Abdulaziz Almaktoom | Resilience modeling | Best Researcher Award

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Assoc Prof Dr. Abdulaziz Almaktoom | Resilience modeling | Best Researcher Award

Effat University | Saudi Arabia

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INTRODUCTION 🌟

Dr. Eng. Abdulaziz Turki Almaktoom is a highly distinguished academic and professional in the fields of Operations and Supply Chain Management. Holding a Ph.D. in Industrial Engineering, Dr. Almaktoom is known for his exceptional leadership, consultancy expertise, and a profound impact in higher education. As an Associate Professor and Chair of the Business Administration Department at Effat University, he has not only contributed to the academic sphere but also played an integral role in shaping the future of education in Saudi Arabia. His diverse skills span across Operations Management, Supply Chain Management, Data Analytics, Project Management, Risk Management, and many more.

EARLY ACADEMIC PURSUITS 📚

Dr. Almaktoom’s academic journey began with a keen interest in engineering and operations, leading him to pursue a Bachelor’s in Engineering Technology at Riyadh College of Technology. He continued to excel in his studies, earning a Master’s degree in Engineering Technology from Pittsburg State University, USA, before pursuing a Ph.D. in Industrial Engineering from Wichita State University, USA. His doctoral research focused on the reliability, robustness, and resilience of complex supply chain systems, showcasing his deep commitment to innovative solutions in operations.

PROFESSIONAL ENDEAVORS 💼

Dr. Almaktoom’s career is marked by a seamless blend of academia and industry. He has held significant roles such as Associate Professor, Chair of the Business Administration Department at Effat University, and Consultant for several prestigious firms in Saudi Arabia. His expertise spans across Project Management (PMP®), Risk Management (RMP®), Lean Six Sigma, and Supply Chain Analysis (CSCA®), making him a sought-after figure in both the education and business sectors. His contributions have led to the development of cutting-edge programs and curricula, helping shape future leaders in business administration and engineering.

CONTRIBUTIONS AND RESEARCH FOCUS 🔍

Dr. Almaktoom’s research interests lie primarily in Operations and Supply Chain Management, with a focus on optimization techniques, systems simulation, forecasting, lean and six sigma, and quality control. He has published over 50 scientific articles in renowned international journals and conferences, contributing significantly to the field’s knowledge base. Dr. Almaktoom is particularly known for leveraging advanced methodologies like Artificial Intelligence, Metaheuristics, and Data Analytics to drive forward-thinking solutions in supply chain management.

IMPACT AND INFLUENCE 🌍

Through his innovative approach to curriculum design and leadership, Dr. Almaktoom has created a lasting impact on the education sector. He has been instrumental in the development of new programs, including Ph.D. and B.Sc. degrees in Operations and Supply Chain Management and Entrepreneurship. His influence extends beyond academia through his involvement with various organizations like the IEOM Society International and his role as an advisor and mentor to numerous students, helping them succeed both academically and professionally. His research and teaching continue to inspire students and professionals alike.

ACADEMIC CITATIONS AND PUBLICATIONS 📖

Dr. Almaktoom has gained significant recognition in the academic world for his publications, which have earned him numerous citations. Ranked among the top 20 scientists in Decision Science and Operations Management in Saudi Arabia in 2024, his work continues to influence both the academic and professional communities. His research papers, especially those related to supply chain optimization and risk management, have been highly regarded and cited by peers in the industry.

HONORS & AWARDS 🏆

Throughout his career, Dr. Almaktoom has received numerous prestigious awards. These include being recognized as the Best Graduate Student at Wichita State University in 2015, the recipient of multiple international honors, and being ranked among the top scientists in Saudi Arabia in 2024. His accolades also include recognition for his academic excellence, including awards such as the Alpha Pi Mu Industrial Engineering Honor Society and membership in various elite organizations such as the Golden Key International Honor Society.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

Dr. Almaktoom’s work has already established a strong legacy in the academic and professional sectors. His pioneering role in developing innovative programs and guiding students to success continues to set a high standard for excellence. Looking forward, he aims to further contribute to the research and development of sustainable and efficient solutions in operations and supply chain management, particularly through emerging technologies like AI and machine learning.

FINAL NOTE ✨

Dr. Abdulaziz Turki Almaktoom’s career exemplifies the power of dedication, innovation, and leadership in academia and industry. With a robust track record of impactful contributions in education, research, and professional development, Dr. Almaktoom’s legacy will undoubtedly continue to inspire future generations of students, researchers, and professionals across the globe. His forward-thinking approach and commitment to excellence ensure that his influence will resonate for years to come.

