Dr. Vamsi Inturi | Machine Learning | Best Researcher Award

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Dr. Vamsi Inturi | Machine Learning | Best Researcher Award

Dr. Vamsi Inturi, Chaitanya Bharathi Institute of Technology, India

Dr. Vamsi Inturi is an accomplished researcher and academic specializing in Mechanical Engineering, with expertise in fault diagnosis, health monitoring, and digital twin technologies. He earned his Ph.D. from BITS Pilani, focusing on adaptive condition monitoring for wind turbine gearboxes. With experience spanning postdoctoral research at Trinity College Dublin and academic roles in India, he has made significant contributions to machine learning applications in engineering. He has received prestigious awards, including the Best Paper Award at the 43rd International JVE Conference. His research integrates AI and signal processing to enhance predictive maintenance and mechanical system reliability.

Professional Profile:

Google Scholar

Orcid

Scopus

🏆 Suitability for Award 

Dr. Vamsi Inturi is an outstanding candidate for the Best Researcher Award, given his pioneering work in mechanical fault diagnosis, machine learning, and predictive maintenance. His research significantly impacts renewable energy systems, particularly wind turbines, optimizing efficiency and reducing downtime. Recognized with international travel grants, research fellowships, and best paper awards, he has demonstrated academic excellence and innovation. His work in digital twins and signal processing has been published in high-impact journals, reinforcing his status as a leader in mechanical engineering research. His commitment to advancing engineering solutions makes him highly deserving of this prestigious recognition.

🎓 Education

Dr. Vamsi Inturi holds a Ph.D. in Mechanical Engineering from BITS Pilani (2016-2020), where he developed an adaptive condition monitoring scheme for wind turbine gearboxes under the supervision of Prof. Sabareesh G R and Prof. Pavan Kumar P. He earned his M.Tech in Machine Design from JNTU Kakinada (2012-2014), focusing on modeling process parameters in milling aluminum composites. His academic journey began with a Bachelor’s in Mechanical Engineering, followed by extensive research in fault diagnosis and mathematical modeling. His interdisciplinary expertise bridges mechanical systems, AI-driven analytics, and sustainable energy solutions, shaping advancements in mechanical diagnostics.

👨‍🏫 Experience 

Dr. Vamsi Inturi has a diverse academic and research career. He is currently an Assistant Professor at CBIT(A), Hyderabad, specializing in engineering drawing, robotics, and mechanical systems. Previously, he was a Postdoctoral Researcher at Trinity College Dublin, managing the REMOTE-WIND project. He also served as a Research Scholar at BITS Hyderabad, working on mechanical vibrations and fault diagnosis. His teaching experience includes faculty positions at PACEITS and QISIT, mentoring students in mechanical design and computational modeling. With extensive research output in AI-driven diagnostics, he plays a crucial role in advancing predictive maintenance strategies.

🏅 Awards and Honors

Dr. Vamsi Inturi has received multiple accolades for his research excellence. He was awarded the Best Paper Award at the 43rd International JVE Conference (2019) and recognized for outstanding Ph.D. performance (2017-18). As a CSIR Senior Research Fellow (2019-20), he contributed to groundbreaking studies in mechanical diagnostics. He also secured a CSIR International Travel Grant (2019) to present his research globally. Additionally, he was elected a campus-level senate member for Ph.D. programs (2018-20). His expertise has made him a sought-after speaker and session co-chair at international mechanical engineering conferences.

🔍 Research Focus 

Dr. Vamsi Inturi’s research centers on health monitoring, fault diagnosis, and AI-driven mechanical analytics. His work integrates machine learning, signal processing, and digital twin technologies to enhance predictive maintenance in mechanical systems, particularly wind turbines. He specializes in mathematical modeling and deep learning applications for fault detection, helping industries reduce operational risks. His studies on adaptive condition monitoring schemes for gearboxes have led to innovative diagnostic frameworks. His interdisciplinary approach merges mechanical engineering with computational intelligence, making significant contributions to sustainable energy and industrial automation.

