Alireza sobbouhi | Predictive Modeling Innovations | Best Researcher Award

Posted on by ScienceFather

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

shahid beheshti university | Iran

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

Posted on by ScienceFather

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 SalmerĂłn
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

Naiwei Lu | Data Analysis | Best Researcher Award

Posted on by ScienceFather

Assoc Prof Dr. Naiwei Lu | Data Analysis | Best Researcher Award

Changsha University of Science of Technology, China

Author Profiles

Orcid

Scopus

Research Gate

👨‍🏫 Associate Prof. Dr. Naiwei Lu

Assoc. Prof. Dr. Naiwei Lu is an Associate Professor in Civil Engineering at Changsha University of Science and Technology (CSUST), China. His research primarily focuses on reliability and safety in bridge engineering. He has a strong background in system reliability evaluation, fatigue analysis, and structural health monitoring, which he applies to the engineering and maintenance of long-span bridges. Dr. Lu is an active member of various international research communities and has been involved in multiple national and international projects.

🎓 Education Background

Dr. Naiwei Lu earned his Ph.D. in Civil Engineering from Changsha University of Science and Technology (CSUST) in 2015, under the supervision of Prof. Yang Liu. Prior to that, he completed his Master’s degree in Civil Engineering in 2011 and his Bachelor’s degree in Bridge Engineering in 2008, all at CSUST, Changsha, China. His academic journey laid a strong foundation for his expertise in bridge engineering and reliability analysis.

💼 Employment and Research Experience

Dr. Lu’s academic career began in 2015 when he became a Postdoctoral Researcher at Southeast University in Nanjing, China, where he worked under Prof. Mohammad Noori. He also held a Postdoctoral Researcher position at Leibniz University Hannover, Germany, working with Prof. Michael Beer. Since 2020, Dr. Lu has been serving as an Associate Professor at CSUST, where he also previously worked as a Lecturer from 2017 to 2019. His diverse academic and international experiences contribute to his deep expertise in bridge engineering.

💰 Research Funding

Dr. Lu has been the Principal Investigator (PI) of several funded research projects, including the National Science Funding in China for research on structural health monitoring of suspension bridges and the fatigue reliability evaluation of steel bridge decks. He has received significant funding support for his work in system reliability and dynamic analysis, with total funding exceeding ÂĽ1 million for his various research initiatives. These projects aim to develop advanced methods for assessing the reliability and safety of long-span bridges.

🔍 Research Interests

Dr. Lu’s research spans several cutting-edge topics in structural engineering. His main research interests include system reliability evaluation of long-span bridges using intelligent algorithms 🤖, fatigue reliability of stay cables and orthotropic steel bridge decks 🌉, and probabilistic modeling using data from structural health monitoring 📊. He is also focused on intelligent maintenance and management of in-service bridges ⚙️, as well as uncertainty quantification in structural engineering 🛠️.

📚 Teaching Experience

As an educator, Dr. Lu teaches undergraduate courses such as Principle of Structural Design (in both Chinese and English) and Building Information Modeling (BIM) Technology (in Chinese). He has supervised 24 undergraduate students and 4 postgraduate students between 2017 and 2020, guiding them in various aspects of civil engineering, particularly related to bridge design, maintenance, and reliability.

🏗️ Engineering Activities

In addition to his academic role, Dr. Lu is a Registered Construction Engineer and a Registered Inspection Engineer in Municipal Engineering and Bridge & Tunnel Engineering, respectively. His engineering activities include overseeing the structural safety of long-span bridges during construction 🏗️, conducting structural health monitoring of suspension bridges 🌉, and contributing to the detection and reinforcement of aging bridges 🛠️. He has also been involved in the advance geological forecasting and monitoring of tunnels during construction, working on over five extra-long tunnels.

Dr. Naiwei Lu’s work integrates advanced intelligent algorithms, data-driven methods, and structural health monitoring to enhance the safety, reliability, and longevity of bridges and infrastructure systems. His research and engineering expertise continue to make significant contributions to the field of civil engineering.

