qureshi, S. H., Javaid, S., & Javaid, M. A.
Published in Pakistan Journal of Society, Education and Language, 10(2), 213–219.

Comparison of Conventional and Computer-Based Detection of Severity Scales of Stalk Rot Disease in Maize (2024)
Qureshi, S.H., Khan, D.M., Razzaq, A., Baig, M.M., & Bukhari, S.Z.A.
Published in SABRAO Journal of Breeding and Genetics, 56(1), 292–301.
DOI: 10.54910/sabrao2024.56.1.26

Intelligent Resistant Source Detection Against Stalk Rot Disease of Maize Using Deep Learning Technique (2023)
Qureshi, S.H., Khan, D.M., & Bukhari, S.Z.
Published in SABRAO Journal of Breeding and Genetics, 55(6), 1972–1983.

Robin Augustine | Artificial Intelligence | Excellence in Research

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Assoc. Prof. Dr. Robin Augustine | Artificial Intelligence | Excellence in Research

Associate Professor, Uppsala University, Sweden

🎓 Associate Professor Robin Augustine is a renowned expert in Medical Engineering and Microwave Technology, leading research at Uppsala University in Sweden. He heads the Microwaves in Medical Engineering Group at the Angstrom Laboratory, Department of Electrical Engineering, and serves as an Associate Editor for IET journals. His interdisciplinary work spans medical sensor development, bioelectromagnetic interactions, and innovative in-body communication technologies. Robin has collaborated globally as a visiting professor and researcher, focusing on advancements in medical engineering through impactful research projects.

Publication Profile

Scopus

Education

📚 Dr. Robin Augustine earned his Ph.D. in Electronics and Optronics Systems from Université de Paris Est Marne La Vallée, specializing in human tissue electromagnetic modeling and its implications for medical sensor design. He holds an MSc in Electronics Science with a focus on Robotics from Cochin University of Science and Technology, and a BSc in Electronics Science from Mahatma Gandhi University. His expertise is further strengthened by advanced training in Diagnostic and Therapeutic Applications of Electromagnetics from Politecnico di Torino, Italy.

Experience

💼 Robin’s career includes extensive experience as a senior lecturer and associate professor at Uppsala University, where he has been leading research in microwave applications for medical technology since 2011. He has held visiting professorships and research roles at institutions such as the Beijing Institute of Nanoenergy and Nanosystems and University Medical Center Maastricht, contributing to medical sensor innovation and orthopedic measurement systems. Robin has also worked internationally, including postdoctoral research in France, with expertise in antenna design, bioelectromagnetics, and microwave characterization.

Research Focus

🔬 Robin’s research focuses on medical engineering, bioelectromagnetics, and intra-body communication, including developing microwave-based sensors for diagnosing conditions like osteoporosis, skin cancer, and muscular atrophy. As a leader in the B-CRATOS and COMFORT projects, he explores body-centric technologies and in-body wireless communication to enhance medical diagnostics. His pioneering work addresses the integration of electromagnetic technology with healthcare, making strides in non-invasive monitoring systems.

Awards and Honours

🏆 Dr. Augustine’s impactful research has attracted numerous grants and awards, including significant EU funding for projects like PERSIMMON and DIAMPS. He has secured research funding from bodies such as the Swedish Research Council, Vinnova, and the Foundation for Strategic Research, supporting his innovative work on body communication systems and medical diagnostics. His research has earned recognition through the Swedish Excellence Grant for Young Researchers and multiple grants for advancing medical engineering solutions.

Publication Top Notes

Biphasic lithium iron oxide nanocomposites for enhancement in electromagnetic interference shielding properties

Rotation insensitive implantable wireless power transfer system for medical devices using metamaterial-polarization converter

Improving burn diagnosis in medical image retrieval from grafting burn samples using B-coefficients and the CLAHE algorithm

 

Dongbeom Kim | Artificial Intelligence | Best Researcher Award

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Mr. Dongbeom Kim | Artificial Intelligence | Best Researcher Award

Master’s Student, University of Seoul, South Korea

Dongbeom Kim is a dedicated Master’s student at the University of Seoul, specializing in Geoinformatics under the mentorship of Professor Chulmin Jun. With a robust academic background in Geography and a passion for innovative research, Dongbeom is actively engaged in developing smart systems for urban planning and vehicle safety. His work spans advanced studies in fire evacuation simulations, the application of artificial intelligence in urban growth modeling, and the development of safe driving systems for two-wheeled vehicles. 📊🛵

