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

Gabriella d’Albenzio | Artificial Intelligence | Best Researcher Award

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Dr. Gabriella d’Albenzio | Artificial Intelligence | Best Researcher Award

Postdoc, Perk Lab Perk Lab Laboratory for Percutaneous Surgery, Canada

🎓 Gabriella d’Albenzio is a talented researcher with a focus on biomedical engineering and medical imaging. Currently pursuing a Ph.D. in Informatics at the University of Oslo, she has an impressive background in clinical engineering and biomedical engineering. Gabriella has worked on cutting-edge projects related to image-guided therapies and deep learning for medical applications, contributing significantly to her field through both research and development.

Profile

Scopus

 

Education

📚 Gabriella d’Albenzio holds a Ph.D. in Informatics from the University of Oslo (2021-2024). She completed her M.Sc. in Biomedical Engineering and B.Sc. in Clinical Engineering at Sapienza University of Rome, Italy, reflecting a solid foundation in both engineering and medical sciences.

Experience

💼 Gabriella d’Albenzio has extensive experience as a Scientific Software Developer at The Intervention Centre in Oslo, Norway, and as a Research Assistant at NTNU. She has also interned at the Rehabilitation Bioengineering Lab in Rome, contributing to various research projects involving advanced medical imaging and deep learning technologies.

Research Interests

🧠 Gabriella’s research interests are centered around enhancing surgical planning and medical imaging through deep learning and advanced computational techniques. Her work focuses on developing algorithms for medical image segmentation and predictive models for surgical outcomes, aiming to improve patient-specific treatment strategies.

Awards

🏅 Gabriella d’Albenzio has been recognized with the Globalink Research Internship by Mitacs, Canada, and a Grant Research Stay Abroad by The Research Council of Norway. These awards highlight her outstanding contributions to research and her commitment to advancing biomedical engineering.

Publications

Optimizing Surgical Plans for Parenchyma-Sparing Liver Resections through Contour-Guided Resection and Surface Approximation

Using NURBS for Virtual Resections in Liver Surgery Planning: A Comparative Usability Study

Patient-Specific Functional Liver Segments Based on Centerline Classification of the Hepatic and Portal Veins

ALive: Analytics for Computation and Visualization of Liver Resections

Laparoscopic Parenchyma-Sparing Liver Resection for Large (≥50 mm) Colorectal Metastases

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)
Cited by: 10 articles

SS-TMNet: Spatial–Spectral Transformer Network with Multi-Scale Convolution for Hyperspectral Image Classification. Remote Sensing, 2023 (SCI Zone 2, top)
Cited by: 8 articles

Multi-mode dynamic residual graph convolution network for traffic flow prediction. Information Sciences, 2022 (SCI Zone 1 top)
Cited by: 20 articles

A time-dependent attention convolutional LSTM method for traffic flow prediction.

Omar Soufi | Artificial Intelligence | Best Researcher Award

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Dr. Omar Soufi | Artificial Intelligence | Best Researcher Award

Doctorate, Mohammed V University of Rabat Mohammadia School of Engineering, Morocco

👨‍💼 Dr. Omar Soufi is a distinguished Computer Science Engineer specializing in Artificial Intelligence, Data Science, Remote Sensing, and Geographic Information Systems (GIS). With a robust background in data analysis and decision-support systems, Dr. Soufi excels in promoting organizational advancements and enhancing strategic performance through well-planned recommendations. His proactive and industrious approach ensures the achievement of objectives by leveraging data-driven insights.

Profile

ORCID

Education

🎓 Dr. Omar Soufi earned his Ph.D. in Computer Science Engineering with a focus on Artificial Intelligence from EMI Rabat in 2023, completing his doctoral research with the AMIPS/E3S team. He also holds a degree in Engineering from Polytechnique Grenoble, ENSIMAG, and EMI Rabat, specializing in Information Systems Engineering and Software Quality Engineering, respectively. His foundational studies include a Diploma and a Bachelor’s degree in Mechanical Engineering from ARM Merkèns.

Experience

💼 Dr. Soufi’s professional journey includes notable roles such as Project Manager in the IT Department, Team Leader at the Decision Support Center, Head of the BI & Decision Tools Department, Head of the Geomatics & Decision Tools Division, and AI Mission Manager. His expertise spans numerous projects in artificial intelligence and data science, including the development of national geospatial platforms, disaster risk management systems, and SaaS solutions for real estate asset management and financial risk analysis.