📚 Publication Top Notes:

  • Title: Comparison of Condition Monitoring Techniques in Assessing Fault Severity for a Wind Turbine Gearbox Under Non-Stationary Loading
    • Volume: 124
    • Citations: 102
  • Title: Evaluation of Surface Roughness in Incremental Forming Using Image Processing-Based Methods
    • Year: 2020
    • Citations: 68
  • Title: Integrated Condition Monitoring Scheme for Bearing Fault Diagnosis of a Wind Turbine Gearbox
    • Year: 2019
    • Citations: 63
  • Title: Comprehensive Fault Diagnostics of Wind Turbine Gearbox Through Adaptive Condition Monitoring Scheme
    • Year: 2021
    • Citations: 45
  • Title: Optimal Sensor Placement for Identifying Multi-Component Failures in a Wind Turbine Gearbox Using Integrated Condition Monitoring Scheme
    • Year: 2022
    • Citations: 30

 

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

 

Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

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Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

Dr. Satish Mahadevan Srinivasan, Penn State Great Valley , United States.

Dr. Satish Mahadevan Srinivasan is a Tenured Associate Professor of Information Science at Penn State Great Valley, with expertise spanning data mining, machine learning, cybersecurity, and bioinformatics. With a Ph.D. in Information Technology from the University of Nebraska, his research contributions include class-specific motif discovery in protein classification and tools for metagenomic analysis. Dr. Srinivasan’s work merges cutting-edge technologies with practical applications, contributing to bioinformatics, distributed computing, and artificial intelligence. He has a rich academic and professional journey, publishing impactful research and developing transformative software tools. 🌐📊🔬

Publication Profiles

Googlescholar

Education and Experience

Education

  • 🎓 Ph.D. in Information Technology, University of Nebraska, 2010
  • 🎓 M.S. in Industrial Engineering & Management, IIT Kharagpur, 2005
  • 🎓 B.E. in Information Technology, Bharathidasan University, 2001

Experience

  • 📚 Tenured Associate Professor, Penn State Great Valley (2019–Present)
  • 📚 Assistant Professor, Penn State Great Valley (2013–2019)
  • 🔬 Postdoctoral Researcher, Computational Bioinformatics, UNMC (2011–2013)
  • 💻 Postdoctoral Research Assistant, Computer Science, University of Nebraska (2010–2011)
  • 🛠️ Project Assistant, IIT Kharagpur (2001–2005)

Suitability For The Award

Dr. Satish Mahadevan Srinivasan, a Tenured Associate Professor at Penn State, excels in interdisciplinary research spanning data mining, bioinformatics, machine learning, and cybersecurity. His groundbreaking tools like MetaID and Monarch have advanced microbial analysis and software engineering. With impactful publications, innovative solutions, and practical applications, Dr. Srinivasan exemplifies research excellence, making him highly deserving of the Best Researcher Award.

Professional Development

Dr. Srinivasan has developed innovative tools and frameworks, including MetaID for metagenomic studies and Monarch for transforming Java programs for embedded systems. His interdisciplinary research bridges machine learning, predictive analytics, and cybersecurity with bioinformatics, aiding microbial classification and software optimization. By integrating artificial intelligence and distributed computing, he has addressed complex challenges in data science, genomics, and engineering. His professional journey reflects a commitment to cutting-edge technology, impactful research, and knowledge dissemination through teaching and mentorship. 🌟🔍

Research Focus

Dr. Satish Mahadevan Srinivasan’s research focuses on leveraging advanced technologies to address complex problems in data science, bioinformatics, and cybersecurity. His work in data mining and machine learning aims to uncover patterns and develop predictive models for diverse applications. In bioinformatics, he has designed tools like MetaID for microbial classification and motif discovery in protein sequences, contributing to genomics and medical advancements. His expertise extends to cybersecurity, where he explores cryptographic techniques to enhance internet security, and distributed computing, optimizing system performance. Dr. Srinivasan’s interdisciplinary approach bridges artificial intelligence, predictive analytics, and software engineering to create impactful solutions. 🌐🔬📊

Awards and Honors

  • 🏆 Awarded research grants for innovative bioinformatics tools.
  • 📜 Recognized for contributions to cybersecurity and internet authentication.
  • 🌟 Acknowledged as a leading researcher in predictive analytics and machine learning.
  • 📊 Published in high-impact journals like BMC Bioinformatics and BMC Genomics.