Publication Profile

Strengths for the Award:

  1. Academic Background: Dongbeom Kim has a solid educational foundation in Geography and Geoinformatics, with high GPAs in both his undergraduate and current Master’s studies. His ongoing education in Geoinformatics at the University of Seoul under the guidance of a reputed advisor further strengthens his research credentials.
  2. Research Publications: He has authored several papers published in reputable SCIE/ESCI journals like Sensors and Applied Sciences, along with multiple domestic publications. His research spans various topics, including fire evacuation simulations, vehicle safety, and urban growth modeling, indicating a diverse research portfolio.
  3. Conferences and Presentations: Dongbeom Kim has actively presented his research at several international and national conferences, such as the 18th International Conference on Location Based Services in Belgium and the Korean Society for Geospatial Information Science. These experiences highlight his engagement with the academic community and his ability to communicate his research effectively.
  4. Patents and Innovation: He is a co-inventor on four patents related to vehicle safety and route generation, demonstrating innovation and practical application of his research.
  5. Research Projects: Participation in multiple research projects, including those focused on greenhouse gas emission reduction and environmental big data analysis, shows his capability to contribute to significant scientific endeavors.

Areas for Improvement:

  1. Research Leadership: While Dongbeom Kim has collaborated on numerous projects and publications, there is limited evidence of him taking on a leading role in these efforts. Demonstrating more leadership in research projects or publications could strengthen his profile.
  2. Diversity in Research Impact: Although his research covers a range of topics, the majority are closely related to vehicle safety and geospatial data analysis. Expanding his research to cover other areas of geoinformatics or interdisciplinary applications could enhance the breadth of his research impact.
  3. Published Impact Factor: As some of his research is still under review and the impact factors of the journals in which he has published are not mentioned, highlighting the impact factor or citation index of his published work could further substantiate his research quality.

 

Education

Dongbeom holds a Bachelor’s degree in Geography from Kongju National University (2015-2021), achieving a GPA of 3.9/4.5. He is currently pursuing a Master’s degree in Geoinformatics at the University of Seoul, where he has achieved an impressive GPA of 4.33/4.5. 🎓🌍

Experience

Dongbeom’s experience includes multiple research projects, focusing on geospatial information science, urban growth modeling, and traffic safety. He has contributed to several conferences and published numerous peer-reviewed articles in international journals. His practical skills are reinforced by his active involvement in projects such as the development of a good driving evaluation system for two-wheeled vehicles and environmental big data analysis. 🌐📝

Research Focus

Dongbeom’s research primarily revolves around geoinformatics, fire evacuation simulations, urban growth modeling, and traffic safety. He is particularly interested in utilizing sensor-based approaches and artificial intelligence techniques to address urban challenges and enhance public safety. 🚒🌆

Awards and Honors

Dongbeom has presented his work at prestigious international and domestic conferences and has collaborated on innovative projects that have received national attention. He is also recognized for his contributions to patents related to traffic safety and environmental management. 🏆🔬

Publication Top Notes

Under Review: Dongbeom Kim, Hyemin Kim, Yuhan Han, Chulmin Jun, “Fire Evacuation Simulation with Agent-Based Fire Recognition Propagation” (Physica Scripta, 2024)

Dongbeom Kim, Hyemin Kim, Suyun Lee, Qyoung Lee, Minwoo Lee, Jooyoung Lee, Chulmin Jun, “Design and Implementation of a Two-Wheeled Vehicle Safe Driving Evaluation System” (Sensors, 2024) – Cited by 2 articles

Dongbeom Kim, Hyemin Kim, Chulmin Jun, “The Detection of Aggressive Driving Patterns in Two-Wheeled Vehicles Using Sensor-Based Approaches” (Applied Sciences, 2023) – Cited by 3 articles

Minjun Kim, Dongbeom Kim, Daeyoung Jin, Geunhan Kim, “Application of Explainable Artificial Intelligence (XAI) in Urban Growth Modeling: A Case Study of Seoul Metropolitan Area, Korea” (Land, 2023) – Cited by 5 articles

Suyun Lee, Dongbeom Kim, Chulmin Jun, “Calculation of Dangerous Driving Index for Two-Wheeled Vehicles Using the Analytic Hierarchy Process” (Applied Sciences, 2023) – Cited by 1 article

Minjun Kim, Dongbeom Kim, Geunhan Kim, “Examining the Relationship between Land Use/Land Cover (LULC) and Land Surface Temperature (LST) Using Explainable Artificial Intelligence (XAI) Models: A Case Study of Seoul, South Korea” (International Journal of Environmental Research and Public Health, 2022) – Cited by 4 articles 📖🔗

Conclusion:

Dongbeom Kim appears to be a promising candidate for the “Best Researcher Award” due to his solid academic background, active research publication record, involvement in innovative patents, and participation in impactful research projects. To further strengthen his candidacy, he could focus on assuming leadership roles in his research, diversifying his research impact, and emphasizing the citation metrics of his work. Overall, his contributions to the field of geoinformatics and vehicle safety suggest he is a strong contender for this award.

