Cybersecurity, previously at University of Central Florida in USA and now at Tikrit University in Iraq

Qutaiba Abdullah Hasan Alasad is an Associate Professor and Head of the Department of Control and Computer Engineering at the University of Tikrit, Iraq. With a Ph.D. in Computer Engineering from the University of Central Florida (UCF), USA, he has developed expertise in hardware security, particularly in the areas of logic encryption, obfuscation techniques, and secure design for emerging devices. His research work focuses on enhancing hardware protection, preventing side-channel attacks, and leveraging memory computing for secure and high-performance systems. He has also been involved in various presentations and has earned several prestigious awards for his contributions to computer engineering and cybersecurity. 📚🔒

Publication Profile

Google Scholar

Education

Dr. Alasad completed his Ph.D. in Computer Engineering from the University of Central Florida (UCF) in 2020, with a perfect GPA of 4.0/4.0. His dissertation, titled “Provably Trustworthy and Secure Hardware Design with Low Overhead,” was supervised by Prof. Yuan Jiann-Shiun. He also holds an M.Sc. in Computer Engineering from the University of Mosul, Iraq, where he designed a math pipeline processor using VHDL and implemented it on Spartan-3E. 🎓🇮🇶

Experience

Dr. Alasad has served in various prestigious positions, including the Head of the Department at the University of Tikrit’s College of Petroleum and Minerals Engineering and Dean of the College of Petroleum Systems Control Engineering. He was also involved in several roles at the University of Central Florida, where he worked under the supervision of Prof. Jiann-Shiun Yuan. His vast experience spans over teaching, research, and administrative roles. 💼👨‍🏫

Awards and Honors

Dr. Alasad has received several notable recognitions, including a Travel Award from the ICCD Conference in 2017 and a complimentary annual membership from Gabriele Kotsis, President of the ACM journal, in 2020. He has presented his research at various symposiums, covering topics such as Internet of Things (IoT) applications and power electronics systems simulation. 🏅🌍

Research Focus

Dr. Alasad’s research interests are centered around hardware security, particularly logic encryption and obfuscation techniques, side-channel attack prevention, and the application of emerging devices to enhance hardware security. He is also focused on designing secure memory systems using ReRAM and creating high-performance machine learning accelerators. Additionally, his work on big data security and cybersecurity protection based on machine learning is highly impactful in the domain. 🔐💻

Conclusion

Qutaiba Alasad’s interdisciplinary expertise and contributions to hardware security, especially in the realm of logic encryption and emerging devices, position him as a leader in the field. His academic achievements, coupled with his extensive work in cybersecurity, make him a prominent figure in the engineering community. 🏆👨‍💻

Publications

Design a Pipelined Math Processor, Doubling Its Speed and Implementing It on FPGA

Al-Rafidain Engineering Journal (AREJ), Volume 22, Issue 4, Pages 131-148, 2014

Cited by: 10+

E2LEMI: Energy-Efficient Logic Encryption Using Multiplexer Insertion

Electronics, vol. 6, issue 1, 2017

Cited by: 50+

Logic Locking Using Hybrid CMOS and Emerging SiNW FETs

Electronics, vol. 6, issue 3, 2017

Cited by: 30+

Ultra-Low-Power Design and Hardware Security Using Emerging Technologies for Internet of Things

Electronics, vol. 6, issue 3, 2017

Cited by: 40+

Logic Obfuscation against IC Reverse Engineering Attacks with Low Overhead

ACM Trans. TODAES, 2020

Cited by: 75+

Resilient and Secure Hardware Devices Using ASL

ACM journal on emerging technologies in computing systems, 2021

Cited by: 20+

Multi-Tier 3D IC Physical Design with Analytical Quadratic Partitioning Algorithm Using 2D P&R Tool

Electronics, 2021

Cited by: 15+

Mitigation of Black-Box Attacks on Intrusion Detection Systems-Based ML

MDPI Computers, 2022

Cited by: 25+

IDRISS DAGAL | Electrical Engineering | Best Researcher Award

Posted on 27/12/202427/12/2024 by sciencefather

Dr. IDRISS DAGAL | Electrical Engineering | Best Researcher Award

Assistant Professor, Istanbul Beykent University, Turkey

Dr. Idriss Dagal, an Assistant Professor at Istanbul Beykent University, is a researcher and engineer from Chad specializing in Electrical Engineering, Renewable Energy, and Artificial Intelligence. With a career spanning over a decade, he has worked in various roles, including Aircraft Engineer and Lecturer, and has contributed extensively to the field of electrical systems, power electronics, and optimization algorithms. His academic journey includes a Ph.D. from Yıldız Technical University, Istanbul, Turkey, where he also completed his MSc in Avionics Engineering. Dr. Dagal has authored over 30 publications and is an active reviewer for renowned journals. 🌍💡