Publication Top Notes

  • Effect of negation in sentences on sentiment analysis and polarity detection  – Cited by 93, 2021 📊📚
  • LocSigDB: A database of protein localization signals  – Cited by 49, 2015 🧬📖
  • K-means clustering and principal components analysis of microarray data of L1000 landmark genes– Cited by 46, 2020 🧪📊
  • Mining for class-specific motifs in protein sequence classification – Cited by 29, 2013 🔬📜
  • Web app security: A comparison and categorization of testing frameworks– Cited by 27, 2017 🔒🖥️
  • MetaID: A novel method for identification and quantification of metagenomic samples – Cited by 23, 2013 🌍🔍
  • Sensation seeking and impulsivity as predictors of high-risk sexual behaviours among international travellers – Cited by 21, 2019 ✈️🧠
  • Cybersecurity for AI systems: A survey – Cited by 20, 2023 🤖🔐

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

 

 

 

 

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

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

Conclusion:

Dr. Jianhuan Cen’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.

 

 

 

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

 

 

 

 

Mr. Yan hui Wu | Machine Learning Awards | Best Researcher Award

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Mr. Yan hui Wu | Machine Learning Awards | Best Researcher Award

Mr. Yan hui Wu , Hebei University of Engineering , China

Yanhui Wu is a Senior Engineer at the School of Mining and Surveying Engineering, Hebei University of Engineering. He completed his Ph.D. in Geophysical Exploration and Information Technology at the China University of Mining and Technology (Beijing) in 2023. He also holds an M.Sc. in the same field from the China University of Geosciences (Beijing) and a B.Sc. in Computer Science and Technology from Hebei University of Technology. Wu’s career includes nearly a decade at the Geological Geophysical Center, Hebei Coal Science Research Institute, Jizhong Energy Group, where he served as a Senior Engineer. He has participated in significant research projects, including the Ministry of Science and Technology’s National Key R&D Program on dynamic intelligent detection technology for hidden disaster geological factors in coal mines. Wu’s research has been published in several renowned journals, with notable works on seismic multiattribute machine learning, fault evaluation, and collapse column prediction in coal strata.

Professional Profile:

Orcid

 🎓Education:

Yanhui Wu holds a Ph.D. in Geophysical Exploration and Information Technology from the China University of Mining and Technology (Beijing), which he completed in June 2023. He also earned an M.Sc. in the same field from the China University of Geosciences (Beijing) in June 2010. Additionally, Wu has a B.Sc. in Computer Science and Technology from Hebei University of Technology, which he obtained in June 2007.

 🏢Work Experience:

Yanhui Wu currently serves as a Senior Engineer at the School of Mining and Surveying Engineering, Hebei University of Engineering. Prior to this role, he held a Senior Engineer position at the Geological Geophysical Center of Hebei Coal Science Research Institute, part of the Jizhong Energy Group, from August 2010 to July 2019.

Publication Top Notes:

  • Application of seismic multiattribute machine learning to determine coal strata thickness
    • Published Year: 2021
    • Journal: Journal of Geophysics and Engineering
    • Cited by: 834-844
  • Quantitative Evaluation of Faults by Combined Channel Wave Seismic Transmission-Reflection Detection Method
    • Published Year: 2022
    • Journal: Minerals
    • Cited by: 1022-1032
  • Precise prediction of the collapse column based on channel wave spectral disparity characteristics and velocity tomography imaging
    • Published Year: 2022
    • Journal: Journal of Geophysics and Engineering
    • Cited by: 326-335
  • Application research of combined detection of transmission and reflection slot waves for small structures—Taking Longquan Mining Area in Shanxi as an example
    • Published Year: 2021
    • Journal: Progress in Geophysics
    • Cited by: 1325-1332

Ms. Priyanka | Neuromorphic Computing

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Ms. Priyanka : Leading Researcher in Neuromorphic Computing

Ms. Priyanka, Rajkiya Engineering College, India

👨‍🏫 Ms. Priyanka, a dedicated researcher and educator, is currently immersed in the realm of electronics and semiconductor technology, pursuing a Ph.D. in the Department of Electronics Engineering at NIT Patna. With a Master’s degree in Technology from NIT Rourkela and a Bachelor’s degree from Ajay Kumar Garg Engineering College, Ms. Priyanka boasts an impressive academic journey. With over 6 years of teaching experience, Ms. Priyanka has become a respected figure in the field, holding various positions such as Cultural and Literary Club Coordinator and serving as a Girl Hostel Warden at REC Mainpuri. Notably, Ms. Priyanka has excelled as a Library In-charge for the Department of Applied Sciences and Humanities and as Lab Incharge for Electronics, ADE, Communication, and Microprocessor Lab at Rajkiya Engineering College, Mainpuri. 🎓🔬