📖Top Noted Publications 

Structural damage diagnosis of a cable-stayed bridge based on VGG-19 networks and Markov transition field: numerical and experimental study

Authors: Naiwei Lu, Zengyifan Liu, Jian Cui, Lian Hu, Xiangyuan Xiao, Yiru Liu

Journal: Smart Materials and Structures

Year: 2025

Coupling effect of cracks and pore defects on fatigue performance of U-rib welds

Authors: Yuan Luo, Xiaofan Liu, Fanghuai Chen, Haiping Zhang, Xinhui Xiao, Naiwei Lu

Journal: Structures

Year: 2025

A Time–Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen

Authors: Naiwei Lu, Yiru Liu, Jian Cui, Xiangyuan Xiao, Yuan Luo, Mohammad Noori

Journal: Sensors

Year: 2024

A Novel Method of Bridge Deflection Prediction Using Probabilistic Deep Learning and Measured Data

Authors: Xinhui Xiao, Zepeng Wang, Haiping Zhang, Yuan Luo, Fanghuai Chen, Yang Deng, Naiwei Lu, Ying Chen

Journal: Sensors

Year: 2024

Experimental and numerical investigation on penetrating cracks growth of rib-to-deck welded connections in orthotropic steel bridge decks

Authors: Zitong Wang, Jun He, Naiwei Lu, Yang Liu, Xinfeng Yin, Haohui Xin

Journal: Structures

Year: 2024

Fatigue Reliability Assessment for Orthotropic Steel Decks: Considering Multicrack Coupling Effects

Authors: Jing Liu, Yang Liu, Guodong Wang, Naiwei Lu, Jian Cui, Honghao Wang

Journal: Metals

Year: 2024

Biying Fu | Machine Learning Applications | Best Researcher Award

Posted on by ScienceFather

Dr. Biying Fu | Machine Learning Applications | Best Researcher Award

Hochschule RheinMain, Germany

Professional Profile👨‍🎓

Early Academic Pursuits 📚

Dr. Biying Fu’s academic journey began with her primary and secondary education in Shanghai, China, where she developed a strong foundation in subjects like mathematics, German, English, physics, and chemistry. Her academic excellence continued through high school, culminating in an outstanding Abitur score of 1.1. She pursued a Bachelor’s degree in Electrical Engineering and Information Technology at Karlsruhe Institute of Technology (KIT), Germany, followed by a Master’s degree with a focus on Communications and Information Technology. Dr. Fu’s academic pursuits further advanced with a Ph.D. from the Technical University of Darmstadt (TUda), where she specialized in sensor applications for human activity recognition in smart environments.

Professional Endeavors 💼

Dr. Fu’s professional career began at the Fraunhofer Institute for Integrated Circuits (IGD), where she contributed significantly to the Sensing and Perception group. Over time, she expanded her expertise into the Smart Living and Biometric Technologies department, becoming a scientific employee and project leader. Her roles included innovative work on smart environments, human activity recognition, and biometric technologies. Dr. Fu has been instrumental in creating real-world applications for sensor technologies and machine learning algorithms, with notable contributions to the Smart Floor project, which focuses on indoor localization and emergency detection in ambient assisted living environments.

Contributions and Research Focus 🔬

Dr. Fu’s research has been centered around smart environments, sensor systems, and human activity recognition. Her dissertation, titled “Sensor Applications for Human Activity Recognition in Smart Environments,” examined multimodal sensor systems, including capacitive sensors, accelerometers, and smartphone microphones, for tracking physical activities and indoor localization. Her work merges signal processing, neural networks, and data generation techniques to enhance the interaction between people and machines. Her ongoing research continues to explore the intersection of artificial intelligence and explainability, contributing to the development of transparent and interpretable machine learning models.