Publication Profile

ORCID

Education:

Dr. Dagal holds a Bachelor of Science (B.S.) degree in Industrial and Maintenance Engineering from Mongo Polytechnic University (Chad, 2006), a Master of Science (M.Sc.) in Aviation Engineering from Ethiopian Airlines Aviation School (Ethiopia, 2010), and a Ph.D. in Electrical Engineering from Yıldız Technical University (Turkey, 2022). He is currently pursuing a second M.Sc. in Avionics Engineering at Yıldız Technical University. 🎓📚

Experience:

Dr. Dagal’s professional experience spans multiple countries and roles, including serving as an Aircraft Maintenance Engineer in Chad, a Lecturer at various institutions in Chad, and a Sales Engineer in Turkey. Since 2024, he has been serving as an Assistant Professor at Istanbul Beykent University, Turkey, specializing in electrical engineering, renewable energy, and avionics. 🛠️✈️

Awards and Honors:

Dr. Dagal has received several prestigious awards, including the Chad’s Government National Scholarship (2003), Ethiopian Airlines Aviation School International Scholarship (2008), Turkish Government International Scholarship (2015), Young Research Scholarship Award for Eurasia Research (2019), and the Leadership Skills African Civic Engagement Academy (2022). 🏆🌟

Research Focus:

Dr. Dagal’s research interests are centered on optimization algorithms, artificial intelligence, renewable energy systems, power electronics, and aircraft control systems. His doctoral research focused on optimizing photovoltaic battery charging systems using hybrid particle swarm-based algorithms. He has a strong background in developing control mechanisms for sustainable energy systems and dynamic systems in aviation. 🔋🔧🚀

Conclusion:

Dr. Idriss Dagal is an accomplished academic and researcher who combines his expertise in electrical and aerospace engineering with a deep commitment to renewable energy and technology optimization. His interdisciplinary work continues to contribute to advancements in energy systems, aircraft control, and smart technologies. 🌱💻

Publications

Energy transfer from PV panel to Battery via Buck-Boost Converter, International Journal of Technology and Science, Vol. 5, Issue 3, pp. 46-60, 26 November 2019. DOI

Improved salp swarm algorithm based on particle swarm optimization for maximum power point tracking of optimal photovoltaic systems, International Journal of Energy Research, 2022; 1-18. DOI: 10.1002/er.7753. Impact Factor: 4.3, Q1.

MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization (PSOSSO) algorithm for battery charging through Simulink, Scientific Reports Journal, 2022; 12:2664. DOI. Impact Factor: 3.8, Q1.

A Novel Hybrid Series Salp Particle Swarm Optimization (SSPSO) for Standalone Battery Charging Applications, Ain Shams Engineering Journal, 2022; 13:10174. DOI. Impact Factor: 6, Q1.

Improved Particle Swarm Optimization based Buck-Boost converter (IPSOBBC) for Photovoltaic System Application, Recent Advances in Science & Engineering (RASE), 2022.

Transformer rail-tapped buck-boost converter design-based feedback controller for battery charging systems, Energy Storage Journal, 2022; e414, DOI. ESCI.

Secure and Optimized Satellite Image Sharing based on Chaotic eπ Map and Racah Moments” Expert Systems with Applications, Volume 236, February 2024, 121247, DOI: 10.1016/j.eswa.2023.121247. Impact Factor: 7.5, Q1.

Hybrid SSA-PSO-based intelligent direct sliding-mode control for extracting maximum photovoltaic output power and regulating the DC-bus voltage, International Journal of Hydrogen Energy, Volume 51, Part C, 2 January 2024, Pages 348-370, DOI. Impact Factor: 8.1, Q1.

An Improved Constant Current Step-based Grey Wolf Optimization Algorithm for Photovoltaic Systems, Journal of Intelligent & Fuzzy Systems, 2024, DOI. Impact Factor: 1.7, Q3.

A Modified Multi-Stepped Constant Current Based on Grey Wolf Algorithm for Photovoltaics Applications, Springer, Electrical Engineering, 2024, DOI. Impact Factor: 1.6, Q3.

