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.

šŸŽ“Education:Ā 

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 (Ī™.Īš.Ī„.) 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.

šŸ¢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.

šŸ…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.

šŸ”¬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:Ā 

  • “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 Dynamicsā€“Periodic Orbits and Dynamical Stability”
    • Citations: 31

 

 

 

 

Dr. Julius Olaniyan | Machine Learning Award |Best Researcher Award

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Dr. Julius Olaniyan | Machine Learning Award |Best Researcher Award

Dr. Julius Olaniyan, Bowen University, NigeriaĀ 

Olaniyan JuliusĀ in Odo-Owa, Kwara State, Nigeria. He is a Lecturer II in the Computer Science Department at Bowen University, Iwo, Osun State, Nigeria. Julius holds a Ph.D. in Computer Science (2023) and has extensive experience in software development, data analysis, and teaching. He has worked in several institutions, including Landmark University, Federal Polytechnic Auchi, and Feghas Solutions Ltd. Over his career, he has developed various applications using programming languages such as C, C++, Java, Python, and PHP. Julius specializes in Artificial Intelligence, Computer Vision, Natural Language Processing, and Machine Translation. A devoted husband and father of three, Julius is passionate about advancing AI and its application in healthcare and education. He has contributed to several innovative research papers in the field of computer science and AI.

Professional Profile:

Google Scholar

Summary of Suitability for Award:

Dr. Olaniyan has demonstrated outstanding proficiency and expertise in the fields of Artificial Intelligence, Computer Vision, Natural Language Processing, and Machine Translation, with a solid academic background in Computer Science. He holds a Ph.D. in Computer Science from Landmark University, and has published extensively in high-impact journals and conferences. His work on cataract detection using deep learning, as well as his innovative contributions in areas like speech refinement and emotion recognition, highlights his commitment to advancing technology for real-world applications. Furthermore, his ability to collaborate across interdisciplinary research teams and contribute to several peer-reviewed articles reflects his academic rigor and leadership.

šŸŽ“Education:Ā 

Olaniyan Julius completed his Ph.D. in Computer Science at Landmark University (2023). He also holds a Master’s in Computer Science (M.Tech) from the Federal University of Technology, Akure (2019), where he also earned a Postgraduate Diploma (PGD) in 2012. Julius started his academic journey with a Bachelorā€™s in Computer Science from the Federal University of Oye Ekiti (2022). His earlier qualifications include a Higher National Diploma (HND) in Computer Science from Auchi Polytechnic (2006), and a National Diploma (ND) in the same field (2000). Julius completed his Secondary Education at Orota Community High School, Odo-Owa (1994) and his Primary Education at St. Thomas Catholic School (1988). His strong educational foundation in Computer Science has shaped his successful academic and professional career.

šŸ¢Work Experience:

Olaniyan Julius has a diverse career in academia and industry. He is currently a Lecturer II at Bowen University, Nigeria. Previously, he served as a Lecturer II at Landmark University (2023-2024) and as a Data Analyst at Federal Polytechnic Auchi (2013-2022). His industry experience includes working as a Software Developer/Business Developer at Feghas Solutions Ltd. (2009-2012) and a Tutor/Application Developer at Pesoka Systems Ltd. (2008). Julius also has teaching experience from his time as a Lecturer during his NYSC service at Maritime Academy of Nigeria (2007-2008). His early career included roles like Data Processing Officer at Ajaokuta Steel Company (2002-2004) and School Database Admin at Sani Bello Secondary School (2001). Juliusā€™s experience spans academic teaching, research, software development, data analysis, and project management.

šŸ…Awards:

Olaniyan Julius has received numerous accolades throughout his academic and professional journey. His Ph.D. dissertation was highly recognized, contributing to his recognition as an emerging scholar in Computer Science. He was awarded a best student award during his time at Landmark University and has been recognized by the Federal Polytechnic Auchi for his outstanding performance as a Data Analyst. Juliusā€™s commitment to education and research has earned him several institutional commendations for his efforts in developing AI-driven solutions in healthcare and education. His research in Artificial Intelligence and Machine Translation has garnered him recognition at international conferences. He is also an active member of several professional organizations in computer science and artificial intelligence. Juliusā€™s leadership and contributions to academic and professional initiatives have cemented his reputation as a passionate educator and researcher.