TOP NOTES PUBLICATIONS 📚

Blockchain-Assisted Hierarchical Attribute-Based Encryption Scheme for Secure Information Sharing in Industrial Internet of Things

    • Authors: A. Sasikumar, L. Ravi, M. Devarajan, A. Selvalakshmi, A.T. Almaktoom, A.S. Almazyad, G. Xiong, A.W. Mohamed

    • Journal: IEEE Access

    • Year: 2024

Corrections to “Blockchain-Assisted Hierarchical Attribute-Based Encryption Scheme for Secure Information Sharing in Industrial Internet of Things”

    • Authors: A. Sasikumar, L. Ravi, M. Devarajan, A. Selvalakshmi, A.T. Almaktoom, A.S. Almazyad, G. Xiong, A.W. Mohamed

    • Journal: IEEE Access

    • Year: 2024

Deep Reinforcement Learning for Multiobjective Scheduling in Industry 5.0 Reconfigurable Manufacturing Systems

    • Authors: M. Bezoui, A. Kermali, A. Bounceur, S.M. Qaisar, A.T. Almaktoom

    • Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

    • Year: 2024

Hybrid Metaheuristics for Industry 5.0 Multi-Objective Manufacturing and Supply Chain Optimization

    • Authors: M. Bezoui, A.T. Almaktoom, A. Bounceur, S.M. Qaisar, M. Chouman

    • Journal: 21st International Learning and Technology Conference: Reality and Science Fiction in Education, L and T 2024

    • Year: 2024

Multiple criteria decision-making for determining the optimal wind farm site under uncertainty

    • Authors: A.T. Almaktoom, M.M. Samkari

    • Journal: International Journal of Critical Infrastructures

    • Year: 2024

 

xian Zhang | Geosciences | Best Researcher Award

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Dr. xian Zhang | Geosciences | Best Researcher Award

Hunan University of Finance and Economics | China

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INTRODUCTION 🧑‍🏫

Dr. Xian Zhang is a distinguished academic in the field of information technology and management, currently serving as a Lecturer at the School of Information Technology and Management, Hunan University of Finance and Economics since 2023. With a robust educational background and a strong research profile, Dr. Zhang has made significant contributions to the field of electromagnetic data processing and signal identification. His research spans a wide range of topics, particularly focusing on the processing of magnetotelluric data and noise elimination methods.

EARLY ACADEMIC PURSUITS 🎓

Dr. Zhang embarked on his academic journey with a focus on computer science and engineering. He earned his D.D. from Shaoyang University in 2016, followed by an M.D. from Hunan Normal University in 2019. His academic pursuits culminated in a Ph.D. from Central South University in 2022, laying a strong foundation for his future research endeavors. These early years of study instilled in him a deep understanding of data analysis and computational methods, which he later applied to his work on electromagnetic data.

PROFESSIONAL ENDEAVORS 💼

Since 2023, Dr. Zhang has been contributing to the academic community as a Lecturer at the School of Information Technology and Management, Hunan University of Finance and Economics. His professional career has been characterized by a commitment to both teaching and groundbreaking research. In his role, he imparts knowledge to future professionals in the field, shaping the next generation of experts in data analysis and information technology.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Dr. Zhang’s research is centered on signal processing, with a particular emphasis on magnetotelluric and electromagnetic data. His work on separating magnetotelluric signals, utilizing advanced computational techniques like composite multiscale dispersion entropy and orthogonal matching pursuit, has garnered recognition within the scientific community. Additionally, his exploration of machine learning techniques, such as grey wolf optimization and detrended fluctuation analysis, has brought innovative approaches to electromagnetic signal identification and noise reduction.

IMPACT AND INFLUENCE 🌍

Dr. Zhang’s research has not only advanced the field of electromagnetic signal processing but also impacted the methods used in geophysics, specifically in noise elimination and feature extraction from complex data sets. His work has influenced both theoretical developments and practical applications in geophysical exploration. Furthermore, his interdisciplinary approach bridges the gap between data science, physics, and engineering, offering insights into improving electromagnetic signal processing technologies.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Dr. Zhang’s scholarly contributions are well-documented in numerous peer-reviewed journals. His work has been published in prestigious journals, including Earth Planets and Space, Acta Geophysica, Oil Geophysical Prospecting, Machine Learning: Science and Technology, and Geophysical Prospecting. His notable journal articles cover a wide range of topics, from noise removal techniques to advanced signal processing methods using machine learning algorithms. These publications have significantly contributed to the body of knowledge in the areas of signal processing and geophysical exploration.

HONORS & AWARDS 🏆

Dr. Zhang’s exceptional research efforts have been recognized with various accolades, including the prestigious Hunan Xiaohe Science and Technology Talent Award in 2024. This recognition underscores his outstanding contributions to science and technology, particularly in the realm of geophysical data processing and electromagnetic signal analysis. His work continues to inspire and influence future research in these fields.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

As Dr. Zhang continues to develop his research and academic career, his contributions to signal processing and electromagnetic data analysis are expected to have lasting effects on both academia and industry. His future work is poised to further bridge the gap between theoretical research and practical applications, particularly in environmental monitoring, resource exploration, and technological advancements in data processing. His legacy will be defined by his ability to solve complex scientific problems and inspire innovation in data-driven technologies.

FINAL NOTE 📝

Dr. Xian Zhang’s career reflects a deep commitment to advancing the field of electromagnetic signal processing. His impressive academic background, coupled with his ongoing professional contributions, solidifies his role as a leading figure in his field. With a growing portfolio of research, honors, and impactful publications, Dr. Zhang’s work continues to push the boundaries of what is possible in data analysis and signal processing. His future endeavors are sure to influence both academia and practical applications across various industries.

