Prof. Dr. Brigitte Jaumard | Machine Learn Award | Best Researcher Award

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Prof. Dr. Brigitte Jaumard | Machine Learn Award | Best Researcher Award

Prof. Dr. Brigitte Jaumard, Concordia University, Canada

Prof. Dr. Brigitte Jaumard is a distinguished professor in the Computer Science and Software Engineering Department at Concordia University, Canada. She has a prolific career in academia and research, holding multiple prestigious roles, including Tier I Canada Research Chair (CRC) in Optimization of Communication Networks. Her work spans over several decades, and she has contributed significantly to the fields of artificial intelligence, communication networks, and optimization. Dr. Jaumard has also held leadership positions at the Computer Research Institute of Montreal (CRIM) and has been recognized for her innovative work in AI and machine learning. She has received numerous awards, including Best Paper Awards at international conferences. 🌟

Professional Profile

Google Scholar

Suitability for Award

Prof. Dr. Brigitte Jaumard is an ideal candidate for the Research for Best Researcher Award due to her outstanding contributions to the fields of artificial intelligence, optimization, and communication networks. Her leadership in research, exemplified by her role as a Tier I Canada Research Chair and her work in AI and machine learning, has made significant strides in both theoretical and applied research. Prof. Jaumard’s numerous awards and honors further attest to the high regard in which her work is held. Her impactful research and dedication to advancing technology make her an excellent choice for this prestigious award. 🏆

Education

🎓 Prof. Dr. Brigitte Jaumard holds a Thèse d’Habilitation from Université Pierre et Marie Curie, Paris (1990), and a Ph.D. in Electrical Engineering from École Nationale Supérieure des Télécommunications (ENST), Paris, with the highest honors in 1986. She also completed a DEA (M.Sc.) in Artificial Intelligence from Université Paris VI (1984) and a degree in Computer Engineering/Information System Engineering from Institut d’Informatique d’Entreprise (1983). Her educational background laid a solid foundation for her career in optimization, AI, and communication networks. 📘

Experience

🧑‍🏫 Prof. Jaumard has held several prestigious academic appointments, including as a professor at Concordia University since 2010, where she currently teaches and conducts research in optimization and AI. She served as a Tier I Canada Research Chair in Optimization of Communication Networks from 2001 to 2019. Additionally, Prof. Jaumard has been involved in administrative roles, such as the Scientific Director of CRIM and Principal Data Scientist at Ericsson’s Global AI Accelerator. Her leadership in both academic and industrial research has made significant impacts on AI and network optimization. 🌍

Awards and Honors

🏅 Prof. Jaumard has received multiple accolades, including Best Paper Awards at the IEEE International Symposium on Measurements & Networking (2022) and IEEE Sarnoff Symposium (2017). She also ranked 1st in the 2022 ITU Artificial Intelligence/Machine Learning in 5G Challenge (Graph Neural Networking) and 2nd in 2021. These awards highlight her groundbreaking contributions to AI, machine learning, and network optimization. Her consistent recognition in prestigious conferences and competitions underscores her expertise and leadership in the field. 🌟

Research Focus

🔬 Prof. Jaumard’s research focuses on optimization of communication networks, artificial intelligence, machine learning, and data-centric AI. She has made significant contributions to the development of scalable network models, including network digital twins, and has advanced the application of graph neural networks in communication systems. Her work in AI spans across both theoretical aspects and real-world applications, particularly in optimizing network performance and improving AI systems’ reliability. Prof. Jaumard’s research has had a lasting impact on both academia and industry. 🧑‍💻

Publication Top Notes:

  • New branch-and-bound rules for linear bilevel programming
    • Year: 1992
    • Citations: 969
  • Cluster analysis and mathematical programming
    • Year: 1997
    • Citations: 961
  • Algorithms for the maximum satisfiability problem
    • Year: 1990
    • Citations: 558
  • A generalized linear programming model for nurse scheduling
    • Year: 1998
    • Citations: 408
  • A branch and cut algorithm for nonconvex quadratically constrained quadratic programming
    • Year: 2000
    • Citations: 262

 

Mr. Yeonsoo Kim | AI Network Awards | Best Researcher Award

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Mr. Yeonsoo Kim | AI Network Awards | Best Researcher Award

