Luis Pastor Sanchez-Fernandez | Computer Science and Artificial Intelligence | Cross-disciplinary Excellence Award

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Prof. Dr. Luis Pastor Sanchez-Fernandez | Computer Science and Artificial Intelligence | Cross-disciplinary Excellence Award

Senior Researcher at Center for Computing Research Instituto Politecncico Nacional, Mexico

Luis Pastor Sánchez-Fernández is a Full Professor at the Computer Research Center of the National Polytechnic Institute (IPN) in Mexico City, with a PhD in Technical Sciences from the José Antonio Echeverría Polytechnic Institute (CUJAE), Havana (1998). A distinguished researcher and educator, he has been a member of Mexico’s National System of Researchers since 2007 (currently Level II). His work spans multiple disciplines, including biomechanics, bioinformatics, environmental acoustics, signal processing, expert systems, and intelligent automation. He has supervised over 13 doctoral and 46 master’s students, many of whom received honors or were inducted into national research systems. Dr. Sánchez-Fernández has led several research groups and CONACYT-funded projects, notably designing the Environmental Noise Monitoring System for the Historic Center of Mexico City. A recipient of the 2014 IPN Applied Research Award, he is also an accomplished keynote speaker, reviewer for high-impact journals, and advocate for interdisciplinary and socially impactful research.

Professional Profile 

🎓 Education of Luis Pastor Sánchez-Fernández

Luis Pastor Sánchez-Fernández holds a PhD in Technical Sciences from the prestigious José Antonio Echeverría Polytechnic Institute (CUJAE) in Havana, Cuba, awarded in 1998. His doctoral education laid a strong interdisciplinary foundation, combining elements of engineering, computer science, and applied research. This academic background has been instrumental in shaping his cross-disciplinary research career, allowing him to contribute significantly to fields such as biomechanics, signal processing, and intelligent systems.

💼 Professional Experience of Luis Pastor Sánchez-Fernández

Luis Pastor Sánchez-Fernández has served as a Full Professor at the Computer Research Center of the National Polytechnic Institute (IPN), Mexico City, since 2000, where he has been a key figure in advancing interdisciplinary scientific research and technological development. With over two decades of academic and research leadership, he has directed multiple research groups in bioinformatics and intelligent measurement systems, supervised numerous postgraduate theses, and mentored future leaders in science. His expertise spans diverse fields including biomechanics, environmental acoustics, expert systems, and automation. He has also played critical roles as a project leader for national research initiatives funded by CONACYT, and as an advisor and evaluator of scientific proposals. His contributions extend beyond academia into societal impact projects, such as the Environmental Noise Monitoring System for Mexico City, solidifying his reputation as a cross-disciplinary innovator and research leader.

🔬 Research Interests of Luis Pastor Sánchez-Fernández

Luis Pastor Sánchez-Fernández’s research interests lie at the intersection of engineering, computer science, health sciences, and environmental studies, reflecting his strong cross-disciplinary approach. He focuses on the biomechanical analysis of patients with Parkinson’s disease, exploring computational and signal-based methods to improve medical diagnostics and rehabilitation. He is also deeply engaged in environmental acoustics, developing noise indicators and acoustic indices to assess and mitigate the harmful effects of urban noise pollution. His work extends into signal pattern recognition, expert systems, virtual instrumentation, and the design of intelligent systems for automation. Additionally, he has a sustained interest in bioinformatics, leading research groups that develop advanced computational tools for biological data analysis. His research consistently integrates theory and practical application, addressing real-world problems through innovative, multidisciplinary solutions.

🏅 Awards and Honors of Luis Pastor Sánchez-Fernández

Luis Pastor Sánchez-Fernández has received several prestigious awards and honors in recognition of his outstanding contributions to interdisciplinary research and academic mentorship. He was honored with the Applied Research Award by the National Polytechnic Institute (IPN) in 2014, acknowledging his impactful work that bridges scientific innovation and real-world application. As a dedicated mentor, he has received two thesis advisor awards from IPN, celebrating the excellence of his supervised postgraduate research. Many of his doctoral and master’s students have earned honorable mentions and Cum Laude distinctions, with several joining Mexico’s National System of Researchers—a testament to his role in cultivating high-caliber scholars. Since 2007, he has held Level II membership in the National System of Researchers of Mexico (SNI), further solidifying his reputation as a leader in cross-disciplinary scientific advancement.

🧾 Conclusion

The candidate demonstrates exceptional cross-disciplinary impact, strong leadership, and a deep commitment to advancing science at the intersection of multiple fields. His contributions in biomechanics, environmental monitoring, signal processing, and intelligent systems showcase not only depth but also the integration of diverse disciplines to address complex societal challenges. He is an ideal nominee for the Cross-disciplinary Excellence Award. Minor enhancements in visibility, global partnerships, and documentation of publications would make his case even more compelling.