Research Interests

🔍 Dr. Soufi’s research focuses on applying deep learning techniques to satellite image super-resolution and spacecraft attitude control. His interests extend to big data architecture, distributed systems, and geospatial data analysis, aiming to enhance the accessibility and quality of high-resolution satellite imagery.

Awards

🏆 Dr. Soufi has been recognized for his contributions to artificial intelligence and remote sensing. He has received certifications in various professional and personal development areas, including PMO, coaching, and personal development, further solidifying his expertise and commitment to excellence in his field.

Publications

📄 Study of deep learning-based models for single image super-resolution. Soufi, O., Belouadha, F.Z. (2022). Revue d’Intelligence Artificielle, Vol. 36, No. 6, pp. 939-952. https://doi.org/10.18280/ria.360616

📄 FSRSI: New deep learning-based approach for super-resolution of multispectral satellite images. Soufi, O., Belouadha, F.Z. (2023). Ingénierie des Systèmes d’Information, Vol. 28, No. 1, pp. 113-132. https://doi.org/10.18280/isi.280112

📄 Deep learning technique for image satellite processing. O. Soufi and F.Z- Belouadha. Intell Methods Eng Sci, vol. 2, no. 1, pp. 27–34, Mar. 2023.

📄 Enhancing Accessibility to High-Resolution Satellite Imagery: A Novel Deep Learning-Based Super-Resolution Approach. O. Soufi and F.Z- Belouadha. Journal of Environmental Treatment Techniques, 11(2), 44-49, 2023.

📄 An intelligent deep learning approach to spacecraft attitude control: the case of satellites. O. Soufi and FZ.- Belouadha. (2023). (Under Review)

JAINUL FATHIMA | Artificial Intelligence | Best Researcher Award

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Dr. JAINUL FATHIMA | Artificial Intelligence | Best Researcher Award

Associate Professor, Francis Xavier Engineering College, India

📘 Dr. A. Jainul Fathima, B.Tech., M.E., Ph.D., is an innovative professor with a strong passion for fostering academic development and success for every student. With 12 years of combined experience in teaching, research, and industry, she excels in implementing technology-based curriculum delivery and assessment tools.

Profile

Scopus

Education🎓

Dr. Fathima holds a Ph.D. in Computational Drug Discovery from Kalasalingam Academy of Research and Education, where her interdisciplinary research focused on developing anti-viral drugs for dengue targets using AI techniques. She earned her M.E. in Computer Science and Engineering from Anna University with an 83% aggregate and a B.Tech. in Information Technology from Anna University with a 75% aggregate.

Experience 🛠️

👩‍🏫 With 12 years of total experience, Dr. Fathima has 6 years of teaching experience, currently serving as an Assistant Professor at Francis Xavier Engineering College. She has previously worked at K.L.N. College of Information Technology, Sethu Institute of Technology, and Kalasalingam University. Her research experience includes 3 years as a UGC Research Fellow and 2 years of teaching and instructing in Qatar. She also has 1 year of industrial experience as a Research Assistant in Computer-Aided Drug Design.

Research Interests 🔍

🔬 Dr. Fathima’s research interests are in the areas of computational drug discovery, machine learning, artificial intelligence, and bioinformatics. Her work focuses on applying advanced computational techniques to predict protein interactions and develop therapeutic solutions for diseases like dengue and Alzheimer’s.

Awards 🏆

🏆 Dr. Fathima has received several accolades, including the “Research Associate Award” from the Anti-viral Research Society in 2022, “Best Paper Award” at INCODS ’17 and NCAC ’09, and the “Outstanding Student Award” from Mepco Schlenk Engineering College.

Publications 📚

A comprehensive review on heart disease prognostication using different artificial intelligence algorithms, Computer Methods in Biomechanics and Biomedical Engineering, February 2024. Cited by 1.5

Alzheimer’s Patients Detection using Support Vector Machine (SVM) with Quantitative Analysis, Neuroscience Informatics, 2021. Cited by 0.5

IoT-Based Intelligent System for Garbage Level Monitoring in Smart Cities, International Conference on IoT, Communication and Automation Technology, 2023. Scopus Indexed

Intelligent Deep Learning Framework for Breast Cancer Prediction using Feature Ensemble Learning, IEEE Global Conference for Advancement in Technology, 2023. Scopus Indexed

Compressing Biosignal for diagnosing chronic diseases, Journal of Physics: Conference Series, 2021. Scopus Indexed