šŸ”¬Research Focus:

Olaniyan Julius specializes in Artificial Intelligence (AI), with a focus on Computer Vision, Natural Language Processing (NLP), and Machine Translation. His work primarily involves using deep learning techniques to create solutions for healthcare (e.g., cataract detection) and education (e.g., student performance evaluation). Julius is dedicated to developing hybrid AI models that combine traditional methods with transformative learning approaches. His research in audio signal denoising and speech-to-speech translation aims to enhance communication and multilingual interaction. He is passionate about designing AI-powered systems that can automate and optimize processes, improving outcomes in health diagnostics and online learning environments. Juliusā€™s work on emotion detection in virtual classrooms and the integration of CNN models for speech emotion recognition represents a significant contribution to the AI field. His interdisciplinary research approach holds promise for real-world AI applications in various domains.

Publication Top Notes:Ā 

  • “Utilizing an Attention-Based LSTM Model for Detecting Sarcasm and Irony in Social Media”
  • “Implementation of Audio Signals Denoising for Perfect Speech-to-Speech Translation Using Principal Component Analysis”
  • “Advancements in Accurate Speech Emotion Recognition Through the Integration of CNN-AM Model”
  • “Transformative Transparent Hybrid Deep Learning Framework for Accurate Cataract Detection”
  • “Parallel Attention Driven Model for Student Performance Evaluation”

 

 

 

 

Dr. Jianhuan Cen | AI for Science Awards | Best Researcher Award

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Dr. Jianhuan Cen | AI for Science Awards | Best Researcher Award

Dr. Jianhuan Cen, Sun Yat-sen University, China

Dr. Jianhuan Cen holds a master’s degree in Computational Mathematics and a bachelor’s degree in Information and Computing Science from Sun Yat-sen University, where he has consistently excelled academically and earned multiple scholarships. His research has made significant strides in AI model benchmarking for molecular property prediction and crystal structure prediction using diffusion models, showcasing his ability to integrate deep learning with scientific computation. Dr. Cenā€™s work has implications for material science and molecular simulation. He is known for his collaborative spirit and leadership in various research projects and software development efforts, and his versatility is evident from his involvement in programming problem review and testing school OJ websites.

Professional Profile:

Scopus
Google Scholar

Educational Background:

Dr. Cen has a robust academic foundation, with a master’s degree in Computational Mathematics and a bachelor’s degree in Information and Computing Science from Sun Yat-sen University, a leading institution in China. He has excelled academically and received multiple scholarships for his achievements.

Technical Skills and Contributions:

He has extensive hands-on experience in distributed computing, high-performance computing, and algorithm implementation using C/C++, Python, and Matlab. Dr. Cenā€™s project experience includes:

Implementing Locality Sensitive Hashing (LSH) on distributed clusters using Hadoop and Spark.

Developing a Non-Volatile Memory (NVM) based linear hash index, showcasing expertise in advanced database systems and memory environments.

Research Impact:

Dr. Cen has contributed to various high-impact projects, including AI model benchmarking for molecular property prediction and crystal structure prediction using diffusion models. His interdisciplinary work bridges the gap between deep learning and scientific computation, which could have broad applications in areas like material science and molecular simulation.

Collaboration and Leadership:

He has been involved in multiple research projects and collaborative software development efforts, indicating strong teamwork and leadership capabilities. He has also reviewed programming problems and tested school OJ websites, demonstrating his versatility.

Research Excellence:

Dr. Cen’s research focuses on solving high-dimensional partial differential equations (PDEs) using deep learning methods. He has developed innovative approaches that combine cutting-edge deep learning techniques with finite volume methods to tackle these complex problems.

Research Publications

1.Ā  “Adaptive Trajectories Sampling for Solving PDEs with Deep Learning Methods” (Applied Mathematics and Computation).