TOP NOTES PUBLICATIONS 📚

Controlled-source electromagnetic noise attenuation via a deep convolutional neural network and high-quality sounding curve screening mechanism

    • Authors: Yecheng Liu, Diquan Li, Jin Li, Xian Zhang

    • Journal: GEOPHYSICS

    • Year: 2025

Noise Elimination for Wide Field Electromagnetic Data via Improved Dung Beetle Optimized Gated Recurrent Unit

    • Authors: Zhongyuan Liu, Xian Zhang, Diquan Li, Shupeng Liu, Ke Cao

    • Journal: Geosciences

    • Year: 2025

Coordinate Attention-Temporal Convolutional Network for Magnetotelluric Data Processing

    • Authors: Jin Li, Hong Cheng, Jiayu Wang, Xian Zhang, Jingtian Tang

    • Journal: IEEE Transactions on Geoscience and Remote Sensing

    • Year: 2024

Intelligent processing of electromagnetic data using detrended and identification

    • Authors: Xian Zhang, Diquan Li, Bei Liu, Yanfang Hu, Yao Mo

    • Journal: Machine Learning: Science and Technology

    • Year: 2023

Deep structure of the Rongcheng geothermal field, Xiongan New Area: Constraints from resistivity data and boreholes

    • Authors: Yunqi Zhu, Diquan Li, Yanfang Hu, Xian Zhang, Fu Li, Feng Ma, Guiling Wang

    • Journal: Geothermics

    • Year: 2023

 

Yongzhi Qu | Scientific Machine Learning | Excellence in Innovation

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Dr. Yongzhi Qu | Scientific Machine Learning | Excellence in Innovation

University of Utah | United States

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Biography of Dr. Yongzhi Qu

🏅 Assistant Professor at University of Utah | Ph.D. in Industrial Engineering & Operations Research

Dr. Yongzhi Qu is an accomplished assistant professor at the University of Utah in the Department of Mechanical Engineering, specializing in AI-powered systems, data-driven dynamics, autonomous manufacturing, and digital twins. He earned his Ph.D. from the University of Illinois at Chicago in 2014, with a focus on Industrial Engineering & Operations Research. His research spans several fields, including machine learning, system modeling, and control for mechanical and structural systems.

📚 Education

  • Ph.D. in Industrial Engineering & Operations Research – University of Illinois at Chicago (2014)
  • M.S. in Measurement & Testing Technology – Wuhan University of Technology (2011)
  • B.Sc. in Measurement & Control Instrumentation and Technology – Wuhan University of Technology (2008)

💼 Professional Experience

  • Assistant Professor (07/2023 – Present)
    Department of Mechanical Engineering, University of Utah
  • Assistant Professor (08/2019 – 06/2023)
    Department of Mechanical & Industrial Engineering, University of Minnesota Duluth
  • Assistant/Associate Professor (01/2015 – 07/2019)
    Department of Mechanical Engineering, Wuhan University of Technology
  • Application Engineer (12/2013 – 12/2014)
    The DEI Group, Millersville, Maryland, US

🧠 Research Interests ON Scientific Machine Learning

Dr. Qu’s research focuses on scientific machine learning, AI-powered system modeling, estimation, and control for dynamic systems, with applications in autonomous manufacturing and digital twins. His recent work explores the intersection of machine learning, physics, and mathematics to model and control complex systems.

🏆 Research Grants

  • A Neural Differential Machine Learning Framework with Nonlinear Physics
    National Institute of Standards and Technology (NIST), $121,015 (2023-2026)
  • Real-time System Identification for Machining Spindles
    NIST, $159,950 (2020-2022)
  • Learning Real-time Dynamics of a Rotor System
    University of Minnesota, $44,501 (2020-2021)

🏅 Academic Awards

  • Best Academic Paper Award (IEEE International Conference on Prognostics and Health Management, 2013)
  • Best Student Paper Award (Society for Machinery Failure Prevention Technology Conference, 2014)
  • Best Paper Award (Prognostics and System Health Monitoring Conference, 2018)

📢 Invited Talks

  • Machine Learning for Dynamic System Modeling, Seagate (2022)
  • Keynote on Deep Learning in PHM, Annual Conference of PHM Society (2019)
  • FBG Sensing for Machinery Health Monitoring, Northeastern University, China (2016)

🎓 Teaching

  • Machine Learning for System Dynamics and Control, University of Minnesota Duluth
  • Six Sigma and Quality Control, University of Minnesota Duluth
  • Control Engineering, Wuhan University of Technology

🤝 Professional Service

  • Organizing Chair, Data Challenge, 15th Annual Conference of PHM Society (2023)
  • Panelist, Doctoral Symposium, 14th Annual Conference of PHM Society (2022)
  • Symposium Chair, ASME Manufacturing Science and Engineering Conference (2022, 2023)