Jian Sun | Smart Grid Control | Best Researcher Award

Posted on 27/12/202427/12/2024 by sciencefather

Assoc. Prof. Dr. Jian Sun | Smart Grid Control | Best Researcher Award

Associate Professor, Southwest University, China

Jian Sun is an Associate Professor in the School of Electronic and Information Engineering at Southwest University, Chongqing, China. With a strong academic and research background in automation and electrical engineering, his work focuses on control systems, reinforcement learning, and grid frequency regulation. Over the years, he has made significant contributions to the field through his publications and innovative approaches to tackling complex power grid challenges. 📚🔬

Publication Profile

ORCID

Education

Jian Sun earned his Ph.D. in Automation from Chongqing University in December 2014. He also completed a visiting Ph.D. program at the University of Wisconsin-Madison, USA, in 2014, specializing in Electrical and Computer Engineering. Prior to his doctoral studies, he obtained a Master’s degree in Automation and a Bachelor’s degree in the same field from Chongqing University. 🎓🌍

Experience

Jian Sun has extensive academic and research experience, currently serving as an Associate Professor at Southwest University. His expertise spans areas like frequency regulation in power systems, energy storage systems, and adaptive control techniques. He has published numerous papers in prestigious journals and has contributed to several interdisciplinary research projects. His work often combines advanced reinforcement learning techniques with cyber-physical systems. 💼🔧

Awards and Honors

Throughout his career, Jian Sun has received recognition for his outstanding research and contributions to the field. His work has been widely cited and appreciated by both academic and industry professionals. He continues to push the boundaries of research in smart grids, energy management, and reinforcement learning. 🏆📈

Research Focus

Jian Sun’s research focuses on developing adaptive and resilient control strategies for smart grids, particularly in the context of frequency regulation. His work includes the integration of Vehicle-to-Grid (V2G) technologies, reinforcement learning for DoS attack resilience, and advanced control systems for energy-efficient power grids. He aims to improve the stability and security of power systems in the face of cyber threats and dynamic load conditions. ⚡🧠

Conclusion

Jian Sun’s academic journey and research have contributed to advancements in smart grid technology, power system regulation, and control theory. His continued dedication to addressing critical challenges in energy systems positions him as a leading figure in his field. His research aims to make power systems smarter, more efficient, and resilient to emerging threats. 🌐🔋

Publications

Load Forecasting for Commercial Buildings Using BiLSTM–Transformer Network and Cyber–Physical Cognitive Control Systems
Published Year: 2024
Journal: Symmetry
Cited by: Crossref

An Adaptive V2G Capacity-Based Frequency Regulation Scheme With Integral Reinforcement Learning Against DoS Attacks
Published Year: 2024
Journal: IEEE Transactions on Smart Grid
Cited by: Crossref

Cooperative Grid Frequency Control Under Asymmetric V2G Capacity via Switched Integral Reinforcement Learning
Published Year: 2024
Journal: International Journal of Electrical Power & Energy Systems
Cited by: Crossref

Resilient Frequency Regulation for DoS Attack Intensity Adaptation via Predictive Reinforcement V2G Control Learning
Published Year: 2024
Journal: IEEE Transactions on Smart Grid
Cited by: Crossref

Safe Online Integral Reinforcement Learning for Control Systems via Controller Decomposition
Published Year: 2023
Journal: Arabian Journal for Science and Engineering
Cited by: Crossref

A DoS Attack-Resilient Grid Frequency Regulation Scheme via Adaptive V2G Capacity-Based Integral Sliding Mode Control
Published Year: 2023
Journal: IEEE Transactions on Smart Grid
Cited by: Crossref

A DoS Attack Intensity-Aware Adaptive Critic Design of Frequency Regulation for EV-Integrated Power Grids
Published Year: 2023
Journal: International Journal of Electrical Power & Energy Systems
Cited by: Crossref

Structural Scheduling of Transient Control Under Energy Storage Systems by Sparse-Promoting Reinforcement Learning
Published Year: 2022
Journal: IEEE Transactions on Industrial Informatics
Cited by: Crossref

A Sparse Neural Network-Based Control Structure Optimization Game under DoS Attacks for DES Frequency Regulation of Power Grid
Published Year: 2019
Journal: Applied Sciences
Cited by: Crossref

A Stable Distributed Neural Controller for Physically Coupled Networked Discrete-Time System via Online Reinforcement Learning
Published Year: 2018
Journal: Complexity
Cited by: Crossref

Frequency Regulation of Power Systems with Self-Triggered Control under the Consideration of Communication Costs
Published Year: 2017
Journal: Applied Sciences
Cited by: Crossref

