Omar Haddad | Artificial Intelligence | Best Researcher Award

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

Shubing Dai | Algorithm Development | Best Researcher Award

Prof. Shubing Dai | Algorithm Development | Best Researcher Award

Prof. Shubing Dai at Northwest A&F University, China

Professional Profile👨‍🎓

👨‍🏫 Summary

Prof. Shubing Dai is an Associate Professor at Northwest A&F University, specializing in Hydraulic Engineering. With a background in Hydraulics and River Dynamics, he has published over 20 research papers and actively participated in over 20 research projects. His work primarily focuses on urban flood management, hydraulic structures, and water flow dynamics. He is also an active member of key professional organizations, including the China Society for Hydroelectric Engineering and the International Association for Hydro-Environment Engineering and Research (IAHR).

🎓 Education

Prof. Dai began his academic career at Northwest A&F University, where he earned his Bachelor’s (2008–2012) and Master’s (2012–2015) degrees in Hydraulic and Hydroelectric Engineering. He then pursued a Ph.D. in Hydraulics and River Dynamics at Dalian University of Technology (2016–2021). Additionally, he worked as a visiting scholar at the University of La Coruña in Spain (2024).

💼 Professional Experience

Prof. Dai has extensive professional experience, both in academia and industry. He currently serves as an Associate Professor at Northwest A&F University and the Department Secretary of the Hydraulic Engineering Department. He also previously worked as an Assistant Engineer at the Changjiang Survey, Planning, and Design Institute (2015–2016), contributing to several major hydropower and hydraulic engineering projects.

📚 Academic Contributions

Prof. Dai is an active contributor to the academic community, serving as a reviewer for several leading journals such as Journal of Hydrology and Physics of Fluids. He also serves as an editorial board member for an international journal. His research focuses on water resources, hydraulic structures, and flow dynamics, with over 20 published papers and several high-impact research projects.

🔧 Technical Skills

Prof. Dai has developed a range of technical skills, including:

  • Hydraulic Engineering: Focus on energy dissipation and optimization of flood discharge systems.
  • Urban Flooding & Drainage: Expertise in urban drainage system design, stormwater management, and flood mitigation.
  • Flow Dynamics: Proficient in Computational Fluid Dynamics (CFD) and non-steady flow simulations for hydraulic applications.
  • Hydropower Engineering: In-depth research on dam-break flood modeling, hydraulic structures, and their interactions with water flow.

👩‍🏫 Teaching Experience

As a dedicated educator, Prof. Dai mentors master’s students and teaches courses on fluid dynamics, hydraulic modeling, and water resource management. He is also responsible for the administration of the Water Resources and Hydroelectric Engineering department at Northwest A&F University, playing a key role in curriculum development and academic planning.

🔬 Research Interests

Prof. Dai’s research interests are focused on:

  • Hydraulic Engineering: Research on energy dissipation in hydraulic structures and optimization of flood discharge processes.
  • Flood Disaster Management: Urban flood management, drainage systems, and dam-break flood evolution.
  • Non-steady Flow & Hydrodynamics: Investigating the dynamics of free-surface flows, wave behavior, and non-constant flow conditions in hydraulic systems.

🔍 Research Projects

Prof. Dai leads and participates in several important research projects, such as:

  • City Flood and Drainage Systems Simulation (2022–2025)
  • Optimization of Urban Drainage Under Extreme Rainfall Conditions (2023–2025)
  • Dam-Break Flood Evolution and Structural Interaction Studies (2024–2026)
    He is also involved in national and regional projects on hydraulic structure optimization, flood forecasting, and water resource management.

 

📖Top Noted Publications

Numerical study of roll wave development for non-uniform initial conditions using steep slope shallow water equations

Authors: Dai, S., Liu, X., Zhang, K., Liu, H., Jin, S.
Journal: Physics of Fluids
Year: 2024

Discharge coefficients formulae of grate inlets of complicated conditions for urban floods simulation and urban drainage systems design

Authors: Dai, S., Hou, J., Jin, S., Hou, J., Liu, G.
Journal: Journal of Hydrology
Year: 2023

Land Degradation Caused by Construction Activity: Investigation, Cause and Control Measures

Authors: Dai, S., Ma, Y., Zhang, K.
Journal: International Journal of Environmental Research and Public Health
Year: 2022

Numerical investigations of unsteady critical flow conditions over an obstacle using three models

Authors: Dai, S., Jin, S.
Journal: Physics of Fluids
Year: 2022

Interception efficiency of grate inlets for sustainable urban drainage systems design under different road slopes and approaching discharges

Authors: Dai, S., Jin, S., Qian, C., Ma, Y., Liang, C.
Journal: Urban Water Journal
Year: 2021

Susan Stead | Technology Innovation | Best Researcher Award

Dr. Susan Stead , Technology Innovation, Best Researcher Award

Doctorate at RWTH University, Institute for Technology and Innovation Management, Germany

Google Scholar Profile
Scopus Profile

🌟Summary

Dr. Susan Stead is an Assistant Professor at RWTH Aachen University, specializing in Healthcare and Service Innovation. She serves as Managing Director of the Healthcare Innovation Lab and Digital Responsibility Lab at the Institute for Technology and Innovation Management. Her interdisciplinary research focuses on multisensory customer service experiences and the integration of artificial intelligence in healthcare.