📚 TOP NOTES PUBLICATIONS 

State space neural network with nonlinear physics for mechanical system modeling
    • Authors: Reese Eischens, Tao Li, Gregory W. Vogl, Yi Cai, Yongzhi Qu
    • Journal: Reliability Engineering & System Safety
    • Year: 2025
    • DOI: 10.1016/j.ress.2025.110946
Graph neural network architecture search for rotating machinery fault diagnosis based on reinforcement learning
    • Authors: Jialin Li, Xuan Cao, Renxiang Chen, Xia Zhang, Xianzhen Huang, Yongzhi Qu
    • Journal: Mechanical Systems and Signal Processing
    • Year: 2023
    • DOI: 10.1016/j.ymssp.2023.110701
Development of Deep Residual Neural Networks for Gear Pitting Fault Diagnosis Using Bayesian Optimization
    • Authors: Jialin Li, Renxiang Chen, Xianzhen Huang, Yongzhi Qu
    • Journal: IEEE Transactions on Instrumentation and Measurement
    • Year: 2022
    • DOI: 10.1109/TIM.2022.3219476
A domain adaptation model for early gear pitting fault diagnosis based on deep transfer learning network
    • Authors: Jialin Li, Xueyi Li, David He, Yongzhi Qu
    • Journal: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
    • Year: 2020
    • DOI: 10.1177/1748006X19867776
Gear pitting fault diagnosis using disentangled features from unsupervised deep learning
    • Authors: Yongzhi Qu, Yue Zhang, Miao He, David He, Chen Jiao, Zude Zhou
    • Journal: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
    • Year: 2019
    • DOI: 10.1177/1748006X18822447

 

Vinit Vijay Deshpande | Algorithm Development | Best Researcher Award

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Dr. Vinit Vijay Deshpande | Algorithm Development | Best Researcher Award

University of Applied Sciences, Darmstadt | Germany

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DR. VINIT VIJAY DESHPANDE– BIOGRAPHY 🌱📚

📍 PhD in Computational Mechanics | Researcher, Educator, Innovator

Education 🎓

PhD in Computational Mechanics (Expected Feb 2025)
University of Applied Sciences, Darmstadt, Germany

  • Thesis: “Computational strategies for characterization, reconstruction, and property estimation of ceramic foam” (magna cum laude)
  • Advisor: Prof. Dr. Romana Piat

Master of Technology in Engineering Mechanics (May 2013)
Indian Institute of Technology, Delhi, India

Invited Talks 🗣️

  1. Use of image segmentation to characterize failure modes of struts in ceramic foam under compression
    49th International Conference and Expo on Advanced Ceramics and Composites (ICACC 2025), Daytona Beach, Florida, USA
  2. Application of skeletonization algorithm to investigate failure modes of ceramic foam in uniaxial compression
    4th International Workshops on Advances in Computational Mechanics (IWACOM-IV), Kitakyushu, Japan

Conference Presentations 📅

  • Investigating microstructure failure modes of ceramic foam under uniaxial compression – 16th World Congress on Computational Mechanics (WCCM 2024)
  • Artificial microstructure reconstruction algorithm for stiffness property estimation – 48th ICACC 2024
  • Computational methodology for the relation between volume fraction and compression strength of ceramic foam – 21st International Conference on Fracture and Damage Mechanics (FDM 2023)
    (For the complete list of conferences, refer to the original document.)

Patents 📑

  • 12 Patents on combined braking systems for two-wheelers.
  • 2 Patents on innovative stand concepts for two-wheelers.

Awards & Recognitions 🏆

  • Best Paper Award, Collaborative European Research Conference (CERC) 2020
  • Lieutenant Arpan Banerjee Award for securing the highest CGPA in MTech and D.I.I.T programmes at IIT Delhi (2012-13)

Scholarships 💡

  • Doctoral Fellowship, University of Applied Sciences, Darmstadt
  • DAAD Sandwich Scholarship for master’s thesis in Germany

Teaching Experience 👨‍🏫

  • Teaching Assistant: Laboratory course for ‘Numerical Solutions to Partial Differential Equations’ since Fall 2020

Student Advising 👨‍🎓

  • Supervised 6 Master’s Thesis students in the field of computational mechanics.

Research Interests 🔬

  • Microstructure reconstruction algorithms
  • Constitutive modeling
  • Surrogate modeling using machine learning
  • Microstructure segmentation algorithms

Research Experience  ON Algorithm Development 🧑‍🔬

  • Research Associate – University of Applied Sciences, Darmstadt (Sept 2024 – Present)
    Focus: Conductive polymer composites & microstructure algorithms

  • Scientific Assistant – University of Applied Sciences, Darmstadt (Dec 2019 – Aug 2024)
    Focus: Porous ceramics, fracture modeling, and transfer learning-based neural networks

  • Research Assistant – Karlsruhe Institute of Technology (Sept 2012 – Mar 2013)
    Focus: Topology optimization of carbon-carbon composites

  • Research Assistant – IIT Delhi (June 2012 – Aug 2012)
    Focus: Elastic properties of carbon-carbon composites

Industry Experience 🏭

  • Analyst – Vehicle Dynamics Simulation, Hero MotoCorp (Aug 2013 – Dec 2019)
    Focus: Multibody simulations, vehicle dynamics, stability, ride-comfort, and braking systems
  • Trainee – Computer Aided Engineering, Tata Technologies Ltd (July 2010 – July 2011)
    Focus: Mesh modeling of four-wheelers for safety and durability analysis