Akbar Rezaei | Fuzzy Mathematics | Best Researcher Award

Posted on 27/12/202427/12/2024 by sciencefather

Assoc. Prof. Dr. Akbar Rezaei | Fuzzy Mathematics | Best Researcher Award

Associate Professor of Mathematics, Payame Noor University, Iran

Dr. Akbar Rezaei is an Associate Professor in the Department of Mathematics at Payame Noor University, Kerman, Iran. He is an expert in algebraic structures, hyperstructure theory, fuzzy sets, and neutrosophic science. With over a decade of research experience, Dr. Rezaei has made significant contributions to the field of pure mathematics, particularly focusing on BE-algebras and related areas. His academic journey is complemented by a number of impactful publications, making him a respected figure in his field. 📚🔬

Publication Profile

Google Scholar

Education

Dr. Rezaei earned his Ph.D. in Pure Mathematics in 2014 from Payame Noor University (PNU), under the supervision of renowned professors Dr. Rajab Ali Borzooei, Dr. Arsham Borumand Saeid, and Dr. Reza Ameri. His doctoral thesis was titled Topics in BE-algebras, exploring the theoretical aspects of algebraic structures and their applications. 🎓🔍

Experience

Dr. Rezaei has been an Associate Professor at Payame Noor University, where he has been actively involved in teaching, supervising graduate students, and conducting research. His research experience includes a deep exploration of fuzzy logic, hyper algebras, and the application of neutrosophic science to algebraic structures. 🏫👨‍🏫

Awards and Honors

Throughout his career, Dr. Rezaei has been recognized for his contributions to the field of mathematics. He has earned awards and honors for his research and teaching, making him a prominent figure in Iranian academic circles. 🏆🎖

Research Focus

Dr. Rezaei’s research primarily focuses on algebraic structures, hyperstructure theory, fuzzy sets, and neutrosophic science. His work on BE-algebras and CI-algebras, particularly in the areas of fuzzy sub-algebras and fuzzy congruence relations, has gained attention and has contributed significantly to advancements in these fields. His interest in the application of fuzzy logic in algebraic structures continues to shape his research direction. 🔢📊

Conclusion

Dr. Akbar Rezaei is a dedicated academic and researcher whose work in pure mathematics, particularly in the field of algebraic structures and fuzzy sets, has made a lasting impact. His contributions continue to shape mathematical research in Iran and beyond, and his passion for teaching and advancing knowledge in the field of mathematics remains strong. 👏💡

Publications

A. Rezaei and A. Borumand Saeid, On Fuzzy sub-algebras of BE-algebras, Afrika Matematika, Vol. 22, No. 2, (2011), pp. 115-127.

A. Rezaei and A. Borumand Saeid, Fuzzy Congruence Relations in CI-algebras, Neural Comput & Applic, Vol. 21, Issue 1 (2012), pp. 319-328.

A. Rezaei and A. Borumand Saeid, Some results in BE-algebras, Analele Universitatii Oradea Fasc. Matematica, Tom XIX (2012), pp. 33-44.

A. Rezaei and A. Borumand Saeid, N sub-algebras and N-Filters in CI-algebras, Scientific Studies and Research. Series Mathematics and Informatics, Vol. 22, No. 1 (2012), pp. 103-116.

A. Rezaei and A. Borumand Saeid, Quotient CI-algebra, Bulletin of the Transilvania University of Brasov, Vol. 5(54), No. 2, (2012), Series III: Mathematics, Informatics, Physics, pp. 1-8.

A. Rezaei and A. Borumand Saeid, Commutative ideals in BE-algebras, Kyungpook Math. J, Vol. 52, No. 3, (2012), pp. 483-494.

A. Borumand Saeid and A. Rezaei, Intuitionistic (T, S)-fuzzy CI-algebras, Computers and Mathematics with Applications, Vol. 63 (2012), pp. 158-166.

A. Rezaei, A. Borumand Saeid, Generalized Fuzzy Filters (Ideals) of BEAlgebras, Journal of Uncertain Systems, Vol.7, No. 2 (2013), pp. 152-160.

A. Borumand Saeid, A. Rezaei and R. A. Borzooei, Some Types of Filters in BE-algebras, Mathematics in Computer Science, Vol. 7, No. 3, (2013), pp. 341-352.

A. Borumand Saeid and A. Rezaei, Smarandache N-Structure on CI-algebras, Results in Mathematics, Vol. 63, No. 1-2 (2013), pp. 209-219.

Michael Ineh | Differential Equations | Best Researcher Award

Posted on 27/12/202427/12/2024 by sciencefather

Dr. Michael Ineh | Differential Equations | Best Researcher Award

Department of Mathematics and Computer Science, Faculty of Natural and Applied Sciences, Ritman University, Ikot Ekpene, Akwa Ibom State, Nigeria.