Mr. Yeonsoo Kim, Surromind, South Korea

Yeonsoo Kim is a South Korean researcher specializing in AI and robotics development, with a particular focus on data analytics and autonomous systems. Currently, Yeonsoo is a researcher at Surromind in Seoul, where they contribute to advanced robotics and AI projects. With prior experience as a researcher at HnT in Suwon and an internship at the Korea Railroad Research Institute in Uiwang, Yeonsoo has developed a robust skill set in data-driven innovation. Yeonsoo holds degrees in engineering from Kyonggi University and has earned professional certifications in big data analysis and advanced data analytics. Recognized for their contributions to the AI field, Yeonsoo was awarded the ICONI 2023 Outstanding Paper award. Proficient in Python and ROS 2, they are committed to advancing automation and machine learning in applied technology. Yeonsoo’s background reflects a blend of technical expertise and innovation, making them a promising figure in the realm of AI and robotics.

Professional Profile:

Google Scholar

Summary of Suitability for the Award:

Yeonsoo Kim is a promising candidate for the Best Researcher Award due to her strong background in AI and robotics, relevant industry experience, and award-winning contributions to data analytics and advanced technology. Her work in AI and robotics, supported by her roles at prominent research institutions in South Korea, demonstrates her capability to advance these rapidly evolving fields.

🎓Education :

Yeonsoo Kim pursued their academic journey in engineering at Kyonggi University, South Korea. Beginning their studies in 2017, Yeonsoo completed a bachelor’s degree with a focus on engineering in early 2023 and is currently engaged in postgraduate studies, expected to finish in August 2024. Throughout their education, Yeonsoo specialized in areas integral to modern AI and robotics, such as big data analysis and autonomous systems, equipping them with the theoretical and practical skills necessary for advanced technological development. Their academic experience includes coursework and projects that emphasize AI applications, data analytics, and robotics programming, providing a comprehensive foundation for their research work. With an emphasis on interdisciplinary learning, Yeonsoo’s education has shaped their approach to real-world challenges in robotics and machine learning, further enhanced by certifications in advanced data analytics.

🏢Professional Experience :

Yeonsoo Kim has amassed valuable professional experience in AI, robotics, and data analytics. Currently, they work as a researcher at Surromind in Seoul, where they contribute to AI and robotics projects, integrating machine learning techniques to drive innovations in automation. Previously, Yeonsoo was a researcher at HnT in Suwon from 2022 to early 2024, focusing on the practical application of data analytics in industrial settings. Before that, they interned at the Korea Railroad Research Institute in Uiwang (2021-2022), where they gained hands-on experience in real-time data processing and control systems in transportation. Each role has enhanced their expertise in data-driven research and reinforced their commitment to developing AI-driven technologies. Yeonsoo’s work experience has honed their ability to integrate AI methodologies into various industrial applications, making significant contributions to the fields of robotics and big data.

🏅Awards and Honors :

Throughout their career, Yeonsoo Kim has been recognized for their achievements in AI and data analytics. They hold several notable certifications and awards, including the Engineer Big Data Analysis certification, which signifies their advanced skill in managing and interpreting complex datasets. In recognition of their expertise in data science, Yeonsoo earned the Advanced Data Analytics Semi-Professional (ADsP) certificate, a credential that underscores their proficiency in advanced analytics and statistical applications. Yeonsoo’s research contributions have also been acknowledged with the ICONI 2023 Outstanding Paper award, reflecting their ability to produce impactful, high-quality research in AI. These awards and certifications highlight Yeonsoo’s dedication to continuous learning and excellence in data analytics and artificial intelligence, positioning them as a forward-thinking researcher committed to pushing the boundaries of robotics and AI technology.

🔬Research Focus:

Yeonsoo Kim’s research is centered on the development of AI and robotics, with a focus on integrating big data analytics into autonomous systems. Their work encompasses both software and hardware aspects of robotics, with applications ranging from industrial automation to transportation technology. Yeonsoo’s current role at Surromind involves utilizing AI algorithms to enhance robotic functions, leveraging data analytics to optimize decision-making in autonomous systems. Their previous research at HnT and the Korea Railroad Research Institute focused on real-time data processing and implementing machine learning models for system control, showcasing their versatility across different sectors. With proficiency in Python and ROS 2, Yeonsoo develops scalable, data-driven solutions for complex robotic applications, aiming to make autonomous systems more efficient and adaptable. Their work is driven by a commitment to advancing AI as a transformative tool in robotics, with a special emphasis on data-informed system intelligence.