Technical Skills 💻

  • Advanced simulation software
  • Computational algorithms for material modeling
  • Finite Element Analysis (FEA) and multibody dynamics simulations
  • Machine learning for data-driven modeling

Top Notes Publications 📚

Biaxial compression failure of brittle foams: A transfer learning-based strategy
    • Authors: Vinit Vijay Deshpande; Romana Piat
    • Journal: Procedia Structural Integrity
    • Year: 2024
Numerical Strategies to Study Compression Failure in Brittle Foams with 3D Realistic Microstructures
    • Authors: Vinit Vijay Deshpande; Romana Piat
    • Journal: Advanced Structured Materials
    • Year: 2024
Numerical studies of the elastic properties of ceramic foam by creation of the artificial microstructures after processing of computed tomographic images
    • Authors: Romana Piat; Vinit Vijay Deshpande
    • Journal: AIP Conference Proceedings
    • Year: 2023
Compression failure of porous ceramics: A computational study about the effect of volume fraction on damage evolution and failure
    • Authors: Vinit Vijay Deshpande; Romana Piat
    • Journal: Mechanics of Materials
    • Year: 2023
Application of statistical functions to the numerical modelling of ceramic foam: From characterisation of CT-data via generation of the virtual microstructure to estimation of effective elastic properties
    • Authors: Vinit Vijay Deshpande; Kay André Weidenmann; Romana Piat
    • Journal: Journal of the European Ceramic Society
    • Year: 2021

Snehal Laddha | Medical Image Analysis | Best Researcher Award

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Prof. Snehal Laddha | Medical Image Analysis | Best Researcher Award

University of Bradford | United Kingdom

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INTRODUCTION 🌟

Ms. Snehal Laddha is a highly accomplished and dynamic educator and professional, with an extensive background in Electronics and Computer Science, specializing in AI, Data Analysis, and Deep Learning. With over 16 years of experience in the academic field, she has significantly contributed to student engagement, research innovation, and global academic exposure through teaching roles in India, Australia, and the UK.

EARLY ACADEMIC PURSUITS 📚

Snehal’s academic journey began with a keen interest in electronics and computer science. She completed her formal education, setting the foundation for her research in emerging fields such as Artificial Intelligence (AI) and data analysis. Her academic pursuit took her across various top institutions, where she honed her skills in programming, image analysis, and deep learning, fueling her desire to make a significant impact on both the academic and technological landscapes.

PROFESSIONAL ENDEAVORS 👩‍🏫

Snehal’s career includes prestigious teaching roles such as Assistant Professor at Ramdeobaba University, H.V.P.M.C.O.E.T., and S.R.K.N.E.C. in India, as well as a Teaching Tutor position at the University of Technology, Sydney, Australia. She has also demonstrated remarkable versatility, contributing in non-teaching roles such as Customer Service at Sydney CBD METCENTER, where she gained invaluable international exposure and insights into multicultural education systems.

CONTRIBUTIONS AND RESEARCH FOCUS  ON MEDICAL IMAGE ANALYSIS💡

A passionate researcher, Snehal’s work primarily revolves around AI, computer vision, and Internet of Things (IoT) applications. Her efforts in data analysis, deep learning, and image analysis have led to several publications in both national and international journals. Her most notable invention is the IoT-powered smart trash bin (patent granted in 2024). She is deeply committed to improving academic practices by leading initiatives to organize Faculty Development Programs (FDPs) and research projects sponsored by AICTE.

IMPACT AND INFLUENCE 🌍

Snehal’s global exposure and significant contributions in both teaching and research have shaped the careers of many students and academics. She consistently fosters innovation, critical thinking, and leadership in her students by incorporating advanced technologies into the curriculum. Through her work, she has become a vital figure in the academic community, nurturing the next generation of scientists and engineers.

ACADEMIC CITATIONS AND PUBLICATIONS 📑

Snehal has published numerous papers in international and national journals, covering a wide range of topics, from embedded systems to AI applications. Her citations reflect her deep expertise and recognition in the academic community. She remains dedicated to advancing her field and continues to contribute valuable insights through her research endeavors.

HONORS & AWARDS 🏆

Ms. Snehal Laddha has been recognized for her exceptional academic and professional contributions with multiple prestigious honors:

  • Australian Qualified Professional Engineer certification by Engineers Australia
  • Best Paper Award at Cardiff Metropolitan University, UK
  • Grants for organizing Faculty Development Programs and SPICES from AICTE
  • IELTS Score of 6.5/10 from the British Council

These awards reflect her dedication to excellence in both teaching and research, cementing her as a leader in her field.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

Looking forward, Snehal plans to continue her research and academic endeavors, focusing on the evolution of AI and its practical applications in various industries. She is determined to contribute to the development of innovative solutions that can address societal challenges, particularly through IoT, deep learning, and image processing.