📚 Publications by Luis Pastor Sánchez-Fernández

1.Title: Dataset for Gait Assessment in Parkinson’s Disease Patients

  • Authors: (Not provided)
  • Year: (Not explicitly listed)
  • Type: Data Paper – Open Access
  • Citations: 0

2.Title: Innovations and Technological Advances in Healthcare Remote Monitoring Systems for the Elderly and Vulnerable People: A Scoping Review

  • Authors: (Not fully listed)
  • Year: (Not explicitly listed)
  • Type: Review – Open Access
  • Citations: 0

3.Title: Computer Model for Gait Assessments in Parkinson’s Patients Using a Fuzzy Inference Model and Inertial Sensors

  • Authors: (Not fully listed)
  • Journal: Artificial Intelligence in Medicine
  • Year: 2025
  • Citations: 2

4.Title: Motion Smoothness Analysis of the Gait Cycle, Segmented by Stride and Associated with the Inertial Sensors’ Locations

  • Authors: (Not fully listed)
  • Journal: Sensors
  • Year: 2025
  • Type: Article – Open Access
  • Citations: 1

5.Title: Network Long-Term Evolution Quality of Service Assessment Using a Weighted Fuzzy Inference System

  • Authors: (Not fully listed)
  • Journal: Mathematics
  • Year: 2024
  • Type: Article – Open Access
  • Citations: 0

6.Title: Biomechanics of Parkinson’s Disease with Systems Based on Expert Knowledge and Machine Learning: A Scoping Review

  • Authors: (Not listed)
  • Year: (Not explicitly listed)
  • Type: Review – Open Access
  • Citations: 0

7.Title: An Integrated Approach to the Regional Estimation of Soil Moisture

  • Authors: (Not fully listed)
  • Journal: Hydrology
  • Year: 2024
  • Type: Article – Open Access
  • Citations: 0

8.Title: A Fuzzy Inference Model for Evaluating Data Transfer in LTE Mobile Networks via Crowdsourced Data

  • Authors: (Not fully listed)
  • Journal: Computación y Sistemas
  • Year: 2024
  • Type: Article
  • Citations: 1

9.Title: Computer Model for an Intelligent Adjustment of Weather Conditions Based on Spatial Features for Soil Moisture Estimation

  • Authors: (Not fully listed)
  • Journal: Mathematics
  • Year: 2024
  • Type: Article – Open Access
  • Citations: 4

 

 

Badr Machkour | Artificial Intelligence | Best Researcher Award

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Dr. Badr Machkour | Artificial Intelligence | Best Researcher Award

Professor, Faculty of Legal, Economic and Social Sciences, Morocco 

Dr. Badr Machkour is a Moroccan researcher and academic with deep expertise in economics, finance, and digital transformation. Currently holding a Ph.D. in Economic and Management Sciences, he has contributed to multiple domains including Industry 4.0, financial digitalization, and educational innovation. With a robust blend of academic and consulting experience, Dr. Machkour bridges theory and practice to drive impactful research. 🌐📊

Profile

Scopus

Google Scholar

Orcid

🎓 Education

Dr. Machkour holds a Doctorate in Economic and Management Sciences (2018–2023) from the FSJES of Agadir. His academic foundation includes a degree in Audit and Management Control from ENCG Agadir (2014–2017), post-preparatory classes in Economics and Commerce (2012–2014), and a Mathematics Baccalaureate (2011–2012). His diverse training forms a strong base for multidisciplinary research. 📚🧠

💼 Professional Experience

Dr. Machkour has extensive experience as a financial auditor, consultant, and trainer. He currently serves as a trainer at the Cité des Métiers et des Compétences (OFPPT), delivering finance and management programs. His previous roles span auditing and consulting at prominent firms like Augeco, MAZARS Maroc, and Agadir Conseil, involving sectors from agriculture to banking. 🏢💼📈

🔬 Research Interests

His research explores the intersection of Industry 4.0, digital banking solutions, customer experience, AI in education, and entrepreneurship. Dr. Machkour is particularly interested in how technology transforms economic relationships, pedagogical structures, and corporate strategies. 🤖📱🏫

🏆 Awards & Honors

While specific awards are not listed, Dr. Machkour’s work has been featured in indexed journals and cited internationally — notably his highly cited paper on Industry 4.0’s implications in finance. His academic contributions reflect both quality and influence. 🥇🌍

📑 Publications

Industry 4.0 and its Implications for the Financial Sector, Procedia Computer Science, 2020 — Cited by 151 🏦

The Rise of Artificial Intelligence in Educational Management: A Prospective Analysis on the Role of the Virtual Educational Director, Procedia Computer Science, 2025 🧠

Internet of Things in Education: Transforming Learning Environments, Enhancing Pedagogy, and Optimizing Resource Management, Data and Metadata, 2024 🏫

L’impact de l’adoption des solutions digitales sur la relation banque-client, Revue Française d’Economie et de Gestion, 2024 — Cited by 2 📲

Les facteurs d’adoption des solutions digitales bancaires par les consommateurs marocains, IJAFAME, 2022 — Cited by 1 📱

The Uses of Connected Objects and Their Influence on the Customer Experience, Test Engineering and Management, 2020 — Cited by 1 🌐