Publication Top notes:

Title: “Autoencoder-Based Cargo Recommendation System with Latent Factor Model”

Citations: 1

Title: “Deep Learning-Based Freight Recommendation System for Freight Brokerage Platform”
Title: “Real-Time Detection of Printing Defects with YOLOv5 Models”
Title: “Development of a Human-Following Transport Robot for Collaboration with Railway Workers”
Title: “Identifying Process Abnormalities through Real-Time Defect Detection”

 

 

Dr. Thomas Kotoulas | Artificial Intelligence Award | Best Researcher Award

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Dr. Thomas Kotoulas | Artificial Intelligence Award | Best Researcher Award

Dr. Thomas Kotoulas, Aristotle University of Thessaloniki, Greece, Greece

Dr. Thomas Kotoulas is a renowned physicist specializing in Newtonian dynamics and celestial mechanics. He has built a distinguished career in the study of dynamical systems, particularly the behavior of small bodies in the outer Solar System. He is currently a researcher at the University of Thessaloniki, where he earned his B.Sc. in Physics (1995) and Ph.D. in Physics (2003). Over the years, Kotoulas has become a key figure in the field of celestial mechanics, with numerous publications and contributions to the study of periodic orbits, stability, and resonance dynamics. His expertise extends to inverse problems in Newtonian dynamics and its applications in astronomy. Dr. Kotoulas has been awarded for his excellence as an external reviewer and continues to significantly contribute to the advancement of his research areas.

Professional Profile:

Google Scholar

Scopus

Summary of Suitability for Award:

Dr. Thomas Kotoulas is a strong contender for the Best Researcher Awards. His in-depth expertise, consistent scholarly output, contributions to high-impact research, leadership in projects, and acknowledgment from prestigious journals position him as a leading figure in the field of celestial mechanics. Given his outstanding research achievements and influential role in advancing scientific knowledge, Dr. Kotoulas is undoubtedly deserving of recognition as a top researcher in his field.

🎓Education: 

Dr. Kotoulas completed his B.Sc. in Physics at the Department of Physics at Aristotle University of Thessaloniki (A.U.Th.). He further pursued his postgraduate studies, culminating in a Ph.D. in Physics from the same department in 2003. His doctoral research focused on the dynamical evolution of small bodies in resonant areas within the outer Solar System, for which he received an excellent evaluation. His Ph.D. work was supervised by Professor John D. Hadjidemetriou. In addition to his academic qualifications, Dr. Kotoulas was awarded a fellowship from the National Foundation of Fellowships (Ι.Κ.Υ.) during his doctoral studies, where he specialized in dynamical systems and celestial mechanics. His academic journey was marked by excellence, shaping his future contributions to the scientific community in the fields of celestial mechanics and dynamics.

🏢Work Experience:

Dr. Kotoulas has accumulated extensive experience in the field of celestial mechanics and dynamical systems. He has worked on several significant research projects, including the “Dynamics of the restricted three-body problem and applications in Celestial Mechanics,” which was funded by the Greek Ministry of Education and the European Community. As a post-doctoral researcher, he contributed to the study of retrograde periodic orbits in the restricted three-body problem, focusing on applications in asteroids and the Kuiper Belt. Over the years, he has also served as a reviewer for several esteemed journals, such as “Celestial Mechanics and Dynamical Astronomy,” “Astrophysics and Space Science,” and “Research in Astronomy and Astrophysics.” His academic career is marked by his deep involvement in the application of inverse problems in Newtonian dynamics, which he continues to explore and develop through his research.

🏅Awards:

Dr. Thomas Kotoulas has received several prestigious awards and honors throughout his career. Notably, he was recognized as one of the best external reviewers for the journal “Research in Astronomy and Astrophysics” in 2022, receiving the Outstanding Reviewer Award for his valuable contributions. He also received a letter of recognition from Dr. Fabio Santos, the Publishing Editor of “Astrophysics and Space Science,” for his outstanding work as a reviewer during 2021 and 2022. Furthermore, Dr. Kotoulas was included in the Mathematical Reviews database, where he has written reviews for numerous papers on celestial mechanics. His work has been consistently acknowledged by the scientific community, affirming his expertise in dynamical systems and celestial mechanics. These honors highlight his significant contributions to the field, particularly in the areas of celestial mechanics, dynamics, and inverse problems.