Impact and Influence 🌍

Dr. Fu’s research in smart technologies has far-reaching implications for assistive technologies, healthcare, and the development of intuitive human-machine interactions. Her contributions to the field of human activity recognition have improved how we use sensors to monitor and analyze daily activities in smart homes and health environments. Furthermore, her involvement in interdisciplinary projects, such as optical quality control and optical medication detection, has enhanced industrial applications of computer vision and machine learning.

Academic Cites and Recognition 📖

Dr. Fu has earned recognition in both academia and industry. Her dissertation, publications, and research projects have attracted attention in top conferences and journals. Her participation in global programs like the Summer School of Deep Learning and Reinforcement Learning at the University of Alberta further emphasizes her standing in the scientific community. Additionally, Dr. Fu has been an active participant in various educational and research initiatives, such as the REQUAS project, and she continues to serve as a professor at Hochschule RheinMain, where she focuses on the emerging field of Explainable AI.

Technical Skills ⚙️

Dr. Fu possesses advanced technical skills in various programming languages, including C/C++, Java, and Python. She is highly proficient in machine learning libraries such as Scikit-Learn, TensorFlow, Keras, and PyTorch, and has hands-on experience with simulation tools like Matlab/Simulink and CST Microwave Studio. Her expertise extends to signal processing, computer vision, and the use of embedded systems for smart applications. Additionally, Dr. Fu has a strong command of version control tools like GIT and SVN, as well as project management platforms such as JIRA and SCRUM.

Teaching Experience 👩‍🏫

Dr. Fu has contributed to the academic development of students through various teaching roles. She has served as a tutor for subjects like digital technology and wave theory during her time at KIT. As a professor at Hochschule RheinMain, she currently teaches courses in smart environments, with a focus on advanced topics in Explainable AI. Her ability to communicate complex concepts clearly and her passion for fostering intellectual curiosity have made her a respected educator in her field.

Legacy and Future Contributions 🌟

Dr. Fu’s work continues to shape the future of smart environments, human-machine interactions, and explainable AI. Her research on sensor technologies and machine learning has paved the way for smarter and more intuitive technologies in healthcare, industry, and everyday life. As she continues to contribute to both academic and industry advancements, Dr. Fu’s legacy will be marked by her dedication to the development of technologies that improve human well-being and promote transparency in artificial intelligence systems. Her ongoing contributions will continue to inspire the next generation of researchers and engineers.

📖Top Noted Publications

A Survey on Drowsiness Detection – Modern Applications and Methods

Authors: Biying Fu, Fadi Boutros, Chin-Teng Lin, Naser Damer

Journal: IEEE Transactions on Intelligent Vehicles

Year: 2024

Generative AI in the context of assistive technologies: Trends, limitations and future directions

Authors: Biying Fu, Abdenour Hadid, Naser Damer

Journal: Image and Vision Computing

Year: 2024

Biometric Recognition in 3D Medical Images: A Survey

Authors: Biying Fu, Naser Damer

Journal: IEEE Access

Year: 2023

Face morphing attacks and face image quality: The effect of morphing and the unsupervised attack detection by quality

Authors: Biying Fu, Naser Damer

Journal: IET Biometrics

Year: 2022

Generalization of Fitness Exercise Recognition from Doppler Measurements by Domain-Adaption and Few-Shot Learning

Authors: Biying Fu, Naser Damer, Florian Kirchbuchner, Arjan Kuijper

Journal: Book chapter

Year: 2021

Jorge Duque | Machine Learning | Global Data Innovation Recognition Award

Posted on by ScienceFather

Prof Dr. Jorge Duque | Machine Learning | Global Data Innovation Recognition Award

Prof Dr. Jorge Duque at ISLA – Polytechnic Institute of Management and Technology, Portugal

👨‍🎓 Profiles

📚 Education

Prof. Duque is currently pursuing a post-doctorate at the University of Trás-os-Montes and Alto Douro (UTAD). He earned his Ph.D. in Computer Science from UTAD (2013-2018), a Master’s in Information and Communication Technologies from ISLA (2008-2009), and a Bachelor’s in Information Systems and Multimedia Management from ISLA (2003-2007).

