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

Publication Profile

Google Scholar

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

Jingzhao Lu | Environmental Data Analysis | Best Researcher Award

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Dr. Jingzhao Lu | Environmental Data Analysis | Best Researcher Award

Hebei agricultural university | China

Publication Profile

Scopus

Research Gate

EARLY ACADEMIC PURSUITS 🎓

Dr. Jingzhao Lu began his academic journey at Hebei Agricultural University in China, where he initially focused on the environmental sciences. His early studies were deeply rooted in understanding the interaction between land-use types, environmental pollutants, and their broader impact on ecosystem health. With a keen interest in satellite technology and data analytics, he pursued research that involved the application of remote sensing in monitoring and quantifying environmental changes.

PROFESSIONAL ENDEAVORS 💼

Dr. Lu’s professional career has been marked by his dedication to the integration of satellite observations and environmental modeling. He has worked across various academic and research institutions, with Hebei Agricultural University standing as a cornerstone of his professional life. His work has advanced the understanding of environmental data analysis, especially regarding the effects of land-use changes, inorganic pollutants, and CO2 emissions. His professional endeavors include collaborations with national and international research bodies, enhancing global environmental monitoring efforts.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Dr. Lu’s research primarily revolves around environmental data analysis, focusing on the quantification and modeling of environmental impacts. His contributions are vast, particularly in the fields of satellite-based observations, land-use classification, and the impact of inorganic pollutants on various ecosystems. His work on CO2 emissions and numerical modeling has opened up new avenues for understanding the complexities of greenhouse gases and their role in climate change. Dr. Lu has published several impactful papers, contributing to the growing body of knowledge on global environmental monitoring.

IMPACT AND INFLUENCE 🌍

Dr. Jingzhao Lu’s work has had a significant impact on both local and global environmental policy and research. His research findings have been used to inform land-use management practices, environmental protection strategies, and climate change mitigation efforts. Through his contributions, he has influenced the direction of future environmental research, particularly in the area of using remote sensing technologies for monitoring environmental changes. His influence can be seen in the growing integration of satellite data into environmental decision-making processes around the world.

ACADEMIC CITATIONS 📚

Dr. Lu’s academic citations highlight his contributions to the field of environmental science. His research papers are widely cited by scholars and researchers in the areas of environmental monitoring, land-use change, and pollutant studies. These citations are a testament to the relevance and quality of his work, as his findings continue to shape ongoing environmental research. He is frequently referenced in studies on satellite observations, CO2 emissions, and pollutant dynamics, establishing him as a leader in his field.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

Dr. Jingzhao Lu’s legacy will be marked by his profound influence on the field of environmental data analysis and satellite-based observations. His work has laid a strong foundation for future generations of researchers to build upon, especially in addressing the challenges posed by climate change and environmental degradation. Moving forward, Dr. Lu’s future contributions are expected to focus on enhancing environmental models through improved satellite technology, refining CO2 emissions estimates, and advancing numerical models to better predict environmental outcomes. His work continues to inspire new research and collaborations, ensuring that his legacy will endure in the academic and environmental communities for years to come.

Publication Top Notes

Spatial Analysis of Carbon Metabolism in Different Economic Divisions Based on Land Use and Cover Change (LUCC) in China
    • Authors: Cui Yuan, Yaju Liu, Jingzhao Lu, Wei Su
    • Journal: Not specified in the provided text.
    • Year: January 2025
Research on the spatial–temporal distribution of three-dimensional carbon footprint in different urban agglomerations in China
    • Authors: Chengyi Guo, Jingzhao Lu, Cui Yuan, Yanlong Guan
    • Journal: Not specified in the provided text.
    • Year: January 2025
A multivariate analysis of microplastics in soils along the headwaters of Yangtze River on the Tibetan Plateau
    • Authors: Sansan Feng, Hongwei Lu, Yuxuan Xue, Tong Sun
    • Journal: Not specified in the provided text.
    • Year: April 2024
A review of the occurrence, transformation, and removal technologies for the remediation of per- and polyfluoroalkyl substances (PFAS) from landfill leachate
    • Authors: Jingzhao Lu, Hongwei Lu, Dongzhe Liang, Jingyu Li
    • Journal: Not specified in the provided text.
    • Year: May 2023
Population density regulation may mitigate the imbalance between anthropogenic carbon emissions and vegetation carbon sequestration
    • Authors: Dongzhe Liang, Hongwei Lu, Yanlong Guan, Jingzhao Lu
    • Journal: Not specified in the provided text.
    • Year: March 2023

Xianguang Guo | Data Visualization | Best Researcher Award

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Dr. Xianguang Guo | Data Visualization | Best Researcher Award

Chengdu Institute of Biology, Chinese Academy of Sciences, China

Publication Profile

Orcid

📝 Summary

Dr. Xianguang Guo is an Associate Professor at the Chengdu Institute of Biology, Chinese Academy of Sciences, specializing in molecular phylogenetics, biogeography, and evolution. His research primarily focuses on reconstructing evolutionary relationships in reptiles, particularly the racerunner Eremias and toad-headed agama Phrynocephalus in arid Central Asia.

🎓 Education

  • Ph.D. in Hydrobiology, Institute of Hydrobiology, Chinese Academy of Sciences (2006). Dissertation: “Molecular phylogenetics and biogeography of Otocephala fish based on multi-nuclear genes.”
  • M.Sc. in Zoology, Southwest China Normal University (2003). Thesis: “Molecular phylogeny of sisorid catfishes and species validity of genus Euchiloglanis in China.”
  • B.Sc. in Zoology, Lanzhou University (1995). Thesis: “Seasonal variations of blood visible components in Eremias multiocellata.”