🎓Education

  • Ph.D., Maastricht University, the Netherlands, 2020 Dissertation: “The Power of Senses: Unraveling Multisensory Customer Service Experiences”
  • M.Sc., International Business – Strategic Marketing (cum laude), Maastricht University, the Netherlands, 2014
  • B.B.A., Business Administration, Zuyd University of Applied Science, Maastricht, the Netherlands, 2013

💼 Professional Experience

Dr. Susan Stead brings over a decade of expertise in academia and research, currently serving as an Assistant Professor at RWTH Aachen University. Since joining RWTH Aachen in 2020, she has held pivotal roles including Managing Director of the Healthcare Innovation Lab and Digital Responsibility Lab at the Institute for Technology and Innovation Management. Dr. Stead’s career is marked by her leadership in interdisciplinary research, focusing on healthcare and service innovation. She has played a crucial role in advancing the understanding of multisensory customer service experiences and integrating artificial intelligence into healthcare practices. Her contributions extend to mentoring young talents in AI through her involvement with AI Grid and serving as a faculty board member at RWTH Aachen University.

🔬 Research Interests

Dr. Susan Stead’s research interests span the domains of healthcare and service innovation, with a particular emphasis on multisensory customer experiences and the application of artificial intelligence in healthcare settings. Her work explores how sensory modalities impact customer interactions and satisfaction, aiming to enhance service delivery across various industries. Dr. Stead is also passionate about digital transformation in service sectors, investigating how emerging technologies can optimize operational efficiencies and improve patient care outcomes. Her interdisciplinary approach integrates insights from service design, innovation management, and AI ethics, contributing to the development of future-focused strategies in healthcare innovation.

📖 Publication Top Noted

Application of artificial intelligence systems in the emergency room: Do the communication patterns give indications for possible starting points? An observational study

    • Authors: Tjardes, T., Meyer, L.M., Lotz, A., Stead, S., Walossek, N.
    • Journal: Unfallchirurgie (Germany)
    • Volume: 126
    • Issue: 7
    • Pages: 552–558
    • Year: 2023

Hospital resource endowments and nosocomial infections: longitudinal evidence from the English National Health Service on Clostridioides difficile between 2011 and 2019

    • Authors: Stead, S., Vogt, L., Antons, D., Klasen, M., Sopka, S.
    • Journal: Journal of Hospital Infection
    • Volume: 134
    • Pages: 129–137
    • Year: 2023

It is Really Not a Game: An Integrative Review of Gamification for Service Research

    • Authors: Ciuchita, R., Heller, J., Köcher, S., Sidaoui, K., Stead, S.
    • Journal: Journal of Service Research
    • Volume: 26
    • Issue: 1
    • Pages: 3–20
    • Year: 2023

The Inscrutable New Actor: An Employee Perspective on the Flipside of AI

    • Authors: Stead, S.
    • Conference: International Conference on Information Systems (ICIS 2023)
    • Year: 2023

Toward Multisensory Customer Experiences: A Cross-Disciplinary Bibliometric Review and Future Research Directions

    • Authors: Stead, S., Wetzels, R., Wetzels, M., Odekerken-Schröder, G., Mahr, D.
    • Journal: Journal of Service Research
    • Volume: 25
    • Issue: 3
    • Pages: 440–459
    • Year: 2022

Mr. Benjamin Borketey | Machine Learning for fraud detection | Global Data Innovation Recognition Award

Mr. Benjamin Borketey, Machine Learning for fraud detection, Global Data Innovation Recognition Award

Mr. Benjamin Borketey at First Citizens Bank, United States

Professional Profile

Orcid Profile

Summary of Skills

Over 5 years of experience in Data Analytics, Economic Forecasting, Time Series Modelling, Statistical Modelling, Machine Learning, and Data Management.

Professional Experience

Risk Analyst III, First Citizens Bank, NC
October 2023 to Date

  • Independently validate financial crime models (AML, fraud), probability of default (PD), loss given default (LGD), and exposure at default (EAD) for commercial and industrial portfolios.
  • Provide effective challenges, mitigate model risks, and produce comprehensive validation reports.

Quant Model Analyst, U.S Bank, NC
August 2021-September 2023

  • Perform complex mathematical analysis using statistical methods and machine learning techniques.
  • Build and validate fraud detection models and interpret statistical findings for senior management.

Quant Model Analyst, Flagstar Bank, MI
January 2018-August 2021

  • Validate bank-wide models and prepare reports for senior management and regulators.
  • Analyze large datasets to provide strategic insights.

Education

Purdue University
Post Graduate Program in AI and Machine Learning, August 2022

The University of Akron, Ohio
Master of Arts in Economics, December 2017

University of Cape Coast
Bachelor of Arts in Economics and Mathematics, May 2014

Professional Association

  • Association of Data Scientists
  • International Society for Data Science and Analytics (ISDSA)
  • Data Visualization Society
  • Institute of Electrical and Electronics Engineers (Computer Science Society)

Certification Awards

  • Economic Data Analytics Certificate, SAS Institute

Conference Presentation

  • Presented at Global Insight Conference on Artificial Intelligence, 2024
  • International Society for Data Science and Analytics, 2024

Certifications

  • Statistics Essential for Data Science (Simplilearn)
  • Introduction to Artificial Intelligence
  • Python for Data Science (Simplilearn)
  • Data Science with Python (Simplilearn)
  • Machine Learning (Simplilearn)
  • Deep Learning with TensorFlow and Keras (Simplilearn)
  • Advance Deep Learning and Computer Vision (Simplilearn)
  • SAS Certificate in Economics (SAS Institute)
  • Certified Peer Reviewer (Elsevier)

📖 Publication Top Noted

  • How hourly wage and the probability of committing a crime ( May 2024).

  • Real-Time Fraud Detection Using Machine Learning. ( May 2024).