🔬Research Focus:

Dr. Kotoulas’ primary research focus lies in the field of Newtonian dynamics and celestial mechanics, with an emphasis on the restricted three-body problem, orbital stability, and resonance dynamics. His research explores the dynamical evolution of small bodies, particularly in the outer Solar System, and how these bodies behave under the influence of resonances with larger celestial bodies. He specializes in the computation of families of periodic orbits, spectral analysis, and stability/instability in resonance regions. Additionally, Dr. Kotoulas works on inverse problems in Newtonian dynamics, applying them to astronomy and galactic dynamics. His work involves finding generalized force fields from families of orbits, as well as applying these techniques to improve our understanding of the structure and stability of orbital systems. Through his research, Dr. Kotoulas has significantly contributed to advancing theoretical models that describe the motion of celestial bodies and their dynamical interactions.

Publication Top Notes: 

  • “Planar Periodic Orbits in Exterior Resonances with Neptune”
    • Citations: 44
  • “Comparative Study of the 2:3 and 3:4 Resonant Motion with Neptune: An Application of Symplectic Mappings and Low Frequency Analysis”
    • Citations: 43
  • “On the Stability of the Neptune Trojans”
    • Citations: 34
  • “Symmetric and Nonsymmetric Periodic Orbits in the Exterior Mean Motion Resonances with Neptune”
    • Citations: 32
  • “On the 2/1 Resonant Planetary Dynamics–Periodic Orbits and Dynamical Stability”
    • Citations: 31

 

 

 

 

Mr. Congcong Ren | AI Award | Best Researcher Award

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Mr. Congcong Ren | AI Award | Best Researcher Award

Mr. Congcong Ren, Henan University of Science and Technology, China

Mr. Congcong Ren is a dedicated Master’s student in Vehicle and Traffic Engineering at Henan University of Science and Technology, with a Bachelor’s degree in Mechanical and Electrical Engineering from Henan Agricultural University. His expertise spans deep learning, algorithm development, and software testing, with practical experience in developing intelligent vehicles and defect detection systems. Mr. Ren has contributed to projects like an intelligent small car and wire rope defect detection, and he has gained hands-on experience during internships at Iflytek and Zeekr. His technical proficiency includes Python, PyTorch, and HIL test software, complemented by multiple school-level awards for innovation and entrepreneurship.

Professional Profile:

Orcid

Suitability for the Award

Mr. Congcong Ren is a highly suitable candidate for the Best Researcher Award based on the following points:

  1. Innovative Research:
    • His work on nighttime pedestrian detection and trajectory tracking addresses critical safety concerns in autonomous and intelligent vehicle systems. The use of fusion techniques combining visual and radar data showcases innovation in enhancing vehicle safety.
  2. Practical Experience:
    • His participation in significant projects like the intelligent small car and wire rope defect detection demonstrates his ability to apply theoretical knowledge to real-world challenges. These projects not only reflect technical skill but also his capability to collaborate effectively with industry partners.
  3. Academic and Professional Growth:
    • Mr. Ren’s ongoing master’s studies in artificial intelligence and traffic engineering, combined with his hands-on experience in internships at leading companies like Iflytek and Zeekr, underline his rapid professional development and adaptability in a fast-evolving field.
  4. Recognition and Skills:
    • His recognition through scholarships, awards, and publication of SCI papers highlights his academic excellence and contribution to the field. His proficiency in deep learning frameworks, coupled with practical software testing skills, positions him as a strong contender for research excellence.

Summary of Qualifications

  1. Educational Background:

    • Bachelor’s Degree in Mechanical and Electrical Engineering – Henan Agricultural University (2018-2022).
      • Major courses included Mechanical Design, Automobile Design, New Energy, and Traffic Engineering.
    • Master’s Degree (ongoing) in Vehicle and Traffic Engineering – Henan University of Science and Technology (2022-2025).
      • Major courses include Principles and Methods of Artificial Intelligence, Traffic Simulation Technology, System Control Theory, and Intelligent Network Technology.