💼 Professional Experience

  • Associate Professor, Chengdu Institute of Biology, Chinese Academy of Sciences (2009–Present).
  • Assistant Professor, Chengdu Institute of Biology, Chinese Academy of Sciences (2006–2009).

📚 Research Interests on 

Dr. Guo’s main research interests include molecular phylogenetics, biogeography, and evolution. He focuses on reconstructing evolutionary relationships, especially in the Eremias and Phrynocephalus species, using molecular datasets. His studies contribute to understanding the evolutionary history and diversification of these reptiles in arid regions of Central Asia.

🖥️ Technical Skills

  • Expertise in molecular techniques like DNA sequencing and phylogenetic analysis.
  • Proficient in using bioinformatics tools for data analysis and evolutionary studies.

👩‍🏫 Teaching Experience

Dr. Guo has taught various graduate and undergraduate courses related to zoology, molecular biology, and evolutionary studies at the Chengdu Institute of Biology, fostering academic growth and research skills in students.

🔬 Academic Contributions

He has led numerous research projects funded by the National Natural Science Foundation of China (NSFC), focusing on the phylogenetics and molecular basis of species adaptation in arid environments. Dr. Guo has also contributed to international collaborations on the phylogeography and genetic differentiation of reptile species in Central Asia.

🌍 Research Projects

Dr. Guo’s projects include studying the biodiversity and evolutionary patterns of amphibians and reptiles, with an emphasis on the diversity of Eremias and Phrynocephalus in Central Asia’s harsh ecosystems. His work aims to uncover the molecular mechanisms underlying species adaptation and the impact of desertification on biodiversity.

Publication Top Notes

Lineage Diversification and Population Dynamics of the Qinghai Toad-Headed Agama (Phrynocephalus vlangalii) on the Qinghai–Tibet Plateau, with Particular Attention to the Northern Slope of the Kunlun–Arjin Mountains

📑 Authors: Rui Xu, Qi Song, Dali Chen, Xianguang Guo
📰 Journal: Animals
📅 Year: 2025

Lineage Diversification and Population Dynamics of the Qinghai Toad-Headed Agama (Phrynocephalus vlangalii) on the Qinghai-Tibetan Plateau (Preprint)

📑 Authors: Rui Xu, Qi Song, Dali Chen, Xianguang Guo
📰 Journal: Preprint
📅 Year: 2024

Range-Wide Phylogeography and Ecological Niche Modeling Provide Insights into the Evolutionary History of the Mongolian Racerunner (Eremias argus) in Northeast Asia

📑 Authors: Lili Tian, Rui Xu, Dali Chen, Natalia B. Ananjeva, Rafe M. Brown, Mi-Sook Min, Bo Cai, Byambasuren Mijidsuren, Bin Zhang, Xianguang Guo
📰 Journal: Animals
📅 Year: 2024

Genetic Structure and Population History of the Zaisan Toad-Headed Agama (Phrynocephalus melanurus) Inferred from Mitochondrial DNA

📑 Authors: Daniya Ualiyeva, Jinlong Liu, Tatjana Dujsebayeva, Jun Li, Lili Tian, Bo Cai, Xiaomao Zeng, Xianguang Guo
📰 Journal: Animals
📅 Year: 2024

Phylogeography and Ecological Niche Modeling of the Alashan Pit Viper (Gloydius cognatus; Reptilia, Viperidae) in Northwest China and Adjacent Areas

📑 Authors: Rui Xu, Tatjana N. Dujsebayeva, Dali Chen, Byambasuren Mijidsuren, Feng Xu, Xianguang Guo
📰 Journal: Animals
📅 Year: 2023

María Ortiz de Zúñiga | Data Analysis | Best Researcher Award

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Mrs. María Ortiz de Zúñiga | Data Analysis | Best Researcher Award

Mrs. María Ortiz de Zúñiga, UNED and Fusion for Energy, Spain

Publication Profile

Orcid
Google Scholar

🌟 Summary

Mrs. María Ortiz de Zúñiga With over 17 years of experience in Fusion for Energy, I have contributed to various complex, multidisciplinary projects such as the ITER program, leading and managing teams, technical contracts, and large-scale nuclear mechanical systems. My expertise spans across engineering disciplines, including mechanical and computer engineering, and I hold two Master’s degrees in Mechanical Engineering and Computer Engineering. I specialize in project management, leadership, and AI for engineering development, focusing on driving innovation in advanced manufacturing technologies, nuclear safety, and stakeholder management.

🎓 Education

  • Philosopher’s Degree (PhD) in Industrial Technologies
    Universidad Nacional de Educación a Distancia – UNED (2021–Present)
  • Master of Engineering in Mechanical Engineering in Advanced Manufacturing Technologies
    Universidad Nacional de Educación a Distancia – UNED (2017–2021)
  • Master of Engineering in Computer Engineering
    Universidad Pontificia de Comillas – ICAI (2002–2007)

💼 Professional Experience

  • Senior Technical Officer, Fusion for Energy (2022–Present)
    Leading AI for engineering developments in the ITER project, responsible for managing expert contracts and representing F4E in the RCC-MRx nuclear code subcommittee.
  • Deputy Program Manager, Antennas Programme for ITER (2021–2022)
    Managed the design, procurement, and manufacturing of the Electron Cyclotron Antenna, including stakeholder and contract management.
  • Project Manager, ITER Vacuum Vessel Sectors (2019–2021)
    Oversaw the manufacturing of the last 3 European Vacuum Vessel sectors, managing financial, administrative, and technical contract responsibilities.
  • Technical Project Coordinator, ITER Vacuum Vessel (2016–2019)
    Led a team managing technical data, project contracts, and the supply chain for the Vacuum Vessel’s nuclear mechanical systems.
  • Planning Officer, Fusion for Energy (2007–2015)
    Managed planning and scheduling for ITER-related projects, supported risk management, and developed procurement schedules.