Samana Batool | Artificial Intelligence | Best Researcher Award

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Ms. Samana Batool | Artificial Intelligence | Best Researcher Award

PhD scholar, Capital University of Science and Technology, Pakistan

📝 Samana Batool is a dedicated PhD student in Electrical Engineering, specializing in AI applications in medical imaging. She recently completed her final defense at the Capital University of Science and Technology, Islamabad, Pakistan. With a strong foundation in AI-driven healthcare solutions, Samana has made significant contributions to the field of medical imaging, particularly in echocardiogram data analysis. Her work has been published in reputable journals, and she serves as a reviewer for high-impact publications, playing a key role in advancing research standards.

Publication Profile

Google scholar

Strengths for the Award:

Strong Academic Background: Samana Batool holds a PhD in Electrical Engineering with a specialization in AI applications in medical imaging. She has completed advanced research, particularly in echocardiogram data analysis, which is a niche area within medical AI.

Innovative Research: Her research projects, such as the integration of multi-modality techniques (ECG and Echocardiography) and the quantification of LV structure using deep learning, demonstrate innovation and the potential for significant impact on clinical practices.

Publications and Editorial Role: She has published papers in reputable journals (Diagnostics, MDPI; Physica Medica, Elsevier) and serves as a reviewer for high-impact journals, indicating recognition by the scientific community.

Collaboration with Medical Institutions: Her collaboration with the Cardiology Department at Shifa International Hospital, Islamabad, further supports the practical application of her research in clinical settings.

Areas for Improvement:

Limited Citation Index: The citation count of 4 is relatively low, which may reflect a need for more visibility and impact in the academic community.

Lack of Industry Engagement: No consultancy or industry-sponsored projects are mentioned, which could demonstrate a lack of practical industry application or impact.

Absence of Patents and Books: No patents or books published suggests a focus on journal publications rather than other forms of dissemination and intellectual property, which could be considered a limitation in terms of innovation and knowledge transfer.

Professional Memberships and Recognition: The absence of professional memberships and awards or recognitions may limit her visibility and recognition in her field.

 

Education

🎓 Samana holds a PhD in Electrical Engineering, specializing in AI applications in medical imaging. She also earned a Master’s in Computer Engineering and a Bachelor’s in Electrical Engineering. Her academic journey reflects a strong commitment to integrating advanced AI techniques with medical imaging to improve diagnostic tools and healthcare outcomes.

Experience

💼 Samana has a diverse professional background, serving as a Research Associate at Digital Pakistan Lab (NUST), where she focused on AI-driven healthcare solutions. She also worked as an Assistant Manager (Electronics) at the Pakistan Space and Upper Research Commission (SUPARCO). Her roles have centered on leveraging AI for innovative medical applications, particularly in cardiac imaging and disaster management.

Research Focus

🔍 Samana’s research revolves around the applications of machine learning and deep learning in medical image analysis, particularly in echocardiogram data. She has developed methodologies for quantifying left ventricular (LV) structure and function, enhancing the precision of cardiac diagnostics. Her ongoing projects also explore integrating multimodality techniques, such as ECG and echocardiography, to advance AI-based solutions in healthcare.

Awards and Honors

🏆 Samana has been recognized for her contributions to AI-driven medical imaging, particularly for her innovative research on echocardiogram data analysis. Her published work in reputed journals has gained recognition, contributing to advancements in LV quantification and AI-based healthcare solutions.

Publication Top Notes

“Ejection Fraction Estimation from Echocardiograms Using Optimal Left Ventricle Feature Extraction Based on Clinical Methods” – Diagnostics (MDPI), 2023

“Quantification of LV Structure and Function using Deep Learning Techniques” – Physica Medica (Elsevier), 2022

Conclusion:

Samana Batool demonstrates strong potential for the “Best Researcher Award” due to her innovative research in AI applications in medical imaging and her active involvement in academic publishing. However, to enhance her competitiveness, she could work on increasing her citation index, engaging more with industry projects, and contributing to professional organizations. Her existing strengths in academic research and collaboration are notable, but diversifying her achievements could further strengthen her nomination for this award.