💻 Areas of Expertise

His expertise spans Computer Science, specifically in Information Systems, Computer Engineering, and Data Science for Decision Support Analysis.

🛠️ Technical Skills

Prof. Duque possesses technical skills in Cisco Networking (CCNA1), programming with Visual Studio and SQL Server, and web technologies including Python, C#, .NET MVC, ASP.NET, and CSS. He is also proficient in Data Science techniques such as Machine Learning, Deep Learning, Big Data, and Data Mining.

🏢 Professional Experience

His career includes roles at AXA Insurance, CEA Consulting Services, LCA – IT, Inforporto Lda, and Geada & Babo, Lda. He served as an IT Trainer and Coordinator at the IEFP and was the Coordinator for Economic Affairs at the Municipality of BaiĂŁo before joining ISLA as a Professor and Researcher in 2018.

👨‍🏫 Leadership Roles

Prof. Duque has held several leadership positions, including Coordinator of the Postgraduate Program in Analytics and Business Data Science, Coordinator of the Bachelor’s in Computer Science for E-commerce, and Chair of the Pedagogical Council at the School of Technology.

📅 International Conference Participation

He has actively participated in international conferences such as iSCSI, where he served as Workshop Chair and Reviewer. He has also been involved with CENTERIS and ICITS, reviewing papers for various sessions.

📖 Teaching Experience

Prof. Duque has been an Adjunct Professor at ISLA since 2018, teaching courses in Computer Science and Management, and has served as an Assistant Professor at LusĂłfona University since 2021.

🧑‍🏫 Professional Development

His ongoing professional development includes advanced training in Python for Data Science and courses on developing pedagogical competencies for distance education.

📖  Top Noted Publications
Data Mining for Knowledge Management
  • Author: Duque, J.
    Journal: Procedia Computer Science
    Year: 2024
Data Science with Data Mining and Machine Learning: A Design Science Research Approach
  • Author: Duque, J., Godinho, A., Moreira, J., Vasconcelos, J.
    Journal: Procedia Computer Science
    Year: 2024
Blockchain Technologies: A Scrutiny into Hyperledger Fabric for Higher Educational Institutions
  • Author: Dias, P., Gonçalves, H., Silva, F., Martins, J., Godinho, A.
    Journal: Procedia Computer Science
    Year: 2024
Business Intelligence and the Importance of Data Processing
  • Author: Duque, J.
    Journal: Lecture Notes in Networks and Systems
    Year: 2024
The Importance of Big Data and IoT in Smart Cities
  • Author: Duque, J.
    Journal: Lecture Notes in Networks and Systems
    Year: 2024
Data Mining Applied to Knowledge Management
  • Author: Duque, J., Silva, F., Godinho, A.
    Journal: Procedia Computer Science
    Year: 2023
The IoT to Smart Cities: A Design Science Research Approach
  • Author: Duque, J.
    Journal: Procedia Computer Science
    Year: 2023

Qinxu Ding | Machine Learning and AI Applications | Best Researcher Award

Posted on by ScienceFather

Dr. Qinxu Ding | Machine Learning and AI Applications | Best Researcher Award

Dr. Qinxu Ding at Singapore University of Social Sciences, Singapore

PROFILES👨‍🎓

EARLY ACADEMIC PURSUITS 📚

This accomplished individual began their academic journey with a B.S. in Information and Numerical Science from Nankai University, Tianjin, China, graduating in July 2015 with an impressive GPA of 89/100. Their undergraduate studies laid a strong foundation in Mathematical Statistics, Probability Theory, and Data Mining, which paved the way for further academic exploration. They pursued a Ph.D. in Computational Mathematics at Nanyang Technological University, completing their thesis on Numerical Treatment of Certain Fractional and Non-fractional Differential Equations in April 2020.