📝 Academic Citations

  • Co-chair, Artificial Intelligence Track (CT-19) at ASME-PVP
  • Reviewer at international conferences like SMiRT, ITU, and IAEA
  • Published research on AI in manufacturing and engineering processes for ITER components.

💻 Technical Skills

  • Engineering Software: Proficient in CAD systems, Primavera, Enovia Smarteam PLM, and AI tools for engineering applications.
  • Project Management: Skilled in planning, scheduling, risk management, earned value management, and contract negotiations.
  • Nuclear Safety: Experienced in working with the RCC-MRx code, nuclear safety audits, and quality control for nuclear-related projects.
  • Languages: Fluent in up to 6 European languages.

👩‍🏫 Teaching Experience

  • Co-led the Artificial Intelligence Community within Fusion for Energy to raise awareness and promote AI usage in engineering projects.
  • Actively contributed to Diversity, Equity, and Inclusion initiatives within F4E, supporting training and workshops on these topics.

🔬 Research Interests On Data Analysis

  • Artificial Intelligence for manufacturing optimizations in nuclear components.
  • Data Analysis in high-tech engineering, focusing on predictive models for welding success, ultrasonic testing, and superconducting magnets.
  • Development and integration of advanced manufacturing technologies into nuclear engineering systems.

Publication Top Notes

Project management techniques used in the European Vacuum Vessel sectors procurement for ITER

📑 Authors: M Losasso, MO de Zuniga, L Jones, A Bayon, JF Arbogast, J Caixas, …
📰 Journal: Fusion Engineering and Design
📅 Year: 2012

Artificial Intelligence for the Output Processing of Phased-Array Ultrasonic Test Applied to Materials Defects Detection in the ITER Vacuum Vessel Welding Operations

📑 Authors: M Ortiz de Zuniga, N Prinja, C Casanova, A Dans Alvarez de Sotomayor, …
📰 Journal: Pressure Vessels and Piping Conference
📅 Year: 2022

Artificial Intelligence for quality control in manufacturing applied to materials defects detection in the ITER Vacuum Vessel welding operations

📑 Authors: MO de Zúñiga López-Chicheri, M Febvre, ADA de Sotomayor, N Prinja, …
📰 Journal: IASMiRT
📅 Year: 2022

 

Jean Chamberlain Chedjou | Statistical Analysis | Best Researcher Award

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Assoc Prof Dr. Jean Chamberlain Chedjou | Statistical Analysis | Best Researcher Award

University of Klagenfurt | Austria

Author Profile

Scopus

EARLY ACADEMIC PURSUITS 📚

Assoc. Prof. Dr. Dr.-Ing. Jean Chamberlain Chedjou’s academic journey began with a strong foundation in electronics and physics. After earning his Bachelor’s degree in Physics from the University of Yaoundé, Cameroon, in 1990, he pursued a Bachelor’s Honors degree in Electronics, followed by a Master’s-equivalent DEA in Electronics. His passion for research led him to further his studies, culminating in a Doctorate (Doctorat de troisème cyle) in Electronics at the University of Yaoundé in 1999. Chedjou continued to expand his academic knowledge, attaining a Dr.-Ing. Degree in Electrical Engineering and Information Technology from Leibniz University of Hanover, Germany, in 2004. These early years laid the groundwork for his later contributions in systems optimization, dynamic systems modeling, and traffic simulation.

PROFESSIONAL ENDEAVORS 💼

Dr. Chedjou’s professional journey reflects a commitment to both teaching and research excellence. He started his academic career as a part-time Assistant Lecturer at the University of Yaoundé, followed by various faculty roles at the University of Dschang in Cameroon. His research experience expanded internationally through postdoctoral positions at Université Blaise Pascal, France, and the Abdus Salam International Centre for Theoretical Physics, Italy. These roles were instrumental in shaping his research focus on neural networks, simulation techniques, and dynamic systems modeling. Since 2009, Dr. Chedjou has served as an Associate Professor at Alpen-Adria-Universität Klagenfurt, Austria, where he has continued to excel in research and teaching.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Dr. Chedjou’s research is deeply centered on optimization in graph networks, particularly the development of neuro-processor solvers aimed at ultra-fast solutions for classical graph theoretical problems such as the Shortest Path Problem (SPP), Traveling Salesman Problem (TSP), and Minimum Spanning Tree (MST). He integrates his expertise in neural networks and cellular neural networks to advance simulation and optimization techniques, applying them to real-world challenges in systems simulation and nonlinear dynamics.

His work also extends to traffic modeling, electronic circuit design, and the analog computation of stiff differential equations, where his innovative approaches enhance the efficiency of simulation models. Moreover, Dr. Chedjou investigates the nonlinear dynamics of complex systems, addressing equilibrium states, chaos detection, and stability analysis, furthering understanding in fields like system theory, engineering, and telecommunications.

IMPACT AND INFLUENCE 🌍

Dr. Chedjou’s contributions have significantly impacted the academic and research communities, particularly in the areas of transportation informatics and systems modeling. His research in ultra-fast solvers and neurocomputing has paved the way for more efficient solutions to complex optimization problems. As an Associate Professor at Alpen-Adria-Universität Klagenfurt, his courses on methods of transportation informatics and simulation techniques have inspired countless students to explore these domains. His role as a mentor has helped shape future leaders in the field of systems technologies.