Dr. Michael P. Ineh (also known as Dr. Ineh, M.P) is a distinguished academic from Nigeria specializing in Differential Equations, Dynamic Equations on Time Scale, and Lyapunov Stability Theory. He is currently serving as a Lecturer in Mathematics and Computer Science at Ritman University, Ikot Ekpene, Akwa Ibom State, since February 2022. Dr. Ineh is passionate about advancing mathematical theories, particularly in the areas of stability and differential equations, and has contributed significantly to research in fractional calculus and time-scale dynamical systems. 🌍📚

Publication Profile

ORCID

Education

Dr. Ineh’s educational journey is marked by a robust foundation in mathematics. He is currently pursuing a PhD in Differential Equations, with a focus on stability theories. He holds a Master’s degree (MSc) in Differential Equations (2021) from the University of Uyo and a Bachelor’s degree (B.Sc) in Mathematics (2015) from Michael Okpara University, Umudike. Additionally, he is pursuing a Post Graduate Diploma in Education (PGDE) from the National Teachers’ Institute, Kaduna, which will enhance his teaching expertise. 🎓📖

Experience

Dr. Ineh has built an impressive career in academia, having worked as a lecturer at Ritman University since 2022, where he imparts knowledge in mathematics and computer science. His earlier educational journey at institutions such as Akwa Ibom State University and the University of Uyo further solidified his academic foundation. His teaching methods are centered on cultivating a deeper understanding of mathematics, with an emphasis on applying abstract concepts to real-world challenges. 🏫👨‍🏫

Awards and Honors

Dr. Ineh’s commitment to excellence has earned him several academic accolades, including recognition for his contributions to the study of Lyapunov Stability and time-scale differential equations. He has been acknowledged for his groundbreaking research in the realm of mathematical physics, where his work on the stability of fractional differential equations is of considerable importance. 🎖️🏆

Research Focus

Dr. Ineh’s primary research interests are in the fields of Differential Equations, Dynamic Equations on Time Scale, and Lyapunov Stability Theory. His work seeks to expand the understanding of fractional dynamics and their applications in real-world systems, including the stability analysis of nonlinear impulsive systems. His recent publications have made substantial contributions to the mathematical community, particularly in the study of fractional differential equations and dynamic systems. 📊🔬

Conclusion

With a passion for advancing mathematical knowledge and a commitment to education, Dr. Michael P. Ineh is a notable figure in the field of mathematics. His research is advancing the study of dynamic equations and stability theory, with applications in a variety of scientific disciplines. As an educator, he continues to inspire and shape the future of students in mathematics and computer science. 🌟📈

Publications

A Novel Lyapunov Asymptotic Eventual Stability Approach for Nonlinear Impulsive Caputo Fractional Differential Equations

Journal: AppliedMath

DOI: 10.3390/appliedmath4040085

Cited By: Link to citations 📜

On the Novel Auxiliary Lyapunov Function and Uniform Asymptotic Practical Stability of Nonlinear Impulsive Caputo Fractional Differential Equations via New Modeled Generalized Dini Derivative

Journal: African Journal of Mathematics and Statistics Studies

DOI: 10.52589/ajmss-vunaiobc

Cited By: Link to citations 📚

LYAPUNOV UNIFORM ASYMPTOTIC STABILITY OF CAPUTO FRACTIONAL DYNAMIC EQUATIONS ON TIME SCALE USING A GENERALIZED DERIVATIVE

Journal: The Transactions of the Nigerian Association of Mathematical Physics

DOI: 10.60787/TNAMP.V20.431

Cited By: Link to citations

A Novel Approach to Lyapunov Stability of Caputo Fractional Dynamic Equations on Time Scale Using a New Generalized Derivative

Journal: AIMS Mathematics

DOI: 10.3934/math.20241639

Cited By: Link to citations

Results on Existence and Uniqueness of Solutions of Dynamic Equations on Time Scale via Generalized Ordinary Differential Equations

Journal: International Journal of Applied Mathematics

DOI: 10.12732/ijam.v37i1.1

Cited By: Link to citations

Approximating the Solution of a Nonlinear Delay Integral Equation by an Efficient Iterative Algorithm in Hyperbolic Spaces

Journal: International Journal of Statistics and Applied Mathematics

DOI: 10.22271/maths.2023.v8.i3b.1000

Cited By: Link to citations

On a Faster Iterative Method for Solving Nonlinear Fractional Integro-Differential Equations with Impulsive and Integral Conditions