PROFESSIONAL ENDEAVORS 💼

Currently, this individual serves as a Lecturer and DBA Supervisor in the Finance Programme at the Business School of the Singapore University of Social Sciences (SUSS) since July 2021. Their teaching portfolio includes various fintech courses such as Machine Learning and AI for FinTech, Blockchain Technology, and Risk Management for Finance and Technology. Prior to this role, they were a Research Fellow at the Alibaba-NTU Singapore Joint Research Institute, focusing on Explainable Artificial Intelligence.

CONTRIBUTIONS AND RESEARCH FOCUS 🔍

Their research interests lie at the intersection of applied machine learning, computational mathematics, and blockchain technology in fintech. They have made significant contributions through publications in top-tier AI conferences, including ICLR, NeurIPS, AAAI, and CIKM, as well as prestigious journals in computational mathematics and fintech.

IMPACT AND INFLUENCE 🌟

The individual has played a pivotal role in enhancing the understanding of machine learning models and their applicability in real-world financial scenarios. Their work on adversarial attacks in deep neural networks and the development of explainable AI frameworks has positioned them as a thought leader in the field, influencing both academic and industrial practices.

ACADEMIC CITES 📖

Their groundbreaking research has been recognized in multiple high-impact venues, highlighting their innovative approaches to complex problems in fintech. Notable publications include works on adversarial defenses, counterfactual explanations, and recommendation systems, reflecting a robust commitment to advancing knowledge in AI and fintech.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

As a Chartered Fintech Professional and a member of various academic committees, this individual continues to contribute to the fintech community. Their involvement in organizing the Global Web3 Eco Innovation Summit 2022 illustrates their dedication to fostering innovation and collaboration in the fintech space. Looking ahead, they aim to further bridge the gap between academia and industry, shaping the future of fintech through research and education.

TOP NOTED PUBLICATIONS 📖

Stable neural ode with lyapunov-stable equilibrium points for defending against adversarial attacks
    • Authors: Q. Kang, Y. Song, Q. Ding, W. P. Tay
    • Journal: Advances in Neural Information Processing Systems
    • Year: 2021
Non-polynomial Spline Method for Time-fractional Nonlinear SchrĂśdinger Equation
    • Authors: Q. Ding, P. J. Y. Wong
    • Journal: 15th International Conference on Control, Automation, Robotics and …
    • Year: 2018
A hybrid bandit framework for diversified recommendation
    • Authors: Q. Ding, Y. Liu, C. Miao, F. Cheng, H. Tang
    • Journal: Proceedings of the AAAI Conference on Artificial Intelligence
    • Year: 2021
Quintic non-polynomial spline for time-fractional nonlinear SchrĂśdinger equation
    • Authors: Q. Ding, P. J. Y. Wong
    • Journal: Advances in Difference Equations
    • Year: 2020
A survey on decentralized autonomous organizations (DAOs) and their governance
    • Authors: Q. Ding, D. Liebau, Z. Wang, W. Xu
    • Journal: World Scientific Annual Review of Fintech
    • Year: 2023
The skyline of counterfactual explanations for machine learning decision models
    • Authors: Y. Wang, Q. Ding, K. Wang, Y. Liu, X. Wu, J. Wang, Y. Liu, C. Miao
    • Journal: Proceedings of the 30th ACM International Conference on Information …
    • Year: 2021

Gebeyehu Belay Gebremeskel | Machine Learning | Editorial Board Member

Posted on by ScienceFather

Assoc Prof Dr. Gebeyehu Belay Gebremeskel | Machine Learning | Editorial Board Member

Assoc Prof Dr. Gebeyehu Belay Gebremeskel  at  Bahir Dar University, Ethiopia

👨‍🎓 Profiles

🌟 Early Academic Pursuits

Dr. Gebeyehu Belay Gebremeskel’s academic journey began at Alemaya University in Dire Dawa, Ethiopia, where he earned his Bachelor of Science in Computer Science in July 1991. His quest for advanced knowledge led him to London South Bank University in England, where he completed a Master of Science in Advanced Information Technology in January 2001. Under the guidance of Professor Ddembe Williams, he delved into System Dynamics Modeling and Decision Science. Dr. Gebremeskel’s pursuit of deeper expertise continued with a Ph.D. from Chongqing University in China, culminating in June 2013. His dissertation, supervised by Professor Zhongshi He, focused on the integration of Data Mining Algorithms and Multi-Agent Systems with Business Intelligence.