Additionally, Dr. Chedjou’s involvement in global research collaborations—such as his fellowships with the Abdus Salam International Centre for Theoretical Physics—demonstrates his commitment to international knowledge exchange and the advancement of applied sciences.

ACADEMIC CITATIONS AND RECOGNITIONS 🏅

Dr. Chedjou’s academic contributions are well-recognized globally. His innovative work in graph theory and simulation has earned him a place among respected researchers in his field. His commitment to excellence in teaching was highlighted in 2013 when he was honored with the Best Lecturer award at the University of Klagenfurt, a testament to his ability to convey complex concepts effectively and engage students in meaningful learning.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

Dr. Chedjou’s legacy is defined by his pioneering research and his dedication to advancing the fields of optimization, dynamic systems, and transportation informatics. His current focus on neurocomputing for real-time simulation and optimization of nonlinear differential equations promises to influence various industries, from transportation to telecommunications.

Looking ahead, Dr. Chedjou continues to push the boundaries of systems simulation and modeling. His work on neuro-processor solvers and cellular neural networks is poised to revolutionize problem-solving strategies in complex networks, contributing to faster and more scalable solutions for modern engineering challenges. As a mentor, researcher, and academic, Dr. Chedjou’s future contributions will undoubtedly continue to inspire and shape the next generation of innovators and scholars.

📑 NOTABLE PUBLICATIONS 

Article: Impact of source (drain) doping profiles and channel doping level on self-heating effect in FinFET

Authors: Atamuratov, A.E., Jabbarova, B.O., Khalilloev, M.M., Blugan, G., Saidov, K.
Journal: Micro and Nanostructures
Year: 2025

Article: A special memristive diode-bridge-based hyperchaotic hyperjerk autonomous circuit with three positive Lyapunov exponents

Authors: Rong, X., Chedjou, J.C., Yu, X., Jiang, D., Kengne, J.
Journal: Chaos, Solitons and Fractals
Year: 2024

Article: Complex dynamic behaviors in a small network of three ring coupled Rayleigh-Duffing oscillators: Theoretical study and circuit simulation

Authors: Kamga Fogue, S.M., Kana Kemgang, L., Kengne, J., Chedjou, J.C.
Journal: International Journal of Non-Linear Mechanics
Year: 2024

Article: Coupling Induced Dynamics in a Chain-Network of Four Two-Well Duffing Oscillators: Theoretical Analysis and Microcontroller-Based Experiments

Authors: Venkatesh, J., Karthikeyan, A., Chedjou, J.C., Jacques, K., Karthikeyan, R.
Journal: Journal of Vibration Engineering and Technologies
Year: 2024

Article: A unique self-driven 5D hyperjerk circuit with hyperbolic sine function: Hyperchaos with three positive exponents, complex transient behavior and coexisting attractors

Authors: Vivekanandhan, G., Chedjou, J.C., Jacques, K., Rajagopal, K.
Journal: Chaos, Solitons and Fractals
Year: 2024

Alireza sobbouhi | Predictive Modeling Innovations | Best Researcher Award

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Dr. Alireza sobbouhi | Predictive Modeling Innovations | Best Researcher Award

shahid beheshti university | Iran

Author Profile

Early Academic Pursuits 📚

Dr. Alireza Sobbouhi’s academic journey began at Shahid Beheshti University in Iran, where he developed a strong foundation in mathematics, statistics, and computational sciences. His early fascination with complex systems and data-driven decision-making led him to specialize in predictive modeling. This interest propelled him into graduate studies, where he focused on developing and applying sophisticated techniques for forecasting and analyzing data.

Professional Endeavors 💼

Dr. Sobbouhi’s career blends academic achievements with professional success. As a professor at Shahid Beheshti University, he has been deeply involved in teaching, research, and industry collaboration. His role in academia extends beyond teaching as he works on impactful projects that link predictive modeling with real-world applications, from healthcare to finance. His expertise has also made him a sought-after consultant, furthering his reach and influence in both academia and industry.

Contributions and Research Focus On Predictive Modeling Innovations🔬

Dr. Sobbouhi’s research is rooted in the advancement of predictive modeling. His contributions have introduced new methodologies to improve the accuracy and efficiency of data analysis in various domains. Some key areas of focus include:

  • Development of Predictive Algorithms: Crafting algorithms that provide more precise predictions in economic, healthcare, and environmental sectors.
  • Machine Learning Integration: Exploring ways to integrate machine learning techniques into predictive models for better data interpretation and forecasting.
  • Big Data Analytics: Focusing on scalable approaches to handle and analyze massive datasets to uncover patterns that traditional models might miss.

Impact and Influence 🌍

Dr. Sobbouhi’s work has had a profound impact, not only in academia but also across various industries. His innovative contributions to predictive modeling and machine learning have influenced numerous researchers and professionals in fields ranging from economics to environmental science. His approach to enhancing model reliability and interpretability has set new standards and inspired further research in data science. The applications of his work continue to improve decision-making processes worldwide.

Academic Cites 📑

Dr. Sobbouhi’s research has been extensively cited in scholarly articles, journals, and conferences, indicating the high regard in which his work is held. His studies on predictive analytics and statistical modeling have been foundational, influencing a wide range of studies in machine learning and data science. The frequency of his citations reflects the relevance and significance of his contributions to the broader scientific community.

Technical Skills 🧑‍💻

Dr. Sobbouhi possesses a diverse and deep technical skill set that includes:

  • Programming: Expertise in Python, R, and MATLAB for data analysis and modeling.
  • Statistical Modeling: Advanced proficiency in developing and applying statistical techniques for prediction and forecasting.
  • Machine Learning: Expertise in applying machine learning algorithms to large datasets to uncover trends and make predictions.
  • Data Visualization: Strong skills in visualizing complex datasets to facilitate understanding and decision-making.