  2. Project Experience:

    • Challenge Cup Project (2022-2023): Developed an intelligent small car with adjustable wheelbase and chassis height, integrating camera and millimeter-wave radar data for obstacle detection and avoidance.
    • Wire Rope Defect Detection Project (2023): Collaborated with Luoyang Wilrop Testing Technology Co., LTD. to improve YOLOv5s algorithm for defect detection in wire ropes using industrial camera images, meeting the project’s expected requirements.

  3. Internship Experience:

    • Iflytek (2023-2024): Tested large model voice assistant software, proficient in Android Studio and Adobe Audition, and used Python for batch pressure testing.
    • Zeekr (2024): Proficient in HIL test software (ECU-TEST, Canoe, INCA), familiar with software development processes and protocols (LIN/CAN), and involved in new energy vehicle controller testing.

  4. Technical Skills:

    • Proficient in Python, PyTorch, Matlab, Simulink, and various HIL test software.
    • Strong capabilities in deep learning, algorithm development, and software testing.
    • Recognized with school-level scholarships and awards, including the innovation and entrepreneurship competition fund.

Publication Top Notes:

1.  Study on Nighttime Pedestrian Trajectory-Tracking from the Perspective of Driving Blind Spots –  (2024).

2.  Nighttime Pedestrian Detection Based on a Fusion of Visual Information and Millimeter-Wave Radar –  (2023).

Both articles reflect his focus on advanced technologies in vehicle safety, particularly in challenging environments like nighttime driving.

Conclusion

Mr. Congcong Ren is an outstanding candidate for the Best Researcher Award, given his solid educational foundation, innovative research contributions in vehicle safety, and substantial practical experience in engineering and software testing. His ability to combine academic research with practical applications, particularly in the field of intelligent vehicle systems, makes him a deserving recipient of this award.

 

 

 

Assoc Prof Dr. Khaled EL Sayed | AI Awards | Best Researcher Award-3044

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Assoc Prof Dr. Khaled EL Sayed | AI in medicine | Best Researcher Award

Assoc Prof Dr. Khaled EL Sayed, Benha University, Egypt

Prof. Dr. Khaled El Sayed is an esteemed Associate Professor of Biomedical Engineering at Benha University, Egypt, with a comprehensive academic background including a B.Sc., M.Sc., and Ph.D. from Cairo University, specializing in hand geometry verification, protein function prediction, and EEG dynamics. He holds a Diploma in Medical Radiation Protection and is pursuing DBA studies. His notable achievements include awards for Excellence in Graduate Studies and patents for innovative medical systems, including a smart treatment system for heat/sun stroke and a smart patient mattress disinfection system. Prof. El Sayed has extensive teaching experience and has held significant roles, such as heading the Biomedical Department at MTI and consulting for various organizations. Currently, he is also a Medical Planning Consultant for ECG, Executive Manager at the Medical Equipment Manufacture Incubator (MED-Tech), and oversees the Medical Equipment Calibration Lab at Benha University. His expertise extends to BCI, electronic and microcontroller design, and infection control, and he contributes as a reviewer and board member for prominent journals in his field.

Professional Profile🌍

Orcid

Suitability for the Best Researcher Award

Prof. Dr. Khaled El Sayed is highly suitable for the Best Researcher Award due to the following reasons:

  1. Extensive Experience and Expertise: His broad experience spans academia, industry, and consultancy, showcasing his comprehensive understanding and leadership in biomedical engineering. His roles in teaching, research, and management highlight his multifaceted expertise.
  2. Significant Contributions: Prof. El Sayed’s work in developing innovative medical systems and his patents demonstrate a significant impact on medical technology. His contributions in bioinformatics and medical planning underscore his research excellence.
  3. Academic and Research Achievements: His extensive teaching experience, research publications, and editorial roles reflect his commitment to advancing knowledge in his field. His involvement in high-impact journals and conferences further illustrates his active participation in the research community.
  4. Leadership and Management: His leadership roles in various projects, including managing medical equipment incubators and calibration labs, demonstrate his capability in steering important initiatives and fostering collaboration.
  5. Awards and Recognition: His recognition through awards and patents, coupled with his ongoing DBA thesis, highlights his continued dedication to research and development.