🌟 In addition to academic and administrative roles, Ms. Priyanka has received numerous accolades, including the prestigious Best Young Scientist Award at the “17th International Conference on Optics, Lasers & Photonics” in 2021. With a passion for knowledge dissemination, Dr. [Name] has been recognized as a distinguished speaker at five international conferences and has earned NPTEL Online Certifications in CMOS Digital VLSI Design, Fundamentals of Semiconductor Devices, and Microelectronics Devices To Circuits. This accomplished individual also holds a Translator Certificate from IIT Delhi for translating course files into Hindi. The recipient of the Institute Medal for Branch Topper at NIT Rourkela, Ms. Priyanka continues to contribute significantly to the fields of Leaky Integrate and Fire Neuron, Neuromorphic Computing, VLSI Design, and more. 🎓💡🔬

Profiles : Scopus 

🏆 Awards:

  • 🔬 Best Young Scientist Award in “17th International Conference on Optics, Lasers & Photonics” (June 26-27, 2021)
  • 🌍 Best Speaker Award for completing 5 International conferences
  • 💬 NPTEL Translator Certificate (Hindi) by IIT Delhi for Electrical Machines course (2020)
  • 💻 NPTEL Online Certification (Elite+Silver: Top 1%) in CMOS Digital VLSI Design (Feb-April 2019)
  • 🏆 NPTEL Online Certification (Elite+Silver: Top 1%) in Fundamentals of Semiconductor Devices (Jan-April 2019)
  • 🌐 NPTEL Online Certification (Elite+Silver) in Microelectronics Devices To Circuits (July-Oct 2019)
  • 🎓 Institute Medal for Branch Topper at NIT Rourkela (Jan 21, 2017)
  • 🥇 Certificate of Excellence for Holding First Position in M.Tech in Electrical Engineering at NIT Rourkela (Jan 21, 2017)

🌐 Research Interests : 📖

  • 🔍 Leaky Integrate and Fire Neuron
  • 💻 Neuromorphic Computing
  • 🔬 Nano Electronics
  • 🛠️ VLSI Design
  • 📏 Semiconductor Devices
  • ⚙️ Microelectronics
  • ☀️ Perovskite Solar Cells
  • 🚇 Tunnel Field Effect Transistors (TFET)
  • 🔄 Ferro TFET
  • 🚫 Junctionless and Doping-less MOS Devices
  • 🔄 Charge Plasma Bipolar Devices
  • 🔧 FinFETs

📚 Publication Impact and Citations:

Scopus Metrics:

  • 📝 Publications: 31 documents indexed in Scopus.
  • 📊 Citations: A total of 88 citations for his publications, reflecting the widespread impact and recognition of Ms. Priyanka’s research within the academic community.
Publications ( Top Note ) :

1.  Emulation of Neuro-mimetic Dynamics via GaSb/Si Heterojunction V-DGTFET Leaky-Integrate-Fire Silicon Neuron

2.  Analysis of full reference quality metrics for image transmission over a MIMO OWC channel under varying turbulent conditions

3.  Design and Simulation-Based Analysis of Triple Metal Gate with Ferroelectric-SiGe Heterojunction Based Vertical TFET for Performance Enhancement

4.  Simulation Study of Linearly Graded Binary Metal Alloy Pα Q1-α Gate TFET Device for Realization of Boolean Functions

5.  Quality assessment for terrestrial digital video broadcast over optical wireless communication-passive optical network under moderately turbulent regime with spatial diversity

6.  Design of electro-optic Mach–Zehnder interferometer based all-optical binary half adder and half subtractor

7.  Modeling of intensity fluctuations in the turbid underwater wireless optical communication links

8.  Performance estimation of image transmission in indoor visible light communication system based on variable pulse position modulation

9.  Statistical channel model to characterize turbulence-induced fluctuations in the underwater wireless optical communication links

10.  Modeling of laser beam deviation and estimation of link outage due to the presence of air bubbles in the underwater wireless optical communication system