These technical competencies allow him to tackle complex datasets and develop state-of-the-art predictive models.

Teaching Experience 🏫

As an educator, Dr. Sobbouhi has taught a variety of courses on statistics, data science, and machine learning at Shahid Beheshti University. His teaching style blends theoretical knowledge with practical applications, ensuring students are well-prepared for the real-world challenges of the data science field. Dr. Sobbouhi has also supervised many graduate students, guiding them in their research and helping to shape the next generation of data scientists.

Legacy and Future Contributions 🔮

Dr. Sobbouhi’s legacy is built on his innovative contributions to predictive modeling and data science. His ability to bridge the gap between academic theory and industry application has had a lasting influence on both fields. Looking ahead, Dr. Sobbouhi is expected to continue making groundbreaking advancements in predictive analytics, particularly in the integration of AI and machine learning into real-world applications. His future research will likely shape the development of new predictive tools, influencing a wide range of industries for years to come.

Notable Publications  📑 

A novel predictor for areal blackout in power system under emergency state using measured data
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2025
A novel SVM ensemble classifier for predicting potential blackouts under emergency condition using on-line transient operating variables
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2025 (April issue)
Transient stability improvement based on out-of-step prediction
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2021
Transient stability prediction of power system; a review on methods, classification and considerations
    • Authors: Not provided in the source, but typically listed in the full article.
    • Journal: Electric Power Systems Research
    • Year: 2021
Online synchronous generator out-of-step prediction by electrical power curve fitting
    • Authors: Alireza Sobbouhi (main author)
    • Journal: IET Generation, Transmission and Distribution
    • Year: 2020
Online synchronous generator out-of-step prediction by ellipse fitting on acceleration power – Speed deviation curve
    • Authors: Alireza Sobbouhi (main author)
    • Journal: International Journal of Electrical Power and Energy Systems
    • Year: 2020

Youmna Iskandarani | Machine Learning | Best Researcher Award

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Ms. Youmna Iskandarani l Machine Learning | Best Researcher Award

American University of Beirut, Lebanon

Author Profile

Orcid

EARLY ACADEMIC PURSUITS 🎓

Youmna Iskandarani’s academic journey laid a robust foundation for her career in food science and technology. She earned her Bachelor’s degree in Dietetics and Clinical Nutrition Services from Lebanese International University, followed by a Bachelor of Applied Science in Food Science and Technology. Building on this knowledge, she pursued a Master of Science in Food Science and Technology, which further refined her expertise in food processing, safety, and research. During her studies, she also explored economics, expanding her understanding of the broader socio-economic factors influencing food systems.

PROFESSIONAL ENDEAVORS 💼

Youmna’s professional trajectory spans over a decade and includes a wealth of experience in community development, food technology, and business development. As the founder of Ossah Taybeh, a food heritage initiative, she has demonstrated her leadership in promoting sustainable food practices. Additionally, her role as a business development consultant and food expert for various organizations, including the World Food Programme (WFP) and UNDP, highlights her expertise in improving the socio-economic conditions of small and medium enterprises (SMEs) in Lebanon. Youmna has also worked with institutions like the American University of Beirut, where she contributed to food safety training, product development, and innovative food solutions. Her consulting work for international organizations and governments underscores her technical expertise in food processing, quality control, and business strategy.

CONTRIBUTIONS AND RESEARCH FOCUS  On  Machine Learning🔬

Throughout her career, Youmna has been at the forefront of several groundbreaking projects in food science and technology. She has published significant research, including studies on ADHD and nutrition, the production procedures of labneh anbaris (a traditional Lebanese yogurt), and food security. Her research in food safety, quality control, and food product development, especially in the dairy sector, has made substantial contributions to understanding the physicochemical properties of traditional food products. Additionally, her work in food safety, particularly related to cross-contamination prevention and dairy production processes, has helped improve the standards of food processing in Lebanon and beyond.

IMPACT AND INFLUENCE 🌍

Youmna’s impact extends far beyond her professional roles; she has become a key figure in advancing food safety and quality practices in Lebanon. As a consultant and trainer, she has helped develop and implement strategies that enhance the livelihoods of farmers and small business owners in rural and urban communities. Her work with the International Labour Organization (ILO) and various NGOs has supported entrepreneurial initiatives aimed at creating sustainable economic opportunities. Her efforts in building the capacity of SMEs and promoting socially impactful business practices have earned her recognition as a leader in both the food industry and community development sectors. Moreover, her role as a mentor and trainer for aspiring entrepreneurs has inspired many to develop their own successful ventures.

ACADEMIC CITATIONS AND RECOGNITION 🏅

Youmna’s research has been widely cited in academic circles, contributing to the fields of food science and public health. Her work on the physicochemical properties of labneh anbaris and her studies in the areas of food security and nutrition have been valuable in shaping food safety protocols and product development in Lebanon. She is recognized for her expertise in food technology and food safety, as well as for her commitment to advancing the quality and sustainability of food production systems in Lebanon and the broader region. Her contributions have made her a sought-after consultant and expert in various food safety and quality assurance projects.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

Looking forward, Youmna Iskandarani is poised to continue making meaningful contributions to the fields of food science, business development, and community empowerment. Her passion for sustainability and rural development, combined with her technical expertise in food safety and quality assurance, will continue to guide her efforts in enhancing food systems and promoting socio-economic growth. Her vision for the future includes empowering more women and SMEs in the agri-food sector, improving the resilience of local food production systems, and advocating for healthier, safer, and more sustainable food practices. Youmna’s legacy will be built on her commitment to food security, innovation, and the betterment of her community and the global food industry.