2.Ā  “Deep Finite Volume Methods for Partial Differential Equations” (SSRN).

Conclusion:

Dr. Jianhuan Cenā€™s academic achievements, research contributions in deep learning and computational mathematics, and technical prowess make him an outstanding candidate for the Best Researcher Award. His work is not only theoretically rigorous but also practically applicable, showing promise for future advancements in both academic and industrial contexts.

 

 

 

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. Renā€™s ongoing masterā€™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:

    • Bachelorā€™s Degree in Mechanical and Electrical Engineering ā€“ Henan Agricultural University (2018-2022).
      • Major courses included Mechanical Design, Automobile Design, New Energy, and Traffic Engineering.
    • Masterā€™s Degree (ongoing) in Vehicle and Traffic Engineering ā€“ 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 projectā€™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.Ā  Study on Nighttime Pedestrian Trajectory-Tracking from the Perspective of Driving Blind Spots ā€“Ā  (2024).

2.Ā  Nighttime Pedestrian Detection Based on a Fusion of Visual Information and Millimeter-Wave Radar ā€“Ā  (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 ProfilešŸŒ

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 Sayedā€™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. šŸŽ“

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. šŸ…

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. šŸ“š

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. šŸ„

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. šŸ’»

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. šŸ“

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 Masterā€™s in Systems and Computer Engineering from Al-Azhar University, a Ph.D. in Information Technology from Cairo University, and a Professional Masterā€™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 ProfilešŸŒ

Orcid
Scopus

Educational Background šŸŽ“

Dr. Mohamed Ezzat Elhamahmy graduated from the Military Technical College in 1989 with a Bachelor’s degree in Electrical Engineering. He earned a Masterā€™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 Masterā€™s degree in Political Studies and Security from the Faculty of Economics and Political Science.

Professional Experience šŸ’¼

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 šŸ¢

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 šŸ› ļø

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 šŸ…

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 šŸŒŸ

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 Dronesā€™ 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

šŸŽ“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.

šŸ¢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.

šŸ†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

 

 

Mrs. Marcia Baptista | Machine Learning and Prognostics | Best Researcher Award

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Mrs. Marcia Baptista | Machine Learning and Prognostics | Best Researcher Award

Mrs. Marcia Baptista, Delft University of Technology

Mrs. Marcia Baptista, currently an Assistant Professor at TU Delft and soon joining NOVA IMS, completed her Ph.D. in Engineering Design and Advanced Manufacturing at MIT Portugal Program šŸ“š. Her research in machine learning and deep learning for prognostics in aeronautics, conducted in collaboration with Rolls Royce and Embraer, has led to significant advancements in predictive maintenance technology šŸ”¬. Marcia’s career spans leadership roles at NASA Ames Research Center and Instituto TecnolĆ³gico de AeronĆ”utica, focusing on technical prognostics and system engineering across continents. Her contributions have earned her Best Paper awards at esteemed conferences and recognition for teaching excellence šŸ†. Beyond academia, Marcia chairs international conference sessions, serves editorial roles, and contributes to advanced engineering literature šŸŒ.

šŸŒ Professional Profile:

Orcid

Scopus

šŸ“š Education & Academic Path

I completed my Ph.D. in Engineering Design and Advanced Manufacturing at MIT Portugal Program, focusing on machine learning and deep learning for prognostics in aeronautics. This research involved collaborations with Rolls Royce and Embraer, resulting in significant advancements in predictive maintenance technology.

šŸ”¬ Research & Professional Experience

Currently serving as an Assistant Professor at TU Delft and starting soon at NOVA IMS, I’ve been actively involved in teaching, research, and leadership roles. My work spans multiple continents, including positions at NASA Ames Research Center and Instituto TecnolĆ³gico de AeronĆ”utica, where I contributed to cutting-edge projects in technical prognostics and system engineering.

šŸ† Achievements & Recognition

Throughout my career, I’ve been honored with numerous awards, including Best Paper accolades at prestigious conferences like WCE 2019 and ISM 2019. I’ve also received recognition for my teaching contributions and was awarded a Doctorate Scholarship from the Foundation for Sciences and Technology in Portugal.