Educational Background:

Prof. El Sayed earned his B.Sc., M.Sc., and Ph.D. in Biomedical Engineering from Cairo University, with notable research on hand geometry verification, protein function prediction, and EEG dynamics. His academic journey includes a Diploma in Medical Radiation Protection and ongoing DBA studies. 🎓

Prizes and Patents:

He has been awarded for Excellence in Graduate Studies and holds patents for a smart system for treating heat/sun stroke and a smart patient mattress disinfection system. 🏅

Professional Experience:

He has extensive experience teaching Biomedical Engineering courses at Benha University, previously headed the Biomedical Department at MTI, and consulted for various organizations. His earlier roles include Senior Biomedical Engineer at Dar Al-Fouad Hospital and Electronics Instructor at Cairo University. 📚

Current Positions:

Prof. Dr. Khaled El Sayed is an Associate Professor at Benha University in Egypt, specializing in Biomedical Engineering. He also serves as a Medical Planning Consultant for ECG, Executive Manager at the Medical Equipment Manufacture Incubator (MED-Tech), and Executive Manager of the Medical Equipment Calibration Lab at Benha University. Additionally, he is a Biomedical Engineering Consultant for the Egyptian Engineering Syndicate and a Board Member of the Egyptian Biomedical Engineering Society. 🏥

Special Skills and Interests:

Prof. El Sayed is proficient in PC software, MATLAB, and various programming languages. His interests include BCI, electronic design, microcontroller design, and infection control. He is fluent in Arabic and English. 💻

Editorial and Review Positions:

He contributes as a reviewer and editorial board member for journals such as AJMB and the American Journal of Bioinformatics Research. 📝

Publication Top Notes:

  • Title: A Low-Cost and PC-Based Automatic Hand Geometry Verification System
    • Year: 2009
  • Title: Comparison Between Different Methods for Protein Function Prediction
    • Year: 2009
  • Title: Estimation of the Correlation Between Protein Sub-Function Categories Based on Overlapping Proteins
    • Year: 2010
  • Title: Exploring Protein Functions Correlation Based On Overlapping Proteins and Cluster Interactions
    • Year: 2011
  • Title: Determining the Relations Between Protein Sub-Function Categories Based On Overlapping Proteins
    • Year: 2011

 

Dr. Mohamed Elhamahmy | AI – Machine Learning | Best Researcher Award

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Dr. Mohamed Elhamahmy | AI – Machine Learning | Best Researcher Award

Dr. Mohamed Elhamahmy, National Telecommunications Regulatory Authority, Egypt,

Dr. Mohamed Ezzat Elhamahmy is a Senior Expert in Cybersecurity at the National Telecommunications Regulatory Authority in Cairo and serves on the advisory board at the College of Computers and Information Technology, Arab Academy for Science, Technology and Maritime Transport. He holds a Bachelor’s in Electrical Engineering from the Military Technical College, a Master’s in Systems and Computer Engineering from Al-Azhar University, a Ph.D. in Information Technology from Cairo University, and a Professional Master’s in Political Studies and Security. Dr. Elhamahmy has extensive experience in IT and cybersecurity, having managed the Information Systems Department of the Armed Forces and established a dedicated cybersecurity unit. His expertise includes incident handling, network security, and strategic planning, supported by certifications such as CEH and CISSP. His notable contributions include advancing cybersecurity practices and education in the region.

Professional Profile🌍

Orcid
Scopus

Educational Background 🎓

Dr. Mohamed Ezzat Elhamahmy graduated from the Military Technical College in 1989 with a Bachelor’s degree in Electrical Engineering. He earned a Master’s degree in Systems and Computer Engineering from Al-Azhar University in 2001, a Ph.D. in Information Technology from Cairo University in 2011, and a Professional Master’s degree in Political Studies and Security from the Faculty of Economics and Political Science.

Professional Experience 💼

Dr. Elhamahmy has an extensive career in information technology and cybersecurity. From 1990 to 2015, he worked with the Information Systems Department of the Armed Forces, holding roles such as Systems Manager, Network Manager, and IT Manager. He specialized in cybersecurity from 2009 to 2014 and established a dedicated cybersecurity unit in 2015. He led the unit until 2019, overseeing its development, training programs, and strategic planning.