Etude exploratoire du développement de l’esprit Entrepreneurial et des compétences Entrepreneuriales auprès des étudiants au Maroc, Alternatives Managériales Economiques, 2024 👨‍🎓

Entrepreneurship 4.0 and Success Factors in the Context of Industry 4.0: A literature review, African Scientific Journal, 2024 🚀

✅ Conclusion

Overall, Dr. Badr Machkour is a promising and accomplished researcher whose work bridges digital innovation and economic practice with scholarly insight. His growing citation record, topical relevance, and interdisciplinary reach make him a strong candidate for the Best Researcher Award. With continued international engagement and broader collaborative networks, his impact is poised to grow even further. 🌍📈

Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

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Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Shuai Cao, School of Automation, Wuhan University of Technology, China

Dr. Shuai Cao is a dynamic researcher in the field of Computational Intelligence, currently pursuing graduate studies at Kunming University of Science and Technology and engaging in joint research at the Guangdong Academy of Sciences. With a focus on enhancing meta-heuristic algorithms, Dr. Cao has contributed significantly to engineering optimization, especially in AGV path planning and offset printing machine design. He is the mind behind the innovative Piranha Foraging Optimization Algorithm (PFOA) and co-author of several impactful SCI/EI publications. His expertise in algorithm improvement, machine learning, and pattern recognition is reflected through funded projects and hands-on roles in top research institutions like the South China Intelligent Robot Innovation Institute. With a remarkable blend of theoretical insight and practical application, Dr. Cao is a promising candidate for the Best Researcher Award, embodying academic rigor and real-world impact.

Publication Profile 

Orcid

Education

Dr. Shuai Cao’s academic journey began at Baotou Rare Earth High-tech No. 1 High School (2014–2017), where he laid a strong foundation in the sciences. He pursued his undergraduate degree in Mechanical and Electronic Engineering at Chongqing University of Humanities, Science and Technology (2017–2021), gaining critical insights into systems design and robotics. Since 2021, he has been a postgraduate student in Electronic Information at Kunming University of Science and Technology, further sharpening his expertise in computational theory and algorithmic systems. Complementing his studies, Dr. Cao has been engaged in a joint training program at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences since 2022. His coursework includes meta-heuristic algorithms, machine learning, digital signal processing, and pattern recognition, all of which feed directly into his research in Computational Intelligence and engineering optimization. His interdisciplinary background empowers him to tackle complex problems with innovative solutions.

Experience

Dr. Shuai Cao has held impactful roles in prestigious research institutions. From May 2022 to July 2023, he worked at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences, where he conducted advanced research on AGV handling robots. This included applying improved intelligent algorithms for path planning and optimization scheduling—work closely aligned with his master’s thesis. Since July 2023, he has been with the South China Intelligent Robot Innovation Institute, applying swarm intelligence methods to optimize the structure of high-speed multi-color offset printing machines. Dr. Cao’s work integrates theoretical research with industrial application, setting a benchmark for practical relevance. His involvement in key science and innovation projects also reflects his growing leadership in the field. From optimization algorithms to real-world robotic systems, Dr. Cao’s hands-on approach is shaping the future of intelligent manufacturing.

Awards and Honors

Dr. Shuai Cao has earned distinguished recognition in both academic and research circles for his innovative contributions to engineering optimization. As a lead researcher on multiple government-funded projects—including “Research and Application of Intelligent Scheduling of Mobile Collaborative Robot Clusters for Intelligent Manufacturing” (Project Code: 2130218003022) and the “Foshan Science and Technology Innovation Team Project” (Project Code: FS0AA-KJ919-4402-0060)—he has demonstrated expertise in bridging theory with practical industrial solutions. His pioneering research has been published in high-impact SCI and EI journals and conferences, such as IEEE ACCESS and the International Conference on Robotics and Automation Engineering (ICRAE). A highlight of his work is the development of the Piranha Foraging Optimization Algorithm (PFOA), which has garnered considerable attention in the optimization community for its novelty and effectiveness. Dr. Cao’s sustained dedication to cutting-edge innovation, along with his leadership in collaborative, cross-disciplinary projects, makes him a compelling nominee for the Best Researcher Award.

Research Focus

Dr. Shuai Cao’s research is centered on Computational Intelligence, specifically the improvement and engineering application of swarm intelligence algorithms. His work addresses key challenges in traditional optimization methods, such as premature convergence, low population diversity, and slow optimization speeds. He has successfully designed algorithms that overcome these limitations, notably the Piranha Foraging Optimization Algorithm (PFOA). His research extends to practical applications like automated guided vehicle (AGV) path planning, scheduling in smart factories, and mechanical structure optimization for high-speed printing systems. Through interdisciplinary methods, he combines machine learning, pattern recognition, and digital signal processing to bring theoretical advancements into real-world manufacturing challenges. With a clear aim of enhancing intelligent manufacturing systems, his research contributes to both academic knowledge and industrial innovation. His growing body of work reflects originality, technical rigor, and a strong alignment with modern engineering demands.

Publication Top Notes

Research on the Design and Application of Multi-Port Energy Routers