💼 Professional Endeavors

Dr. Gebeyehu’s professional career is distinguished by his impactful roles at Bahir Dar University’s Institute of Technology. As an Associate Professor, he has been instrumental in program accreditation, international conference organization, and curriculum development. His expertise has been further honed through a postdoctoral fellowship at Chongqing University’s College of Automation, focusing on machine learning, big data analytics, and intelligent systems. His commitment to excellence is reflected in his contributions to academic and research training, including programs in GIS, web design, and networking.

🔬 Contributions and Research Focus

Dr. Gebeyehu’s research spans several cutting-edge areas within computer science and engineering. His work in Big Data Analytics emphasizes optimization and precision in performance. In Artificial Intelligence and Machine Learning, he explores neural networks, genetic algorithms, and support vector machines, contributing to advancements in intelligent systems and fault diagnosis. His research in Data Mining includes pattern recognition, outlier detection, and intelligent data systems. Additionally, his focus on Intelligent Systems and Agent Technology involves developing algorithms for multi-agent systems and enhancing system intelligence.

🏆 Accolades and Recognition

Dr. Gebeyehu has received significant recognition for his contributions to academia and research. His roles as conference co-chair and technical program chair for international events like ICAST 2018, 2019, and 2020 highlight his leadership and influence in the field. His research publications in renowned journals, such as the International Journal of Data Science and Analytics, further underscore his impact. His work on big data analytics and neural network models has been widely acknowledged and respected within the academic community.

🌍 Impact and Influence

Dr. Gebeyehu’s influence extends across both academic and practical domains. His research has advanced knowledge in intelligent transportation systems and smart environments. His curriculum development and program accreditation efforts at Bahir Dar University have elevated the quality of education and research opportunities. By mentoring postgraduate students and leading international workshops, Dr. Gebeyehu has significantly impacted the field of computer science and engineering, shaping the future of many students and researchers.

🌟 Legacy and Future Contributions

Dr. Gebeyehu Belay Gebremeskel’s legacy is marked by his pioneering research, extensive teaching experience, and leadership in academia. His contributions to machine learning, big data analytics, and intelligent systems have set a high standard in the field. As he continues to explore new research avenues and educational initiatives, Dr. Gebeyehu is poised to make further advancements and impact future generations of researchers and practitioners. His dedication ensures that his influence will be felt long into the future.

📖 Publications

Architecture and optimization of data mining modeling for visualization of knowledge extraction: Patient safety care

Mao Makara | Machine Learning Applications | Best Researcher Award

Posted on by ScienceFather

Mr. Mao Makara | Machine Learning Applications | Best Researcher Award

Mr. Mao Makara at  Soonchunhyang University, South Korea

👨‍🎓 Profiles

Orcid Profile
Research Gate Profile

📚 Academic Background

Makara MAO earned his Bachelor of Engineering degree in Computer Science from the Royal University of Phnom Penh in 2016. He is currently pursuing a combined Master’s and PhD degree in Software Convergence at Soonchunhyang University, South Korea, starting in 2021. His research interests encompass machine learning, deep learning, image classification, video classification, and object detection.

🎓 Education and Training

Makara MAO’s academic journey includes:

  • Sep 2021 – Present: Enrolled in a combined Master’s and PhD degree program at the Department of Software Convergence, Soonchunhyang University, South Korea.
  • Oct 2019 – Jul 2021: Completed a Master’s Degree in Information Technology Engineering at the Royal University of Phnom Penh, Cambodia.
  • Oct 2012 – Jul 2016: Obtained a Bachelor’s Degree in Computer Science from the Royal University of Phnom Penh, Cambodia.