Current Roles 🏢

Since 2019, Dr. Elhamahmy has been serving as a Senior Expert in Cybersecurity at the National Telecommunications Regulatory Authority, Cairo. He is also a member of the advisory board at the College of Computers and Information Technology, Arab Academy for Science, Technology and Maritime Transport, where he lectures and supervises academic programs.

Skills and Expertise 🛠️

Dr. Elhamahmy is skilled in incident handling, research and development in network security, and strategic cybersecurity planning. His expertise includes advanced knowledge of various technologies and applications, with strong communication, problem-solving, and leadership abilities.

Certifications and Training 🏅

He has obtained numerous certifications, including Certified Ethical Hacker (CEH), Certified Information Systems Security Professional (CISSP), and CCNA. He has also completed specialized training in Oracle, Microsoft Windows Server, and various cybersecurity tools.

Contributions and Achievements 🌟

Dr. Elhamahmy is known for his significant contributions to cybersecurity, including establishing successful cybersecurity units and leading strategic initiatives. His work has greatly impacted the development of cybersecurity practices and education in the region.

Publication Top Notes:

  • Improving Intrusion Detection Using LSTM-RNN to Protect Drones’ Networks
    • Year: 2024
  • Internet of Drones Intrusion Detection Using Deep Learning
    • Year: 2021
  • A Real-Time Firewall Policy Rule Set Anomaly-Free Mechanism
    • Year: 2019
  • A Proposed Approach for Management of Multiple Firewalls Using REST API Architecture
    • Year: 2019
  • Towards a Practical Real-Time Applications of Face Verification
    • Year: 2019

 

 

 

 

Dr. Kuanxin Shen | Artificial intelligent Awards | Best Researcher Award

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Dr. Kuanxin Shen | Artificial intelligent Awards | Best Researcher Award

Dr. Kuanxin Shen , Shenyang University of Technology , China

Kuanxin Shen, a 27-year-old PhD candidate in Control Science and Engineering at Shenyang University of Technology, China, focuses his research on 3D Gaze Estimation using neural networks and deep learning. He holds a Bachelor’s degree earned in 2021 and a Master’s degree obtained in 2024. From 2022 to 2024, Kuanxin worked as an Algorithm Developer at Ningbo Chunjian Electronic Technology Co., Ltd., specializing in 3D intelligent perception in automotive cockpits. His research achievements include a Chinese utility model patent, several Chinese computer software copyrights, and three Chinese invention patents related to 3D eye tracking and gaze estimation. Kuanxin has also authored a book on industrial robot simulation and published a paper in the journal Sensors. He has been recognized with the third prize in the Henan Province College Students’ Robot Innovation Competition, a first-class academic scholarship, and the Excellent Thesis Award from Liaoning Province for his master’s thesis.

Professional Profile:

Orcid

🎓Educational Background:

Kuanxin Shen earned his Bachelor’s degree in 2021 and obtained his Master’s degree in 2024. He is currently pursuing a PhD in Control Science and Engineering at Shenyang University of Technology, China.

🏢Work Experience:

From 2022 to 2024, Kuanxin Shen worked as an Algorithm Developer at Ningbo Chunjian Electronic Technology Co., Ltd., specializing in 3D intelligent perception in automotive cockpits. His responsibilities included driver gaze detection, skeleton landmark detection, behavior detection (such as smoking and phone usage), and the detection of driver distraction and fatigue. His tasks encompassed image processing, 3D detection, data annotation, cleaning, augmentation, neural network training, and model testing.

🏆Awards and Recognitions:

During his undergraduate studies, Kuanxin Shen won the Third Prize in the 6th Henan Province College Students’ Robot Innovation Competition. In April 2024, he was awarded the First-Class Academic Scholarship during his master’s studies. In May 2024, his master’s thesis titled “Research on the Application of Driver Gaze Estimation Technology in DMS” received the Excellent Thesis Award from Liaoning Province, China

Publication Top Notes:

Title: Model-Based 3D Gaze Estimation Using a TOF Camera

  • Journal: Sensors

 

 

Mr. Asif Mehmood | Artificial intelligence Awards | Best Researcher Award

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Mr. Asif Mehmood | Artificial intelligence Awards | Best Researcher Award