 Top Noted Publications 📖

Microbial Quality and Production Methods of Traditional Fermented Cheeses in Lebanon

Authors: Mabelle Chedid, Houssam Shaib, Lina Jaber, Youmna El Iskandarani, Shady Kamal Hamadeh, Ivan Salmerón
Journal: International Journal of Food Science
Year: 2025

Machine Learning Method (Decision Tree) to Predict the Physicochemical Properties of Premium Lebanese Kishk Based on Its Hedonic Properties

Authors: Ossama Dimassi, Youmna Iskandarani, Houssam Shaib, Lina Jaber, Shady Hamadeh
Journal: Fermentation
Year: 2024

Development and Validation of an Indirect Whole-Virus ELISA Using a Predominant Genotype VI Velogenic Newcastle Disease Virus Isolated from Lebanese Poultry

Authors: Houssam Shaib, Hasan Hussaini, Roni Sleiman, Youmna Iskandarani, Youssef Obeid
Journal: Open Journal of Veterinary Medicine
Year: 2023

Effect of Followed Production Procedures on the Physicochemical Properties of Labneh Anbaris

Authors: Ossama Dimassi, Youmna Iskandarani, Raymond Akiki
Journal: International Journal of Environment, Agriculture and Biotechnology
Year: 2020

Production and Physicochemical Properties of Labneh Anbaris, a Traditional Fermented Cheese Like Product, in Lebanon

Authors: Ossama Dimassi, Youmna Iskandarani, Michel Afram, Raymond Akiki, Mohamed Rached
Journal: International Journal of Environment, Agriculture and Biotechnology
Year: 2020

Mohammed Abdullah Alshahrani | Statistics | Best Researcher Award

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Dr. Mohammed Abdullah Alshahrani l Algorithm Development  | Best Researcher Award

Prince Sattam Bin Abdulaziz University, Saudi Arabia

Author Profile

Scopus

Orcid

EARLY ACADEMIC PURSUITS 🎓

Mohammed Abdullah Alshahrani’s academic journey began with a solid foundation in mathematics. His undergraduate studies at Bisha University in Saudi Arabia, culminating in a BSc in Mathematics with honors, set the stage for his future endeavors. His passion for applied statistics grew during his studies at King Saud University, where he earned a Diploma of MSc in Mathematics with exceptional academic performance. This dedication to mathematics led him to the University of Arkansas in the USA, where he completed his MSc in Applied Statistics with a remarkable GPA of 3.85 out of 4. Alshahrani continued his academic excellence by pursuing a PhD in Applied Statistics at the University of Leeds in the UK, focusing on statistical models and their applications.

PROFESSIONAL ENDEAVORS 💼

Alshahrani’s professional career is marked by significant achievements across academia and industry. As an Assistant Professor at Prince Sattam Bin Abdulaziz University, he has demonstrated his expertise in applied statistics by teaching and supervising various statistical courses and graduation projects. Additionally, his role as a consultant in statistics and data science at the Institute of Research and Consulting Services at the same university highlights his ability to bridge academia and practical problem-solving in fields like genetics, financial data analysis, and high-dimensional datasets.

His experience extends beyond academia to notable positions in national institutions. At the General Authority for Statistics, he worked as a Big Data Expert and later as the Director of the Innovation Lab, where he led various projects related to big data, mobile positioning, and satellite data analysis, contributing to national initiatives such as the Household Income and Expenditure Survey and the Real Estate Price Index. He also played a key role in the creation of automated systems for data error detection and the calculation of socioeconomic indices.

CONTRIBUTIONS AND RESEARCH FOCUS  On Statistics🔬

Alshahrani’s research has largely revolved around the application of statistical methods like regression, classification, and clustering to various domains. His work in applied statistics has spanned several fields, including genetics, financial analysis, and public policy. By developing statistical models and utilizing big data techniques, Alshahrani has made significant strides in areas like the Consumer Price Index (CPI) calculation, energy surveys, and the development of machine learning models for outlier detection. His contributions to academic conferences, workshops, and publications, such as those in the areas of deep learning, drought analysis, and plant disease classification, demonstrate his versatile application of statistical techniques to real-world problems.

IMPACT AND INFLUENCE 🌍

Alshahrani’s work has had a profound impact on the academic community, public policy, and the private sector. His research contributions, including new sine-induced statistical models and deep learning applications, have influenced how complex datasets are analyzed and interpreted. His involvement in high-profile projects, such as the Household Income and Expenditure Survey and the real estate index, has provided actionable insights for Saudi Arabia’s economic and social policies. As a speaker at international conferences and a workshop leader, Alshahrani has become a thought leader in the field of applied statistics and data science, sharing his knowledge and inspiring others to explore these areas.

ACADEMIC CITATIONS AND RECOGNITION 🏅

Alshahrani’s scholarly impact is reflected in his numerous publications in esteemed journals. His work on various statistical models and data analysis techniques has been cited in academic circles and has contributed to the advancement of applied statistics. Through his leadership in both educational and professional settings, he has gained recognition for his innovative approaches to solving statistical problems, particularly in areas like public health, economics, and environmental studies. His publications, such as the development of a new drought index and fuzzy adaptive control charts, underscore his ability to combine theoretical research with practical applications.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

As Alshahrani continues to shape the future of applied statistics, his legacy is one of innovation, mentorship, and the pursuit of excellence. His ongoing work in academia and consultancy positions him to influence future generations of statisticians and data scientists. With a passion for developing statistical methods and building data-driven solutions for societal challenges, Alshahrani is poised to make lasting contributions to both the academic field and public policy. His focus on AI, machine learning, and the development of statistical software packages, along with his interest in R Shiny applications, indicates that his future contributions will continue to push the boundaries of statistical analysis and its applications in real-world problems.