💼 Work Experience

Makara’s professional experience includes:

  • Sep 2020 – Jan 2021: Served as the Application Team Leader at ORM Co., Ltd., Phnom Penh, Cambodia.
  • Jul 2016 – Jul 2020: Worked as an Application Engineer at Ezecom Company, Phnom Penh, Cambodia, where he was involved in web development and system management.

🛠 Skills and Interests

Makara MAO’s skills and interests include:

  • Programming Languages: Proficient in Python, PHP, Laravel; knowledgeable in C and C++.
  • Technical Skills: Expertise in GPU Parallel Algorithms, Data Structures, Algorithms, and Object-Oriented Programming.
  • Research Interests: Focused on Video Classification, Deep Learning, and Image Processing.

💬 Communication / Managerial Skills

Makara MAO excels in communication and management:

  • Effective Communicator: Actively participates in local and international conferences.
  • Adaptable: Open-minded and a good listener, comfortable working with new people, including international students.
  • Creative Problem-Solver: Adept at exploring new possibilities and solutions to challenges.
  • Leadership: Demonstrated strong leadership abilities by managing research teams and guiding junior researchers.

📖 Publications

Deep Learning Innovations in Video Classification: A Survey on Techniques and Dataset Evaluations

    • Journal: Electronics
    • Year: 2024

Video Classification of Cloth Simulations: Deep Learning and Position-Based Dynamics for Stiffness Prediction

    • Journal: Sensors
    • Year: 2024

Coefficient Prediction for Physically-based Cloth Simulation Using Deep Learning

    • Journal: International Journal on Advanced Science, Engineering and Information Technology
    • Year: 2023

Supervised Video Cloth Simulation: Exploring Softness and Stiffness Variations on Fabric Types Using Deep Learning

    • Journal: Applied Sciences
    • Year: 2023

Bi-directional Maximal Matching Algorithm to Segment Khmer Words in Sentence

    • Journal: Journal of Information Processing Systems
    • Year: 2022

Zdena Dobesova | Machine learning | Best Researcher Award

Posted on by ScienceFather

Assoc Prof Dr. Zdena Dobesova | Machine learning | Best Researcher Award

Assoc Prof Dr. Zdena Dobesova at PalackĂ˝ University in Olomouc, Czech Republic

🔗Profiles

 Orcid Profile
 Scopus Profile

🏆 Associate Professor Ing. Zdena DOBEŠOVÁ, Ph.D.

🎓 Educational Background

  • 2017: Habilitation in “System Engineering and Information Science” at University of Pardubice, Faculty of Economics and Administration. Habilitation Thesis: Graphical Notation of Visual Languages in GIS.
  • 2002–2007: Ph.D. in Geoinformatics from Technical University of Ostrava, Faculty of Mining and Geology. Ph.D. Thesis: Cartographical Visualization of Spatial Databases for Regional Information Systems.
  • 1982–1987: Master’s degree in Technical Cybernetics from Czech Technical University Prague, Faculty of Electrical Engineering. Master’s Thesis: Set of Programs for Theory of Automatic Control.
  • 2002–2003: Preparation of tutors for e-learning courses.

📜 Certificates

  • 2022: Script Creation for ArcGIS Pro in Python Language (ArcDATA Prague)
  • 2015: GRASS GIS (GISMentros)
  • 2014: Scripting in Python and Processing CAD Data in ArcGIS for Desktop (VARS Brno)
  • 2010: AutoCAD 2010 CZ (Computer Agency Brno)
  • 2006: Introduction to Scripting in Python Language (ArcDATA Prague)
  • 1988–1989: Logic Programming in PROLOG and Course dBASE III+ (ČSVTS)