FINAL NOTE ✨

Ms. Snehal Laddha’s career is a testament to her unwavering commitment to education, research excellence, and global academic collaboration. With a rich background spanning teaching, research, and innovative solutions, she continues to inspire and lead in the realm of AI and data science, ensuring her legacy as an influential figure in the academic and technological spheres.

TOP NOTES PUBLICATIONS 📚

Liver Segmentation from MR T1 In-Phase and Out-Phase Fused Images Using U-Net and Its Modified Variants
    • Authors: SVL Siddhi Chourasia, Rhugved Bhojane
    • Journal: Intelligent Systems. ICMIB 2024. Lecture Notes in Networks and Systems
    • Year: 2025
Deep-Dixon: Deep-Learning frameworks for fusion of MR T1 images for fat and water extraction
    • Authors: SV Laddha, RS Ochawar, K Gandhi, YD Zhang
    • Journal: Multimedia Tools and Applications
    • Year: 2024
Addressing Class Imbalance in Diabetic Retinopathy Segmentation: A Weighted Ensemble Approach with U-Net, U-Net++, and DuckNet
    • Authors: E Gawate, S Laddha
    • Journal: International Conference on Intelligent Systems for Cybersecurity (ISCS)
    • Year: 2024
A Novel Method of Enhancing Skin Lesion Diagnosis Using Attention Mechanisms and Weakly-Supervised Learning
    • Author: SV Laddha
    • Journal: World Conference on Artificial Intelligence: Advances and Applications
    • Year: 2024
Automated Liver Segmentation in MR T1 In-Phase Images Transfer Learning Technique
    • Authors: SV Laddha, AH Harkare
    • Journal: Proceedings of Eighth International Conference on Information System Design
    • Year: 2024
Automated Segmentation of Liver from Dixon MRI Water-Only Images Using Unet, ResUnet, and Attention-Unet Models
    • Authors: E Gawate, SV Laddha, RS Ochawar
    • Journal: Information System Design: AI and ML Applications: Proceedings of Eighth International Conference on Information System Design
    • Year: 2024

Amjad Abu ELSamen | marketing | Best Scholar Award

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Prof. Amjad Abu ELSamen | marketing | Best Scholar Award

Zayed University | United Arab Emirates

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INTRODUCTION 📚

Amjad Abu-Elsamen, PhD, is a distinguished academic and professional in the fields of marketing, predictive modeling, and data mining, based in Abu Dhabi, UAE. With a career that spans over two decades, Dr. Abu-Elsamen has made significant contributions to academia and consultancy, blending his expertise in business strategy, data analytics, and marketing. His passion for continuous learning and his unwavering dedication to professional growth have earned him recognition and numerous accolades in both his academic and practical endeavors.

EARLY ACADEMIC PURSUITS 🎓

Dr. Abu-Elsamen’s academic journey began with his undergraduate studies in Business Administration at the University of Jordan, where he earned his Bachelor’s degree in 2000. He went on to pursue his Master of Business Administration (MBA) at the University of Jordan, completing it in 2003. Following this, he advanced his studies by earning a PhD in Business Administration from Oklahoma State University in 2009. During his academic pursuits, he developed a keen interest in predictive modeling, data mining, and their applications in marketing strategies.

PROFESSIONAL ENDEAVORS 💼

Dr. Abu-Elsamen’s professional career reflects his commitment to education, research, and industry consultancy. He has served as a Professor of Marketing at Zayed University since 2019, with prior roles such as the Associate Professor of Marketing and Graduate Programs Director. His extensive experience as a department chair in various academic institutions, including Zayed University and the University of Jordan, highlights his leadership skills and dedication to curriculum development and accreditation. Dr. Abu-Elsamen’s industry work is equally impressive, with significant consultancy contributions for major corporations in the UAE and Jordan, including Etihad Airways, Marina Mall, and Al-Ain Distribution Company.

CONTRIBUTIONS AND RESEARCH FOCUS  ON MARKETING🔬

Dr. Abu-Elsamen’s research interests lie primarily in marketing strategy, data mining, and predictive modeling. He has published numerous studies on topics such as customer satisfaction measurement, brand management, and the use of advanced analytics in decision-making processes. His research contributions also extend to the design of business programs and the development of new marketing techniques that combine traditional strategies with innovative data-driven insights. Additionally, he has provided key guidance on curriculum redesign and development, particularly in graduate programs, ensuring that they remain aligned with global standards and market needs.

IMPACT AND INFLUENCE 🌍

Dr. Abu-Elsamen’s influence extends beyond his teaching and research contributions. He has been instrumental in shaping the business education landscape in the UAE and Jordan, particularly in the areas of business analytics and marketing strategy. His leadership in developing the Business Analytics Certification Program, the first of its kind in the Middle East, showcases his dedication to advancing education in this critical field. Furthermore, his active participation in committees and task forces within his institutions, including the revision of faculty promotion guidelines and mentorship programs, highlights his commitment to enhancing academic standards and faculty development.

ACADEMIC CITATIONS AND PUBLICATIONS 📝

Dr. Abu-Elsamen has contributed widely to academic journals, conferences, and industry reports. His work has been recognized internationally, with notable citations in the areas of marketing research, customer satisfaction, and data mining techniques. Some of his well-known publications include studies on structural equation modeling, segmentation analysis, and the use of conjoint analysis in new product development. His published research continues to shape contemporary marketing and data analytics practices.

