Jian Sun | Smart Grid Control | Best Researcher Award

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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

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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

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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

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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

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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

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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

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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

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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

 

 

sajjad qureshi | Artificial Intelligence Award | Computer Vision Contribution Award

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Dr. sajjad qureshi | artificial intelligence award | Computer Vision Contribution Award

deputy Director (IT), multan electric power company, Pakistan

📘 Dr. Sajjad Hussain Qureshi is a seasoned professional with over 21 years of experience in Information Technology. Currently serving as the Deputy Director (IT) at Multan Electric Power Company for the past two decades, Dr. Qureshi has established expertise in system analysis and design, machine learning, cybersecurity, IT auditing, and project management. His multidisciplinary educational background, including a Ph.D. in Computer Science, Ph.D. in Agriculture, and an MBA in Human Resource Management, has enabled him to excel in IT-based quality assurance, data analysis, and human resource management. He is passionate about utilizing cutting-edge technologies to create impactful solutions in diverse domains.

Publication Profile

ORCID

Education

🎓 Dr. Qureshi holds a Ph.D. in Computer Science, a Ph.D. in Agriculture, and an MBA in Human Resource Management. His diverse academic achievements reflect his commitment to integrating IT with interdisciplinary knowledge for impactful research and practical solutions.

Experience

💼 Dr. Qureshi has an extensive career spanning over 21 years in the IT field. For the last 20 years, he has been a cornerstone of the Multan Electric Power Company, where he serves as the Deputy Director (IT). His experience covers IT infrastructure development, LAN networks, client/server environments, cybersecurity, and customer billing systems. He also excels in IT-based quality assurance and control, project management, and data management.

Research Interests

🔍 Dr. Qureshi’s research interests lie at the intersection of machine learning, deep learning, cybersecurity, data management, and agriculture technology. He is particularly interested in applying advanced computational techniques to solve real-world problems, such as disease detection in crops and classification of linguistic data.

Awards

🏆 Dr. Qureshi has been recognized for his contributions to IT and interdisciplinary research, achieving notable academic and professional milestones. His work continues to inspire innovation and collaboration across diverse fields.

Publications

Classification of English Words into Grammatical Notations Using Deep Learning Technique (2024)
Imran, M., Qureshi, S. H., Qureshi, A. H., & Almusharraf, N.
Published in Information, 15(12), 801.
DOI: 10.3390/info15120801

Rational Study Of The Use Of Computer-Aided Softwares By The Composers (2024)
Qureshi, S. H., Javaid, S., & Javaid, M. A.
Published in Pakistan Journal of Society, Education and Language, 10(2), 213–219.

Comparison of Conventional and Computer-Based Detection of Severity Scales of Stalk Rot Disease in Maize (2024)
Qureshi, S.H., Khan, D.M., Razzaq, A., Baig, M.M., & Bukhari, S.Z.A.
Published in SABRAO Journal of Breeding and Genetics, 56(1), 292–301.
DOI: 10.54910/sabrao2024.56.1.26

Intelligent Resistant Source Detection Against Stalk Rot Disease of Maize Using Deep Learning Technique (2023)
Qureshi, S.H., Khan, D.M., & Bukhari, S.Z.
Published in SABRAO Journal of Breeding and Genetics, 55(6), 1972–1983.

GEUMTAE KIM | Cryptography Award | Best Researcher Award

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Mr. GEUMTAE KIM | Cryptography Award | Best Researcher Award

Ph.D. candidate, Seoul National University, South Korea

🌟 Geumtae Kim is a dedicated Ph.D. candidate at Seoul National University, specializing in the Department of Electrical and Computer Engineering. Guided by Prof. Jong-Seon No, he focuses on advancing the fields of cryptography and secure computing. With a strong academic foundation, Geumtae’s research centers on innovative cryptographic techniques, including post-quantum cryptography and homomorphic encryption. His contributions are marked by publications in prominent journals and conferences, showcasing his commitment to cutting-edge research in cybersecurity. 📚🔒

Publication Profile

ORCID

Education

🎓 Geumtae Kim began his academic journey at Pohang University of Science and Technology (POSTECH), earning a Bachelor of Science in Electrical Engineering in 2019. Pursuing further excellence, he joined Seoul National University in 2019, where he is currently advancing his expertise as a Ph.D. candidate in Electrical and Computer Engineering. 🌐⚡

Experience

🛠️ Since 2019, Geumtae has been immersed in research at Seoul National University under the mentorship of Prof. Jong-Seon No. His work emphasizes cryptographic algorithms and systems that enhance digital security. With years of rigorous study and hands-on experience, he continues to contribute significantly to the fields of cryptography and encryption. 💻🔐

Research Interests

🔍 Geumtae’s research is driven by a passion for creating robust security solutions in the digital age. His primary interests include cryptography, post-quantum cryptography, and homomorphic encryption. These focus areas aim to address the emerging challenges of quantum computing and ensure the confidentiality and integrity of sensitive data. 🔑✨

Awards

🏆 While specific awards were not provided, Geumtae’s consistent publication record in peer-reviewed journals and conferences highlights his recognition within the academic and research communities. His work reflects a strong commitment to excellence and innovation in cryptography. 🌟📜

Publications

Lazy Modular Reduction for NTT

Masked Ciphertext Comparison without Masking Conversions Using Register Rotation and Chinese Remainder Theorem