 Top Noted Publications 📖

  • On predictive modeling of the twitter-based sales data using a new probabilistic model and machine learning methods
    • Authors: Wan, M., Alshahrani, M.A., Aloraini, N.M., Alkhathami, A.A., Alqahtani, H.
    • Journal: Alexandria Engineering Journal
    • Year: 2025
  • A Fuzzy Adaptive Control Chart as an Alternative to Neutrosophic Techniques for Handling Imprecise Data
    • Authors: Alshahrani, M.A., Khan, I., Sumelka, W.
    • Journal: International Journal of Neutrosophic Science
    • Year: 2025
  • A new probabilistic model: Its implementations to time duration and injury rates in physical training, sports, and reliability sector
    • Authors: Lu, G., Alamri, O.A., Alnssyan, B., Alshahrani, M.A.
    • Journal: Alexandria Engineering Journal
    • Year: 2024
  • Development of maximum relevant prior feature ensemble (MRPFE) index to characterize future drought using global climate models
    • Authors: Gul, A., Qamar, S., Yousaf, M., Alshahrani, M., Hilali, S.O.
    • Journal: Scientific Reports
    • Year: 2024
  • A support vector machine based drought index for regional drought analysis
    • Authors: Alshahrani, M., Laiq, M., Noor-ul-Amin, M., Yasmeen, U., Nabi, M.
    • Journal: Scientific Reports
    • Year: 2024

Amin Hekmatmanesh | Algorithm Development | Best Researcher Award

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Dr. Amin Hekmatmanesh l Algorithm Development  | Best Researcher Award

LUT University, Finland

Author Profile

Google Scholar

🔎 Summary

Dr. Amin Hekmatmanesh is a skilled biomedical engineer and data scientist, specializing in wearable sensors, AI, and machine learning applications for health technologies. He has extensive experience in biosignal processing (EEG, ECG, PPG, EMG, GSR, IMU), rehabilitation robotics, and medical device development. With a Ph.D. in Mechanical Engineering (Biomedical Engineering), he has made significant contributions to the field by developing real-time systems for rehabilitation and health monitoring. His research focuses on using AI to advance rehabilitation robotics and human-robot interactions, publishing over 30 peer-reviewed articles. He is also an active reviewer and editorial board member for several high-ranking journals.

🎓 Education

Dr. Hekmatmanesh holds a Ph.D. in Mechanical Engineering (Biomedical Engineering) from LUT University in Finland, where he achieved a GPA of 4.33. His dissertation focused on artificial intelligence and machine learning for EEG signal processing in rehabilitation robotics. He also completed his M.Sc. in Biomedical Engineering at Shahed University in Iran, with a perfect GPA of 4.0, and a B.Sc. in Electrical Engineering from Islamic Azad University, graduating with a GPA of 4.1.

💼 Professional Experience

Dr. Hekmatmanesh has a diverse professional background, having worked as a Lead Project Manager at Mevea Company, where he managed health monitoring system projects, incorporating wearable sensor technology. At Flowgait Company, he contributed to mathematical solutions for horse motion analysis. As a Junior Researcher and Project Manager at LUT University, he focused on wearable sensor systems and health monitoring. Additionally, he worked as a Research Assistant at Tehran University, working on diagnostic algorithms and therapeutic systems in health technologies.

📚 Academic Citations

Dr. Hekmatmanesh has published over 30 peer-reviewed papers, including book chapters and review articles, and his work has contributed significantly to the biomedical engineering and AI fields. His research has received wide recognition, and he is regularly invited to participate in scientific conferences and review for high-impact journals, showcasing his influence and contributions to advancing health technologies.

🔧 Technical Skills

Dr. Hekmatmanesh is highly proficient in biosignal processing, including EEG, ECG, PPG, EMG, GSR, and IMU signals. He is skilled in machine learning and AI, specifically for biosignal classification and real-time system development. His technical expertise extends to embedded electronics, sensor design, and circuit board assembly. He is proficient in Python and Matlab for data analysis and has experience using version control tools like GitHub to manage research projects.

🎓 Teaching Experience

Dr. Hekmatmanesh has been actively involved in teaching and mentoring within the biomedical engineering field. He has supervised PhD students and contributed to academic programs by delivering lectures and guiding research projects in health technologies, machine learning, and rehabilitation robotics.

🔬 Research Interests On Algorithm Development

Dr. Hekmatmanesh’s research interests include the development of wearable sensor systems for health monitoring, AI and machine learning techniques for biosignal classification, and the design and control of rehabilitation robotics. He is also focused on human-robot interactions and improving prosthetics control through innovative AI applications in healthcare.