šŸŒ Contributions & Outreach

Beyond academia, I’ve chaired sessions at international conferences and served as a web chair for the Intelligent Transport Systems Conference. My editorial roles include being a special issue editor for prominent journals and authoring chapters on advanced engineering topics.

Publication Top Notes:

  • Aircraft Engine Bleed Valve Prognostics Using Multiclass Gated Recurrent Unit
    • Year: 2023
    • Citations: 2
  • 1D-DGAN-PHM: A 1-D denoising GAN for Prognostics and Health Management with an application to turbofan
    • Year: 2022
    • Citations: 4
  • Relation between prognostics predictor evaluation metrics and local interpretability SHAP values
    • Year: 2022
    • Citations: 57
  • A self-organizing map and a normalizing multi-layer perceptron approach to baselining in prognostics under dynamic regimes
    • Year: 2021
    • Citations: 14
  • Classification prognostics approaches in aviation
    • Year: 2021
    • Citations: 15

 

 

Dr. Brijesh Kumar Chaurasia | Smart Technology Awards | Best Researcher Award

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Dr. Brijesh Kumar Chaurasia | Smart technology Awards | Best Researcher Award

Dr. Brijesh Kumar Chaurasia , Pranveer Singh Institute of Technology, Kanpur, India

Dr. Brijesh Kumar Chaurasia is a distinguished academic and researcher specializing in network security, with a primary focus on Vehicular Ad hoc Networks, Trust Management in VANETs, Blockchain, cloud authentication, and IoV/IoT. He earned his Ph.D. in Privacy Preservation in Vehicular Ad-hoc Networks from IIIT-Allahabad in 2013 and his M. Tech in Computer Science and Engineering from DAVV-Indore in 2006. With over 22 years of teaching experience and 4+ years in research and development, Dr. Chaurasia currently serves as a Professor and Dean of Research and Innovation at Pranveer Singh Institute of Technology, Kanpur. He has previously taught at ITM Group in Gwalior and IIIT Lucknow. He has been a principal investigator on several research grants, supervised numerous Ph.D. and postgraduate theses, and holds patents in IoT and smart systems. Dr. Chaurasia is actively involved in professional activities as a Senior Member of IEEE, Fellow of IETE, and member of IE and CSI. He has contributed to international journals and participated in various FDPs and workshops, showcasing his commitment to advancing knowledge and innovation in his field.

Professional Profile:

Google Scholar

šŸŽ“ Education:

Dr. Brijesh Kumar Chaurasia earned his Ph.D. in Computer Science and Engineering from IIIT-Allahabad, India, with his thesis focusing on Privacy Preservation in Vehicular Ad-hoc Networks. This prestigious degree was awarded on April 12, 2013, marking a significant milestone in his academic journey. Prior to his doctoral studies, Dr. Chaurasia completed his Master of Technology in Computer Science and Engineering from DAVV-Indore, India, in 2006. These educational accomplishments laid a strong foundation for his subsequent research and professional endeavors in the field of network security and technology.

šŸ’¼ Employment and Experience:

Dr. Chaurasia has a combined experience of over 27 years in Research & Development, Teaching, and Industry. Currently, he serves as a Professor in Computer Science and Engineering & Dean Research and Innovation at Pranveer Singh Institute of Technology, Kanpur. Previously, he held teaching positions at ITM Group, Gwalior, MP, India, and Indian Institute of Information Technology, Lucknow.

šŸ” Research Grants:

He has been involved in various research projects as Principal Investigator and Expert Member, securing grants for projects related to Hindi News portal development, IoT implementation and security, web redesigning, and Automatic Number Plate Recognition.