Rahma Mani | Artificial Intelligence | Women Researcher Award

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Ms. Rahma Mani | Artificial Intelligence | Women Researcher Award

PhD student, Escuela Técnica Superior de Ingeniería Informática, ETSII, Spain

Rahma Mani is a dedicated Ph.D. candidate in Electrical Engineering and Computer Science at the University of Seville, Spain, with a deep passion for wireless sensor networks, machine learning, and artificial intelligence. With a strong foundation in electrical engineering from the National Engineering School of Monastir, Tunisia, she has demonstrated her expertise through various academic and professional roles. Rahma has contributed to significant research projects and has a keen interest in innovative technologies.

Publication Profile

 

Strengths for the Award:

  1. Academic Excellence: Rahma is currently pursuing a Ph.D. in Electrical Engineering and Computer Science, focusing on cutting-edge fields such as wireless sensor networks, machine learning, and artificial intelligence. Her educational background is robust and well-aligned with emerging technological fields.
  2. Research Contributions: Rahma has multiple publications in reputable journals and conferences, including a submission to the prestigious Pervasive and Mobile Computing Journal by Elsevier. Her research in wireless sensor networks demonstrates innovation and contributes significantly to the field.
  3. Global Perspective: Rahma’s North African upbringing combined with her international academic and professional experiences in Spain, Italy, France, and Tunisia give her a unique global perspective. This diversity enhances her ability to approach problems from different angles, which is a valuable asset in research.
  4. Technical Skills: She possesses a wide range of digital and programming skills, including proficiency in languages like Java, C++, and MATLAB, as well as experience with technologies such as Vivado and Arduino. These skills are critical for her research and development work.
  5. Leadership and Innovation: Rahma demonstrated leadership in her role as the Electrical Committee leader in the ENIM TEAM, where she led the development of an electric car for an international competition. Her involvement in volunteer activities also highlights her leadership abilities and commitment to social causes.
  6. Language Proficiency: Fluent in English, Arabic, and French, with basic Spanish, Rahma’s multilingual capabilities are a significant asset in collaborative international research.

Areas for Improvement:

  1. Broader Research Exposure: While Rahma has a strong publication record, expanding her research impact by collaborating on interdisciplinary projects or participating in more international conferences could further enhance her profile.
  2. Advanced Certifications: Although Rahma has quality management certifications, pursuing advanced certifications related to her research areas (e.g., specialized AI or wireless communication certifications) could strengthen her expertise.
  3. Industry Collaboration: Increasing her engagement with industry partners, beyond internships, through joint research projects or consulting roles could provide practical applications for her research, enhancing its relevance and impact.

 

🎓 Education:

Rahma is currently pursuing her Ph.D. in Electrical Engineering and Computer Science at the University of Seville, Spain, specializing in wireless sensor networks, machine learning, and artificial intelligence. She earned her Electrical Engineering Diploma from the National Engineering School of Monastir, Tunisia, where she also led a team in designing and developing an electric car for an international competition. Rahma began her academic journey with preparatory engineering studies at the Preparatory Institute for Engineering Studies of Monastir, Tunisia.

💼 Experience:

Rahma has gained extensive experience as an adjunct professor at the Higher Institute of Applied Sciences and Technology of Mahdia, Tunisia, where she taught courses on digital signal processing, converters, and electrical machines. She also worked as a Junior Full Stack Engineer at HRDatabank Tunisia (WILL Group, Japan), contributing to the development of HR web applications. Additionally, Rahma has completed internships at Smart Sensors Systems (3S) in Nancy, France, and the Tunisian Electricity and Gas Company in Sousse, Tunisia.

🔬 Research Focus:

Rahma’s research focuses on wireless sensor networks, particularly in the areas of localization algorithms, edge computing, and FPGA-enhanced systems. She is passionate about applying machine learning and artificial intelligence techniques to improve the efficiency and reliability of sensor networks, especially in large-scale and industrial applications.

🏆 Awards and Honors:

Rahma received a merit-based fellowship to pursue her Ph.D. internship in Italy and Spain, recognizing her outstanding academic and research achievements.

📚 Publication Top Notes:

Localizing Unknown Nodes with an FPGA-Enhanced Edge Computing UAV in Wireless Sensor Networks: Implementation and Evaluation (2024)

Improved 3D localization algorithm for large-scale wireless sensor networks (2023).