📖 Top Noted Publications

Nanocaged platforms: modification, drug delivery and nanotoxicity. Opening synthetic cages to release the tiger
    • Authors: PS Zangabad, M Karimi, F Mehdizadeh, H Malekzad, A Ghasemi, …
    • Journal: Nanoscale
    • Year: 2017
Review of the state-of-the-art of brain-controlled vehicles
    • Authors: A Hekmatmanesh, PHJ Nardelli, H Handroos
    • Journal: IEEE Access
    • Year: 2021
Neurosciences and wireless networks: The potential of brain-type communications and their applications
    • Authors: RC Moioli, PHJ Nardelli, MT Barros, W Saad, A Hekmatmanesh, …
    • Journal: IEEE Communications Surveys & Tutorials
    • Year: 2021
A combination of CSP-based method with soft margin SVM classifier and generalized RBF kernel for imagery-based brain computer interface applications
    • Authors: A Hekmatmanesh, H Wu, F Jamaloo, M Li, H Handroos
    • Journal: Multimedia Tools and Applications
    • Year: 2020
EEG control of a bionic hand with imagination based on chaotic approximation of largest Lyapunov exponent: A single trial BCI application study
    • Authors: A Hekmatmanesh, RM Asl, H Wu, H Handroos
    • Journal: IEEE Access
    • Year: 2019

Omar Haddad | Artificial Intelligence | Best Researcher Award

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Dr. Omar Haddad l Artificial Intelligence | Best Researcher Award

MARS Research Lab, Tunisia

Author Profile

Google Scholar

🎓 Early Academic Pursuits

Dr. Omar Haddad began his academic journey with a solid foundation in mathematics, earning his Bachelor in Mathematics from Mixed High School, Tataouine North, Tunisia, in 2008. Building on this, he pursued a Fundamental License in Computer Science at the Faculty of Sciences of Monastir, University of Monastir, Tunisia, graduating with honors in 2012. He further honed his skills in advanced topics through a Research Master in Computer Science specializing in Modeling of Automated Reasoning Systems (Artificial Intelligence) at the same institution, completing his thesis on E-Learning, NLP, Map, and Ontology in 2016. This laid the groundwork for his doctoral studies in Big Data Analytics for Forecasting Based on Deep Learning, which he completed with highest honors at the Faculty of Economics and Management of Sfax, University of Sfax, Tunisia, in 2023.

💼 Professional Endeavors

Currently, Dr. Haddad is an Assistant Contractual at the University of Sousse, Tunisia, where he contributes to the academic and technological growth of the institution. He is a dedicated member of the MARS Research Laboratory at the University of Sousse, where he collaborates on cutting-edge projects in Artificial Intelligence and Big Data Analytics. His professional expertise extends to teaching across various levels, including preparatory, license, engineer, and master levels, with over 2,000 hours of teaching experience in state and private institutions.

📚 Contributions and Research Focus

Dr. Haddad’s research spans several transformative domains, including:

  • Artificial Intelligence (AI) and its application in solving complex problems.
  • Machine Learning (ML) and Deep Learning (DL) for advanced predictive modeling.
  • Generative AI and Large Language Models (LLMs) for innovation in Natural Language Processing (NLP).
  • Big Data Analytics for informed decision-making and forecasting.
  • Computer Vision for visual data interpretation and insights.

He has published three significant contributions in Q1 and Q2 journals and participated in Class C conferences, highlighting his commitment to impactful and high-quality research.

🌟 Impact and Influence

As a peer reviewer for prestigious journals like The Journal of Supercomputing, Journal of Electronic Imaging, SN Computer Science, and Knowledge-Based Systems, Dr. Haddad ensures the integrity and quality of academic contributions in his field. His work has influenced a diverse range of domains, from computer science education to applied AI, establishing him as a thought leader in his areas of expertise.

🛠️ Technical Skills

Dr. Haddad possesses a robust set of technical skills, including:

  • Proficiency in Deep Learning frameworks and Big Data tools.
  • Expertise in programming languages such as Python and C.
  • Knowledge of Database Engineering and algorithms.
  • Application of Natural Language Processing (NLP) in academic and industrial projects.

👨‍🏫 Teaching Experience

Dr. Haddad has an extensive teaching portfolio, covering a wide range of topics:

  • Database Engineering, Algorithms, and Programming, taught across license and engineer levels.
  • Advanced topics such as Big Data Frameworks, Foundations of AI, and Object-Oriented Programming.
  • Specialized courses on Information and Communication Technologies in Teaching and Learning.

His dedication to education is evident in his ability to adapt teaching strategies to different academic levels and institutional needs.

🏛️ Legacy and Future Contributions

Dr. Haddad’s legacy lies in his ability to bridge academia and industry through innovative research and teaching. As he continues to expand his expertise in Generative AI and LLMs, his future contributions will likely shape the next generation of intelligent systems and predictive analytics. His goal is to inspire students and researchers to harness the transformative potential of AI and Big Data to address global challenges.

🌐 Vision for the Future

Dr. Omar Haddad envisions a future where AI and Big Data technologies are seamlessly integrated into various sectors to enhance decision-making, foster innovation, and empower global communities. By combining his teaching, research, and technical skills, he aims to leave a lasting impact on the academic and technological landscape.

📖 Top Noted Publications
Toward a Prediction Approach Based on Deep Learning in Big Data Analytics
    • Authors: O. Haddad, F. Fkih, M.N. Omri
    • Journal: Neural Computing and Applications
    • Year: 2022
A Survey on Distributed Frameworks for Machine Learning Based Big Data Analysis
    • Authors: O. Haddad, F. Fkih, M.N. Omri
    • Journal: Proceedings of the 21st International Conference on New Trends in Intelligent Software Systems
    • Year: 2022
An Intelligent Sentiment Prediction Approach in Social Networks Based on Batch and Streaming Big Data Analytics Using Deep Learning
    • Authors: O. Haddad, F. Fkih, M.N. Omri
    • Journal: Social Network Analysis and Mining
    • Year: 2024
Big Textual Data Analytics Using Transformer-Based Deep Learning for Decision Making
    • Authors: O. Haddad, M.N. Omri
    • Journal: Proceedings of the 16th International Conference on Computational Collective Intelligence
    • Year: 2024