Journal: Palestine Journal of Mathematics

Cited By: Link to citations

Variational Stability Results of Dynamic Equations on Time-Scales Using Generalized Ordinary Differential Equations

Journal: World Journal of Applied Science & Technology

Cited By: Link to citations

On Lyapunov Stability of Caputo Fractional Dynamic Equations on Time Scale Using a New Generalized Derivative (Working Paper)

DOI: 10.20944/preprints202406.2042.v1

Cited By: Link to citations

Sandra Filipe | Management | Excellence in Research

Posted on 20/12/202420/12/2024 by sciencefather

Prof. Sandra Filipe | Management | Excellence in Research

Professor, University of Aveiro, Portugal

🌟 Sandra Sarabando Filipe is a distinguished professor at the University of Aveiro, Portugal. With over two decades of academic excellence, she has made remarkable contributions in the fields of marketing, consumer behavior, and sustainability. Holding a Ph.D. in Marketing, she is also an editor, conference chair, and a key researcher in innovation-driven projects. Sandra has been instrumental in guiding numerous postgraduate students and fostering impactful academic collaborations. 🌱📘

Publication Profile

ORCID

Education:

🎓 Sandra holds a Ph.D. in Marketing (2016) and a Master’s in Management with a double specialization in Marketing and Strategy (2000) from ISCTE Business School – University Institute of Lisbon. She earned her Management degree in 1996 from the Faculty of Economics – University of Coimbra. 📖✨

Experience:

🏫 Sandra has been a Coordinating Professor at the University of Aveiro since 2023. Previously, she served as an Adjunct Professor (2002–2023) and an Assistant Professor (1999–2002). Over her career, she has taught diverse courses in marketing and business development, supervised 30+ MSc dissertations, and guided two Ph.D. theses. Her expertise spans digital marketing, sustainability education, and relationship marketing. 🌍📊

Research Interests:

🔬 Sandra’s research focuses on consumer behavior, relationship marketing, corporate social responsibility, sustainability marketing, digital marketing, and tourism. She is passionate about exploring innovative educational practices and enhancing knowledge in marketing strategies with social and environmental impact. 🌟🌱

Awards:

🏆 Sandra has achieved notable recognition as a leader in education and research. Her ongoing work in marketing innovation and community impact projects highlights her commitment to excellence. She is also a recognized editor and chair for international conferences, showcasing her leadership in academia. 🌍🎉

Publications :

“From Olive Oil Lovers to Mediterranean Diet Lifestyle Followers: Consumption Pattern Segmentation in the Portuguese Context”
Nutrients, 2024.
DOI: 10.3390/nu16234235

“Higher Education for Good: Case of Three Courses at Universidade de Aveiro”
Conference Paper, 2024.
DOI: 10.21125/edulearn.2024.1115

“Higher Education for Good: PBL Practices with Positive Impact on the Community”
Conference Paper, 2023.
DOI: 10.21125/edulearn.2023.0987

“O amor à marca Disney: Realidade ou Utopia?”
7th International Conference on Innovation and Entrepreneurship in Marketing and Consumer Behaviour, 2023.
Source: cv-prod-id-3788838

Ms. Hina Magsi | Signal Processing | Best Researcher Award

Posted on 20/12/202420/12/2024 by sciencefather

Ms. Hina Magsi | Signal Processing | Best Researcher Award

PhD Scholar, Sukkur IBA University, Pakistan

Engr. Hina Magsi is a dedicated lecturer at Mehran University of Engineering & Technology, Khairpur, with over four years of experience in research and teaching in the fields of telecommunication, electronics, embedded systems, AI, and machine learning 📚. She is passionate about advancing the education of her students and has co-supervised several impactful projects, including an IoT-based flood monitoring system 🌊, wireless electric vehicle charging 🚗, and a real-time drowsiness detection system 🛣️. Hina has a strong academic background and actively contributes to research in satellite communication and space weather, with a focus on improving navigation systems using adaptive algorithms 📡.

Publication Profile

ORCID

Education

Hina Magsi holds a PhD in Electrical Engineering (Signal Processing) from Sukkur IBA University, where she earned a CGPA of 3.57 🎓. She completed her M.E. in Electronics and Communication from the same university with a CGPA of 3.47, and her B.E. in Telecommunication Engineering from Mehran University of Engineering & Technology with an impressive CGPA of 3.72. Her thesis topics include MIMO CO-OFDM in Free Space Optical Communication and Received Signal Quality Monitoring (RSQM) algorithms for improved navigation 🧠.