HONORS & AWARDS 🏅

Dr. Abu-Elsamen’s exceptional academic and professional achievements have earned him several prestigious honors, including:

  • Best Paper Award, ACME Conference (2011)
  • Second Best Model Building Award, Data Mining Shootout (2008)
  • Recognition for his leadership in business analytics and marketing strategy across multiple universities and consultancy projects.

FINAL NOTE ✨

Dr. Amjad Abu-Elsamen’s career is a testament to the power of perseverance, innovation, and academic excellence. Through his dedication to both teaching and consultancy, he has made significant strides in reshaping business education, particularly in the realms of marketing, data mining, and analytics. His passion for knowledge and growth continues to inspire both students and professionals in the Middle East and beyond.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Looking to the future, Dr. Abu-Elsamen aims to further elevate business education and consultancy in the UAE and globally. He plans to continue his research into advanced data mining techniques and their applications in marketing strategy, with a particular focus on predictive analytics and artificial intelligence. His ongoing work promises to impact future generations of students and professionals, continuing to drive innovation and excellence in the field.

TOP NOTES PUBLICATIONS 📚

Modelling the impact of 3D product presentation on online behaviour
    • Authors: RS Algharabat, AA Abu-ElSamen
    • Journal: International Journal of Electronic Marketing and Retailing
    • Year: 2013
      🖥️📦👀📊
Examining the Construct Validity of the Lockwood Goal Orientation Scale Using the General Hierarchal Model: An Exploratory Study
    • Author: A Abu ELSamen
    • Journal: Academy of Marketing Science Annual Conference
    • Year: 2010
      🎯📚📊
An empirical model of mobile shopping attitudes and intentions in an emerging market
    • Authors: MN Akroush, B Mahadin, AA ElSamen, A Shoter
    • Journal: International Journal of Web Based Communities
    • Year: 2020
      📱🛒🌍💭
An empirical model of customer service quality and customer loyalty in an international electronics company
    • Authors: AA Abu-ELSamen, MN Akroush, AL Al-Sayed, HJ Hasan
    • Journal: International Journal of Electronic Business
    • Year: 2012
      💼💡🤝📊
Conceptualisation and development of customer service skills scale: an investigation of Jordanian customers
    • Authors: MN Akroush, AA Abu-ElSamen, MS Al-Shibly, FM Al-Khawaldeh
    • Journal: International Journal of Mobile Communications
    • Year: 2010
      📱💬💡🌍
Fintech and contactless payment: help or hindrance? The role of invasion of privacy and information disclosure
    • Authors: AA Alalwan, AM Baabdullah, MM Al-Debei, R Raman, HK Alhitmi, …
    • Journal: International Journal of Bank Marketing
    • Year: 2024
      💳🔒💡🔍

Noor Ul Hadi | Strategic Management | Best Researcher Award

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Dr. Noor Ul Hadi | Strategic Management | Best Researcher Award

Doctorate at Prince Mohammad Bin Fahd University, Saudi Arabia

PROFILES👨‍🎓

 BIOGRAPHY OF DR. NOOR UL HADI 🌟

EARLY ACADEMIC PURSUITS 🎓

Dr. Noor Ul Hadi began her academic journey with a strong foundation in Strategic Management. She earned her advanced degrees from prestigious institutions, where she honed her research skills and developed a passion for data analysis and sustainable business practices. Her commitment to education laid the groundwork for her future endeavors in academia and research.

PROFESSIONAL ENDEAVORS 💼

Currently an Associate Professor at Prince Mohammad Bin Fahd University, Saudi Arabia, Dr. Hadi has built a distinguished career in higher education. With over 30 published articles in reputable journals, she has significantly contributed to the academic community, engaging in editorial roles and fostering collaborations with fellow researchers.

CONTRIBUTIONS AND RESEARCH FOCUS 🔍

Dr. Hadi’s research primarily revolves around Business Circularity, focusing on sustainable practices that align with the United Nations Sustainable Development Goals (SDGs). Her work addresses critical areas such as public health, quality education, and responsible consumption, making her contributions essential for advancing sustainability in industry and society.

IMPACT AND INFLUENCE 🌍

Her influential papers on data analysis have garnered substantial citations, underscoring her impact in the field. Notably, her insights into small enterprises and social entrepreneurship are pivotal for fostering economic growth and innovation. Dr. Hadi’s work in recycling and circular economy principles has inspired both academic peers and industry practitioners.

ACADEMIC CITES 📚

With a citation index of 2107 on Google Scholar, Dr. Hadi’s research is widely recognized and cited. Her notable publications highlight the importance of strategic management in contemporary business practices and demonstrate her leadership in fostering responsible innovation.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Dr. Noor Ul Hadi is committed to advancing knowledge and practices in sustainable business. Her future contributions aim to deepen the understanding of circular economy principles and promote sustainable development in academia and industry. Through her mentorship and research initiatives, she continues to inspire the next generation of scholars and practitioners.