Improved Distance vector-based Kalman Filter localization algorithm for wireless sensor network (2023) .

CRT-LoRa: An efficient and reliable MAC scheme for real-time industrial applications (2023).

Improved Least-Square DV-Hop Algorithm for Localization in Large Scale Wireless Sensor Network (2022) .

 

Conclusion:

Rahma Mani is a well-qualified candidate for the Research for Women Researcher Award. Her solid academic background, impressive research contributions, technical expertise, and leadership qualities make her a strong contender. With continued focus on expanding her research impact and industry collaborations, she is likely to make significant contributions to the field of Electrical Engineering and Computer Science, particularly in the areas of wireless sensor networks and AI. Her application for the award would be well-justified, showcasing both her achievements and potential for future advancements.

 

 

Hesham A. Sakr | Artificial Intelligence | Best researcher award

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Assist Prof Dr. Hesham A. Sakr | Artificial Intelligence | Best researcher award

Assistant professor, Assistant professor -Nile higher institute of engineering and technology -Mansoura -Egypt

📡 Hesham Ali Sakr is an Assistant Professor and Researcher specializing in Communication Networks and Cybersecurity. He earned his Ph.D. in Electrical, Electronics, and Communications Engineering from Mansoura University, Egypt. Dr. Sakr’s research focuses on optimizing wireless technologies for multimedia services, VoIP systems, and LTE-A networks. His contributions to the field are recognized through multiple publications in prestigious journals. He is actively involved in advancing the state-of-the-art in 5G and beyond communication technologies.

Profile

Google Scholar

 

Education

🎓 Ph.D. in Electrical, Electronics, and Communications Engineering
Mansoura University, Egypt (June 2016 – April 2020)
Thesis: Development of Accessing Multimedia Services over Wireless Technologies
GPA: 3.55/4

🎓 M.Sc. in Electrical, Electronics, and Communications Engineering
Mansoura University, Egypt (June 2010 – September 2014)
Thesis: Development of VoIP Systems using MPLS
GPA: 3.6/4

🎓 B.Sc. in Networks and Communications Engineering
Higher Technological Institute of Engineering, 10th of Ramadan, Egypt (September 2004 – August 2009)
Excellent with Honor Degree (84.9%)
Graduation Project Grade: Excellent

Experience

Specializing in Communication Networks and Cybersecurity, Dr. Sakr has significant academic and research experience. His work primarily focuses on enhancing wireless communication technologies, particularly in the realms of 5G and multimedia services. He has been affiliated with Mansoura University, contributing to various research projects and publications.

Research Interests

Dr. Sakr’s research interests encompass Communication Networks, Cybersecurity, and the development of efficient multimedia services over wireless technologies. His work includes performance evaluation of HARQ mechanisms, IPv6 multimedia management, and power-efficient mechanisms for LTE-A networks. He is particularly focused on optimizing handover management in LTE-A networks and evaluating VoIP versus VoMPLS performance.

Awards

Dr. Hesham Ali Sakr has been recognized for his outstanding contributions to the field of Communication Networks and Cybersecurity. His research achievements and academic excellence have earned him a commendable reputation among peers and colleagues in the industry.

Publications

📚 H.A. Sakr, and M.A. Mohamed, “Performance Evaluation Using Smart: HARQ Versus HARQ Mechanisms Beyond 5G Networks,” Wireless. Pers. Communication (Springer), June 2019. Cited by 26 articles

📚 Abeer Twakol Khalil, A. I. Abdel-Fatah and Hesham Ali Sakr, “Rapidly IPv6 multimedia management schemes based LTE-A wireless networks,” International Journal of Electrical and Computer Engineering (IJECE), vol. 9, no. 4, 2018. Cited by 32 articles

📚 H. A. Sakr, A. I. Abdel-Fatah, A. T. Khalil, “Performance Evaluation of Power Efficient Mechanisms on Multimedia over LTE-A Networks,” International Journal on Advanced Science, Engineering and Information Technology (IJASEIT), vol. 9, no. 4, 2019. Cited by 18 articles

📚 H.A. Sakr and M.A. Mohamed, “Handover Management Optimization over LTE-A Network using S1 and X2 handover,” Proc. of The Seventh International Conference on Advances in Computing, Electronics and Communication – ACEC 2018, 2018. Cited by 15 articles