Experience

With diverse experience, Engr. Magsi has worked as a lecturer at Mehran University of Engineering & Technology, delivering courses across various electronic engineering subjects. She previously served as a research associate at Sukkur IBA University, focusing on satellite communication and space weather. Engr. Magsi also worked as a research assistant in bio-sensing, developing adaptive battery-aware methods for smart healthcare systems 💡. Early in her career, she gained practical experience at PTCL and SAKI Institute Sukkur.

Research Interests

Her primary research interests include satellite communication, signal processing, IoT applications, real-time monitoring systems, AI and machine learning in engineering, and adaptive algorithms for improved navigation accuracy 📡🔍. She is particularly interested in applying these technologies to healthcare and transportation systems 🚑🚗.

Awards

Engr. Magsi has received several prestigious awards, including merit-based scholarships at Mehran University and Sukkur IBA University 🎓, as well as the International Merit Scholarship for her Ph.D. at Sukkur IBA University. She has also received funding for research projects from HEC NRPU and has been recognized for her contributions to education and research 🌟.

Publications

Accurate Monitoring and Timely Prediction of Ionospheric Scintillation Using Support Vector Machine
Improved Navigation Based on Received Signal Quality Monitoring (RSQM)
Adaptive Data Length Method for GPS Signal Acquisition in Weak to Strong Fading Conditions
Decentralized Energy Efficient Model for Data Transmission in IoT-based Healthcare System
A Novel Adaptive Battery-Aware Algorithm for Data Transmission in IoT-based Healthcare Applications

Kevin Moreno Gata | Architecture | Best Researcher Award

Posted on 20/12/202420/12/2024 by sciencefather

Mr. Kevin Moreno Gata | Architecture | Best Researcher Award

Research Associate, RWTH Aachen University, Germany

Kevin Moreno Gata is a research associate at RWTH Aachen University, Germany, specializing in structures and structural design. He holds extensive experience in developing innovative and sustainable building systems, particularly using naturally grown timber as a basis for load-bearing structures. With a strong foundation in both theoretical and applied research, Kevin contributes significantly to the advancement of engineering in the context of sustainable architecture and materials. 🌱🏗️

Publication Profile

ORCID

Education:

Kevin earned his academic credentials in the field of structural engineering, focusing on sustainable materials and construction practices. His academic pursuits have been complemented by his hands-on involvement in advanced research projects, contributing to the design and structural analysis of timber-based constructions. 🎓🔧

Experience:

Currently, Kevin is working as a research associate at RWTH Aachen University, Germany, in the Chair of Structures and Structural Design. He is involved in various groundbreaking projects that explore innovative and sustainable ways of utilizing naturally grown timber in construction. His professional experience includes securing prestigious grants and collaborating with international research teams. 💼🌍

Research Interests:

Kevin’s research is primarily focused on the structural analysis, design, and simulation of naturally grown timber elements for use in load-bearing building structures. His interests include circular design in forest construction, the use of advanced computational methods for timber structures, and the development of new techniques for sustainable and environmentally friendly architecture. 🌳📐

Awards:

Kevin has received research funding for projects such as “Naturally grown timber elements as basis for load-bearing building structures” from the Deutsche Forschungsgemeinschaft, and the Zukunft Bau Pop-up Campus Projekt grant from the Bundesinstitut für Bau-, Stadt- und Raumforschung (BBSR). His innovative research continues to gain recognition and shape the future of sustainable building practices. 🏆🌍

Publications:

Function-Oriented Applicability Evaluation of Technical Folding Based on Expert Knowledge
Published: 2024-12-08
Journal: Applied Sciences
Read more here
Cited by: 5

Building with Naturally Grown Timber: Circular Design in Forest Construction – A Pedestrian Bridge Case Study
Published: 2024-08-26
Journal: Proceedings of the IASS 2024 Symposium Redefining the Art of Structural Design
Read more here
Cited by: 10

Geometrical Analysis of Naturally Grown Timber for the Design of Load-Bearing Structures
Published: 2024-06-30
Preprint: Read more here
Cited by: 3

Generalised Scaled Boundary Isogeometric Analysis–A Method for Structural Analysis of Naturally Shaped Timber Structures
Published: 2024
Journal: Wood Material Science and Engineering
Read more here
Cited by: 15

Md. Emran Biswas | Data science | Best Researcher Award

Posted on 20/12/202420/12/2024 by sciencefather

Mr. Md. Emran Biswas | Data science | Best Researcher Award

Research Assistant, Hajee Mohammad Danesh Science and Technology University, Bangladesh

🌟 Md. Emran Biswas, hailing from Dinajpur, Bangladesh, is a passionate researcher and technologist specializing in machine learning, optimization algorithms, and their societal applications. He has actively contributed to predictive analysis, bioinformatics-based drug discovery, and developing AI solutions for global good. As a skilled programmer and researcher, Emran’s work has earned recognition through multiple publications, accolades, and groundbreaking projects in his field.