Publication Top Notes:

  1. Trust based location finding mechanism in VANET using DST
    • K Sharma, BK Chaurasia
    • 2015 Fifth International Conference on Communication Systems and Network, 2015
    • Cited by 66
  2. Message broadcast in VANETs using group signature
    • BK Chaurasia, S Verma, SM Bhasker
    • 2008 Fourth International Conference on Wireless Communication and Sensor Networks, 2008
    • Cited by 65
  3. Infrastructure based authentication in VANETs
    • BK Chaurasia, S Verma
    • International Journal of Multimedia and Ubiquitous Engineering, 2011
    • Cited by 54
  4. State of the art of data dissemination in VANETs
    • P Tomar, BK Chaurasia, GS Tomar
    • International Journal of Computer Theory and Engineering, 2010
    • Cited by 47
  5. Hiding sensitive association rules without altering the support of sensitive item(s)
    • D Jain, P Khatri, R Soni, BK Chaurasia
    • Advances in Computer Science and Information Technology. Networks and Communications, 2012
    • Cited by 43

 

 

 

Dr. Siwei Guan | Deep Learning Award | Best Researcher Award

Posted on by ScienceFather

Dr. Siwei Guan | Deep Learning Award | Best Researcher Award

Dr. Siwei Guan, Hangzhou Dianzi university, China

Dr. Siwei Guan, currently pursuing a Doctorate in Electronic Science and Technology at Hangzhou Dianzi University, China, stands at the forefront of groundbreaking research in anomaly detection. With a Master’s degree from the same university and a Bachelor’s from Jiangxi Normal University, his expertise shines in innovative approaches to multivariate time series data. Driven by a passion for advancement, his work, published in esteemed journals like Computer & Security and IEEE Sensors Journal, showcases pioneering techniques utilizing variational autoencoders and temporal neural networks. Supported by prestigious funding from the National Key Research and Development Program of China and the National Natural Science Foundation of China, he actively contributes to peer review activities, ensuring the quality of academic discourse. Dr. Guan’s dedication and achievements underscore his invaluable contributions to electronic science and technology, propelling the field forward with each innovative stride. šŸŒŸ

Professional Profile:

Orcid

šŸ« Education:

Dr. Siwei Guan is currently pursuing a Doctorate in Electronic Science and Technology at Hangzhou Dianzi University, China, building upon his prior academic achievements. He holds a Master’s degree in Electronic Information from the same university and completed his Bachelor’s in Electronic Information Engineering at Jiangxi Normal University. His research focuses on innovative approaches to anomaly detection in multivariate time series data, as evidenced by his publications in reputable journals like Computer & Security and IEEE Sensors Journal.

šŸ’¼ Work & Research:

As a Doctoral candidate, Dr. Siwei Guan is actively engaged in groundbreaking research, including the development of novel anomaly detection techniques using variational autoencoders and temporal neural networks. His work has received significant funding from prestigious institutions, including the National Key Research and Development Program of China and the National Natural Science Foundation of China. Additionally, he contributes to the academic community through peer review activities for esteemed journals such as Exper System with Application and ISA Transactions.

šŸ“Š Funding & Peer Review:

Dr. Siwei Guan has successfully secured funding to support his research endeavors, demonstrating the recognition and significance of his work in the field. Furthermore, his involvement in peer review activities reflects his commitment to advancing the scientific knowledge and contributing to the quality of research publications.

šŸŒŸ Achievements:

Dr. Siwei Guan’s contributions to the field of electronic science and technology have earned him recognition and support from prestigious funding programs and academic journals. With his dedication to innovative research and scholarly pursuits, he continues to make valuable contributions to the advancement of anomaly detection methodologies in multivariate time series data.

Publication Top Notes:

  1. Multivariate time series anomaly detection with variational autoencoder and spatialā€“temporal graph network
    • Published in Computers & Security, April 2024.
  2. Conditional normalizing flow for multivariate time series anomaly detection
    • Published in ISA Transactions, December 2023.
  3. TPAD: Temporal-Pattern-Based Neural Network Model for Anomaly Detection in Multivariate Time Series
    • Published in IEEE Sensors Journal, December 15, 2023.
  4. GTAD: Graph and Temporal Neural Network for Multivariate Time Series Anomaly Detection
    • Published in Entropy, May 2022.