📚 M. Abdel-Azim, M., Awad, M. M., & Sakr, H. A., “VoIP versus VoMPLS Performance Evaluation,” International Journal of Computer Science Issues (IJCSI), 11(1), 2014. Cited by 20 articles

Lourdes Swentek | Artificial Intelligence | Best Researcher Award

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Assist Prof Dr. Lourdes Swentek | Artificial Intelligence | Best Researcher Award

Academician/Research Scholar, UCI, United States

Dr. Lourdes Swentek is a highly accomplished trauma and critical care surgeon with extensive experience in surgical research and education. She completed her fellowship in Critical Care at the University of California, Irvine, and her residency in Surgery at Loma Linda University Health. Dr. Swentek has been recognized for her outstanding contributions to trauma and acute care surgery, earning numerous awards and accolades throughout her career. Her research interests focus on islet transplantation, oxidative stress in pancreatitis, and innovative surgical techniques.

Profile

Scopus

 

Education

🎓 Dr. Lourdes Swentek completed her Critical Care fellowship at the University of California, Irvine, and her Surgical Residency at Loma Linda University Health. She also served as a Research Resident in the Department of Surgery at the University of California, Irvine, where she focused on islet transplantation.

Experience

🔬 Dr. Lourdes Swentek’s professional journey includes a fellowship in Critical Care at the University of California, Irvine, and a surgical residency at Loma Linda University Health. She has significant research experience in islet transplantation and surgical innovation, having contributed to several impactful research projects and publications.

Research Interests

🧪 Dr. Lourdes Swentek’s research interests encompass islet transplantation, oxidative stress in pancreatitis, and the development of novel surgical techniques. Her work has contributed to advancing knowledge and improving practices in these areas, making a notable impact on the field of trauma and critical care surgery.

Awards

🏆 Dr. Lourdes Swentek has received numerous awards, including the East Oriens Award for her career in Trauma and Acute Care Surgery in 2018, the Highest Resident Absite Score at Loma Linda University Health in 2017, and the UCI School of Medicine Achievement Award for Clinical Science Lecturer in 2022. These accolades reflect her dedication and excellence in her field.

Publications

The Addition of a Nurse Practitioner to an Inpatient Surgical Team Results in Improved Utilization of Resources

Medium and Long-term Outcomes after Pneumatic Dilation or Laparoscopic Heller Myotomy for Achalasia: A Meta-analysis

Presentation, Diagnosis, and Treatment of Oesophageal Motility Disorders

Role of Oxidative Stress in the Pathogenesis of Pancreatitis: Effect of Antioxidant Therapy

Total Pancreatectomy and Islet Auto Transplantation for Chronic Pancreatitis

 

Xiaohui Huang | Artificial Intelligence| Best Researcher Award

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Assoc Prof Dr. Xiaohui Huang | Artificial Intelligence| Best Researcher Award

Dean, East China jiaotong university, Japan

👨‍🏫 Dr. Xiaohui Huang is an Associate Professor at the School of Information Engineering, East China Jiaotong University. He earned his PhD from the School of Computer Science, Harbin Institute of Technology in November 2014. He has been a visiting scholar at the German Cancer Research Center and Nanyang Technological University. Dr. Huang has been leading several high-impact research projects funded by national and provincial bodies. He is an expert reviewer for various prestigious journals and a member of notable academic associations.

Profile

Scopus

 

Education

🎓 PhD in Computer Science, Harbin Institute of Technology, November 2014, German Cancer Research Center, December 2010 – October 2011, School of Computer Science and Engineering, Nanyang Technological University, November 2017 – November 2018

Experience

💼 Associate Professor, School of Information Engineering, East China Jiaotong University, January 2018 – Present
Lecturer, School of Information Engineering, East China Jiaotong University, December 2014 – December 2017
Visiting Scholar, Nuclear Medicine Research Group, German Cancer Research Center, December 2010 – October 2011
Software Engineer, Yichun Branch, China Telecom, August 2008 – February 2010

🔬 Research Interests

Deep Learning. Remote Image Analysis. Intelligent Transportation

🏆 Awards

Principal Investigator for various prestigious research projects including the National Natural Science Foundation of China and Jiangxi Province Natural Science Foundation.

 Publications

Multi-view dynamic graph convolution neural network for traffic flow prediction. Expert Systems With Applications, 2023 (SCI Zone 1 top)
Cited by: 15 articles

MAPredRNN: Multi-attention predictive RNN for traffic flow prediction by dynamic spatio-temporal data fusion. Applied Intelligence, 2023 (SCI Zone 2)
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