🏢 Work Experience

  • 2017–Present: Associate Professor, Department of Geoinformatics, PalackĂ˝ University Olomouc, Czechia
  • 2001–2016: Assistant Professor, Department of Geoinformatics, PalackĂ˝ University Olomouc, Czechia
  • 1991–2001: Administrator of Faculty Computer Network, PalackĂ˝ University Olomouc
  • 1991: Administrator of Computer Laboratory, Department of Mathematical Informatics, PalackĂ˝ University
  • 1987–1991: Researcher, Department of Construction Research, Kovosvit, Sezimovo ÚstĂ­ II, Czechia

📚 Lectures (Academic Year 2023/2024)

  • Bachelor Program:
    • Database Systems (KGI/DATAB)
    • Programming for Geoinformatics (KGI/PROPY)
    • Bachelor Theses Seminar 1 & 2 (KGI/BAK1 & KGI/BAK2)
    • Professional Training in Geoinformatics (KGI/PRAB)
  • Master Program:
    • Data Mining (KGI/DATAM)
    • Student Competition in GI (KGI/SOUGI)
    • Geoinformatics in Practice (KGI/GEXE)
  • Doctoral Program:
    • Programming for GIS (KGI/PGPGI)

🔬 Projects (Selection)

  • 2023: Analysis, Modelling, and Visualization of Spatial Phenomena by Geoinformation Technologies II
  • 2020–2023: UrbanDM, ERASMUS+ Jean Monnet Module Project
  • 2019–2020: RODOGEMA – Development of Doctoral Study Programs
  • 2015–2018: GeoS4S – GeoServices-4-Sustainability
  • 2011–2013: BotanGIS – Innovation in Botany Using Geoinformation Technologies

🌍 Stays Abroad

  • 2007: Salzburg, Austria
  • 2010: Zagreb, Croatia
  • 2011: Belgrade, Serbia
  • 2012: Delft, Netherlands
  • 2013: SzĂŠkesfehĂŠrvĂĄr, Hungary
  • 2014: Salzburg, Austria
  • 2015: Valencia, Spain
  • 2017: Vienna, Austria
  • 2018: Eberswalde, Germany; Vienna, Austria
  • 2019: Bochum, Germany; Dresden, Germany
  • 2022: Bratislava, Slovakia
  • 2024: Szeged and SzĂŠkesfehĂŠrvĂĄr, Hungary

🔍 Scientometrics

  • Web of Science: H-index 7, Publications 49, Sum of Times Cited 227
  • SCOPUS: H-index 10, Publications 50, Sum of Times Cited 358

📚 Membership in Editorial and Advisory Boards

  • ISPRS International Journal of Geo-Information
  • American Journal of Computation, Communication and Control
  • Frontiers in Computer Science, Human-Media Interaction

 

📖 Publication Top Noted

 

Processing of the Time Series of Passenger Railway Transport in EU Countries
Authors: Zdena Dobesova
Journal: Data Analytics in System Engineering
Year: 2024

Evaluation of Orange Data Mining Software and Examples for Lecturing Machine Learning Tasks in Geoinformatics
Authors: Zdena Dobesova
Journal: Computer Applications in Engineering Education
Year: 2024

Evaluation of Changes in Corridor Railway Traffic in the Czech Republic During the Pandemic Year 2020
Authors: Michal Kučera, Zdena Dobešová
Journal: Geographia Cassoviensis
Year: 2023

Map Guide for Botanical Gardens: Multidisciplinary and Educational Storytelling
Authors: Zdena Dobesova, Rostislav Netek, Jan Masopust
Journal: Journal of Geography in Higher Education
Year: 2022

Cognition of Graphical Notation for Processing Data in ERDAS IMAGINE
Authors: Zdena Dobesova
Journal: ISPRS International Journal of Geo-Information
Year: 2021

Analysis of the Degree of Threat to Railway Infrastructure by Falling Tree Vegetation
Authors: Michal Kučera, Zdena Dobesova
Journal: ISPRS International Journal of Geo-Information
Year: 2021

Experiment in Finding Look-Alike European Cities Using Urban Atlas Data
Authors: Zdena Dobesova
Journal: ISPRS International Journal of Geo-Information
Year: 2020