TOP NOTED PUBLICATIONS 📖

Unveiling the Complex Relationship between Open Circular Innovation and Business Circularity: The Role of Circular-Based Dynamic Capabilities and Circular Ambidexterity
  • Authors: Hadi, N.U.
    Journal: Sustainability (Switzerland)
    Volume: 16
    Issue: 17
    Pages: 7647
    Year: 2024
Fostering hotel ambidexterity through knowledge-sharing culture and knowledge-sharing behavior: a study of the hospitality sector in Pakistan
  • Authors: Hadi, N.U., Sheikh, S.A.
    Journal: Business Process Management Journal
    Volume: 30
    Issue: 4
    Pages: 1297–1313
    Year: 2024
Promoting sustainable learning among accounting students: evidence from field experimental design
  • Authors: Hadi, N.U., Abdel-Razzaq, A.I.
    Journal: Higher Education, Skills and Work-based Learning
    Volume: 14
    Issue: 2
    Pages: 479–491
    Year: 2024
Exploring the Relationship Between Performance Assessment and Employee Performance: The Role of Performance Planning and Performance Review
  • Authors: Al Thawadi, M.M., Hadi, N.U.
    Book Title: Studies in Systems, Decision and Control
    Volume: 517
    Pages: 523–531
    Year: 2024
Simple Mediation Analysis: The Complementing Role of Parallel Multiple Mediation Approach via Process Analysis
  • Authors: Mahmood, N., Hadi, N.U., Talha, M.
    Book Title: Studies in Systems, Decision and Control
    Volume: 517
    Pages: 479–493
    Year: 2024

Poonam Mandale – Chemical Engineering – Young Scientist Award 

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Mrs. Poonam Mandale - Chemical Engineering - Young Scientist Award 

D.Y.Patil College of Engineering and Technology - India

Author Profile

Early Academic Pursuits

Mrs. Poonam Ramchandra Mandale embarked on her academic journey with a fervent passion for chemical engineering, which eventually led her to pursue a Ph.D. in the field of Waste Water Treatment from Bharati Vidyapeeth University College of Engineering, Pune. Born on February 23, 1992, her commitment to academia was evident from the beginning.

Her undergraduate and postgraduate studies provided her with a strong foundation in chemical engineering, laying the groundwork for her future research endeavors. Throughout her educational journey, she exhibited a keen interest in environmental sustainability, particularly in the realm of water treatment. Her academic pursuits were driven by a desire to contribute meaningfully to society by addressing critical environmental challenges.

Professional Endeavors

Joining D.Y. Patil College of Engineering and Technology, Kolhapur, as an Assistant Professor in March 2020, Mrs. Mandale embarked on her professional career. Over the past four years, she has imparted knowledge to undergraduate students in various subjects ranging from Chemical Engineering Thermodynamics to Industrial Economics Management & Entrepreneurship. Her dedication to teaching is underscored by her involvement in various academic and extracurricular activities, including serving as the coordinator for several committees and clubs within the institution.

In addition to her teaching responsibilities, Mrs. Mandale has actively engaged in continuous professional development through participation in numerous workshops and faculty development programs. These initiatives have allowed her to enhance her skills and stay abreast of the latest advancements in her field, including topics such as Hydrogen Energy, Aspen Plus simulation software, and Chemical Process Safety.

Contributions and Research Focus On Chemical Engineering

Mrs. Mandale's research primarily focuses on the removal of dyes from aqueous solutions using low-cost bioadsorbents. Her work is significant in addressing environmental concerns associated with industrial wastewater, particularly from sectors such as textiles, plastics, and cosmetics. Through her published papers and presentations, she has explored the efficacy of various bioadsorbents, such as Tricoderma viride and Arjun Saal powder, in removing dyes like Rhodamine B and Malachite Green from wastewater.

Her research contributions extend beyond academic publications, as she actively seeks to bridge the gap between academia and industry. By investigating practical solutions to environmental challenges, she aims to contribute to sustainable manufacturing practices and promote eco-friendly alternatives in wastewater treatment.

Accolades and Recognition

Mrs. Mandale's dedication to her work has not gone unnoticed, as evidenced by her participation in numerous faculty development programs and workshops organized by prestigious institutions like IIT Bombay, IIT Guwahati, and IIT Roorkee. Her contributions to the field have also been recognized through awards such as the Elite certificate from IIT Bombay and the granted patent for her research on dye removal using bioadsorbents.

Impact and Influence

Through her research and academic endeavors, Mrs. Mandale has made significant contributions to the field of chemical engineering, particularly in the area of wastewater treatment. Her work has the potential to revolutionize current practices by offering cost-effective and environmentally friendly solutions to industrial wastewater management.

Legacy and Future Contributions

Looking ahead, Mrs. Mandale aims to further expand her research portfolio and collaborate with industry partners to implement sustainable solutions on a larger scale. By continuing to mentor students and actively participate in academic forums, she hopes to inspire future generations of researchers and contribute to the advancement of knowledge in her field. Her commitment to excellence and passion for environmental sustainability serve as a beacon for aspiring academics and researchers alike.

Notable Publication