Publication Profile

Scopus

Education

🎓 Md. Emran Biswas completed his B.Sc. in Electronics and Communication Engineering at Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur, Bangladesh, from March 2019 to November 2024, with an impressive CGPA of 3.412/4.00. His academic journey is marked by a focus on deep learning, predictive modeling, and optimization algorithms.

Experience

💼 Emran served as a Research Assistant at Petarhub and DIOT Lab, HSTU, contributing to machine learning, predictive modeling, and optimization projects. His notable achievements include developing the ApexBoost Regression model, managing large datasets, and publishing impactful research in reputed journals like IEEE and Electronics.

Research Interests

🔍 Emran’s research focuses on machine learning, optimization algorithms, and their transformative applications in areas like bioinformatics-based drug discovery, predictive analysis, and societal challenges. His work aligns with the vision of ‘AI for Good,’ driving impactful innovation.

Awards

🏆 Emran has earned recognition for his innovative projects, including First Runner-Up at the Project Exhibition 2022 for his “Face Detection-Based Attendance System” and Second Runner-Up in 2023 for his “AI-Based Health Checking System.” These awards reflect his technical expertise and creative problem-solving skills.

Publications

Machine Learning Approach to Estimate Requirements for Target Productivity of Garments Employees. IEEE ICEEICT 2024 (Cited by: 5)

An Effective Data-Driven Approach to Predict Bike Rental Demand. Google Scholar (Cited by: 12)

Spatio-Temporal Feature Engineering and Selection-Based Flight Arrival Delay Prediction Using Deep Feedforward Regression Network. Electronics, 13(24), p.4910 (Cited by: 9)

Pardis Roozkhosh | additive manufacturing | Best Researcher Award

Posted on 20/12/202420/12/2024 by sciencefather

Dr. Pardis Roozkhosh | additive manufacturing | Best Researcher Award

Lecturer, Ferdowsi University of Mashhad, Iran

🎓 Pardis Roozkhosh is a dedicated researcher and academic currently affiliated with the Economic and Administrative Sciences Faculty at Ferdowsi University of Mashhad, Iran. Her work spans the intersection of management science, optimization models, and data-driven decision-making. Pardis is passionate about developing innovative solutions for complex engineering and management problems, contributing significantly to the fields of system assurance and financial prediction. 📚✨

Publication Profile

Scopus

Education

🎓 Pardis Roozkhosh has been pursuing her academic journey at Ferdowsi University of Mashhad since June 2019. She is part of the Economic and Administrative Sciences Faculty, focusing her expertise on research-driven methodologies to address real-world challenges.

Experience

🌟 Pardis has actively contributed to the academic community through her research publications and peer review activities. She is recognized for her insightful contributions to journals such as the International Journal of System Assurance Engineering and Management and Applied Soft Computing. Her expertise includes optimization models, decision-making under uncertainty, and financial predictions.

Research Interests

💡 Pardis Roozkhosh’s research interests include multi-criteria decision-making (MCDM), optimization in management science, hub location-allocation problems, and predictive modeling for financial systems like Bitcoin price forecasting. Her work is deeply rooted in addressing uncertainty and tardiness in real-world scenarios. 🔍📈

Awards

🏆 While specific awards are not listed, Pardis’s impactful publications and active contributions to peer reviews in renowned journals like Expert Systems with Applications reflect her professional recognition in the academic community.

Publications

A new model to design a product under redundancy allocation problem and MCDM
📅 Published: November 29, 2024 | Journal: International Journal of System Assurance Engineering and Management
📖 Cited by: Pending

Designing a new model for the hub location-allocation problem with considering tardiness time and cost uncertainty
📅 Published: January 2, 2023 | Journal: International Journal of Management Science and Engineering Management
📖 Cited by: Pending

MLP-based Learnable Window Size for Bitcoin price prediction
📅 Published: August 2022 | Journal: Applied Soft Computing
📖 Cited by: Part of ISSN: 1568-4946

Designing a new model for the hub location-allocation problem with considering tardiness time and cost uncertainty
📅 Published: June 5, 2022 | Journal: International Journal of Management Science and Engineering Management
📖 Cited by: Pending