Mr. Asif Mehmood, National university of technology, Pakistan

Asif Mehmood is a dedicated professional with a strong academic background and diverse expertise in computer sciences. Currently pursuing a PhD in Computer Sciences at COMSATS University Islamabad, Wah Campus, he holds a Master’s degree and a Bachelor’s degree in the same field. With a keen interest in machine learning and deep learning, Asif has contributed to notable publications in prestigious journals, focusing on human gait recognition and biometric techniques. His experience spans from research associate roles to lecturing positions at HITEC University Taxila, showcasing his commitment to academia and research. Asif’s technical proficiency includes programming languages such as MATLAB, JavaScript, and Java, along with extensive experience in project development and academic projects. He resides in Attock, Punjab, Pakistan, and is open to providing references upon request.

Professional Profile:

Scopus

🎓 Education:

Asif Mehmood has pursued a remarkable academic journey, demonstrating consistent excellence in his educational endeavors. He commenced his formal education with a Bachelor of Science in Computer Sciences (BSCS) from the University of Wah, spanning from 2013 to 2017, where he attained a commendable CGPA of 3.46 out of 4.0. Building upon this foundation, he pursued a Master of Science in Computer Sciences (MSCS) at COMSATS University Islamabad, Wah Campus, from 2018 to 2020, achieving an impressive CGPA of 3.84. Asif further advanced his academic pursuits by undertaking a PhD in Computer Sciences at the same institution, currently in progress, with an outstanding CGPA of 3.94 thus far.

💼 Experience:

Asif Mehmood has enriched his professional experience through roles at HITEC University Taxila. He commenced as a Research Associate in January 2022, where he actively contributed to research endeavors until June 2022. Building upon his expertise, Asif transitioned into the role of Lecturer in Computer Science at the same institution in September 2022, a position he currently holds. These roles have allowed Asif to apply his academic knowledge and research skills in a practical setting while also nurturing the next generation of computer science professionals through teaching and mentorship.

📝 Projects:

Asif Mehmood has demonstrated his proficiency in software development and research through various notable projects. Among these, he developed a Document Clustering Search Engine using Java and MySQL, showcasing his skills in both programming and database management. Additionally, his thesis focused on Prosperous Human Gait Recognition, employing Machine Learning techniques within MATLAB, highlighting his expertise in this advanced field. Furthermore, Asif has undertaken diverse academic projects encompassing Assembly Language programming, Android app development, and web development, reflecting his versatility and innovative approach to problem-solving in the realm of computer science.

Publication Top Notes:

  1. Human Gait Recognition by using Two Stream Neural Network along with Spatial and Temporal Features
    • Authors: Mehmood, A.; Amin, J.; Sharif, M.; Kadry, S.
    • Journal: Pattern Recognition Letters, 2024, 180, pp. 16–25
    • Citations: 0
  2. Prosperous Human Gait Recognition: an end-to-end system based on pre-trained CNN features selection
    • Authors: Mehmood, A.; Khan, M.A.; Sharif, M.; Riaz, N.; Ashraf, I.
    • Journal: Multimedia Tools and Applications, 2024, 83(5), pp. 14979–14999
    • Citations: 24
  3. TS2HGRNet: A paradigm of two stream best deep learning feature fusion assisted framework for human gait analysis using controlled environment in smart cities
    • Authors: Khan, M.A.; Mehmood, A.; Kadry, S.; Alsubai, S.; Alqatani, A.
    • Journal: Future Generation Computer Systems, 2023, 147, pp. 292–303
    • Citations: 3
  4. Human gait analysis for osteoarthritis prediction: a framework of deep learning and kernel extreme learning machine
    • Authors: Khan, M.A.; Kadry, S.; Parwekar, P.; Khan, J.A.; Naqvi, S.R.
    • Journal: Complex and Intelligent Systems, 2023, 9(3), pp. 2665–2683
    • Citations: 23
  5. Human gait recognition: A deep learning and best feature selection framework
    • Authors: Mehmood, A.; Khan, M.A.; Tariq, U.; Mostafa, R.R.; ElZeiny, A.
    • Journal: Computers, Materials and Continua, 2021, 70(1), pp. 343–360
    • Citations: 8