Lluis Miquel | Operations Research | Mathematical Modeling Breakthrough Award

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Prof. Dr. Lluis Miquel | Operations Research | Mathematical Modeling Breakthrough Award

Departamento Matemática at Pla-Aragones Universidad de Lleida, Spain

Dr. Luis Miguel Plà-Aragonès 🇪🇸 is a renowned expert in Operations Research 🔍 and Decision Analysis 🧠, with a focus on applications in agriculture 🌾, economics 💹, and health systems 🏥. As a professor at the University of Lleida, Spain, he has made significant contributions through multi-criteria decision-making, optimization modeling, and policy analysis. His interdisciplinary approach bridges the gap between theory and real-world impact, particularly in areas like agricultural planning, resource allocation, and cost-effectiveness analysis. 📊 With numerous publications 📚 and collaborations across Europe and Latin America 🌍, Dr. Plà-Aragonès is recognized for advancing the role of decision science in solving complex societal challenges. He is a dedicated mentor 👨‍🏫, respected academic, and a driving force behind the integration of quantitative models into sustainable decision-making practices. ♻️

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile

🎓 Education

Dr. Luis Miguel Plà-Aragonès holds a Ph.D. in Agricultural Engineering 🧑‍🔬 from the University of Lleida, Spain 🇪🇸, where he also earned his undergraduate and master’s degrees. His academic journey has been deeply rooted in applying mathematical and decision-analytic tools 📐 to complex agricultural systems 🌾. With a strong foundation in statistics, optimization, and operations research, he further enriched his expertise through postdoctoral training and international research exchanges across Europe 🌍. His educational background blends technical rigor with practical insight, laying the groundwork for his interdisciplinary research. His early academic excellence and commitment to innovation have made him a respected scholar in quantitative decision-making 🧠, particularly within the agricultural and environmental sectors. 📊 His educational path has continuously evolved toward bridging scientific research and real-world problem solving. 🧑‍🏫

💼 Professional Experience

Dr. Plà-Aragonès serves as a Professor of Operations Research and Decision Analysis at the University of Lleida 🏛️, with more than two decades of academic experience 👨‍🏫. He has held leadership roles in multiple international research networks, including coordinating the EURO Working Group on Operational Research in Agriculture and Forest Management 🌳. His career spans collaborative projects with both academic and industry stakeholders, particularly in the pig and dairy farming sectors 🐖🐄. As a principal investigator, he has led EU and Latin American research consortia in modeling and AI-driven agricultural innovation 🤖. He also mentors Ph.D. students and has developed decision-support systems used in real-world agribusiness. His dynamic professional profile showcases a balance of teaching, research, consultancy, and technological transfer across interdisciplinary domains. 🌍

🔬 Research Interests

Dr. Plà-Aragonès’s research revolves around mathematical modeling, multi-criteria decision-making, and operations research applied to agriculture, healthcare, and resource management 🌾🏥📊. He is especially known for his work in livestock logistics, sow replacement optimization, and agri-food supply chain modeling using Markov Decision Processes, stochastic optimization, and AI-enhanced systems 🤖. His interests also extend to cost-effectiveness analysis in healthcare, bridging economic modeling with decision science 💊. He is a key advocate for integrating AI, cloud computing ☁️, and IoT into agricultural modeling, ensuring smarter and more sustainable farm management. Through international collaborations 🌍 and cross-sector applications, his research continually addresses real-world challenges in food systems, environmental sustainability ♻️, and public health policy using rigorous quantitative methods. 📈

🏅 Awards and Honors

Dr. Luis Miguel Plà-Aragonès has been honored for his outstanding contributions to operations research and agricultural modeling 🌍. He is a recipient of various research leadership recognitions, including the prestigious coordination role in the CYTED BigDSSAgro Network and awards from international agricultural and engineering bodies 🧪. His work has earned accolades for bridging research and practice in farming systems, and he has been frequently invited as a keynote speaker 🎤 at global conferences in AI for agriculture and decision support systems. Under his leadership, several European Union and international collaborative projects have won funding and academic praise 💼💡. His active role in mentoring, publishing, and innovating across disciplines has made him a respected and decorated figure in decision science and sustainable development. 🥇

🧰 Research Skills

Dr. Plà-Aragonès possesses advanced skills in mathematical modeling, optimization, stochastic processes, and simulation modeling 🔢. He is adept in applying Markov Decision Processes, Multi-Criteria Decision Analysis (MCDA), and AI algorithms to develop decision-support tools for agriculture and health sectors 🌱🏥. His programming capabilities span R, Python, and MATLAB, while his modeling expertise extends to GAMS, LINGO, and AnyLogic 💻. He’s proficient in integrating data analytics, machine learning, and cloud-based architectures for developing scalable, digital decision systems ☁️🤖. Dr. Plà’s multidisciplinary skills allow him to lead cross-border research, publish in top-tier journals 📚, and translate theory into practical tools for industry. His ability to synthesize quantitative methods into actionable solutions defines his technical excellence. ⚙️

Publications Top Note 📝

  • Title: Operational research models applied to the fresh fruit supply chain
    Authors: WE Soto-Silva, E Nadal-Roig, MC González-Araya, LM Plà-Aragonès
    Year: 2016
    Citations: 337
    Source: European Journal of Operational Research, 251(2), 345-355

  • Title: Sugar cane transportation in Cuba, a case study
    Authors: EL Milan, SM Fernandez, LMP Aragones
    Year: 2006
    Citations: 132
    Source: European Journal of Operational Research, 174(1), 374-386

  • Title: Optimizing fresh food logistics for processing: Application for a large Chilean apple supply chain
    Authors: WE Soto-Silva, MC González-Araya, MA Oliva-Fernández, et al.
    Year: 2017
    Citations: 123
    Source: Computers and Electronics in Agriculture, 136, 42-57

  • Title: A perspective on operational research prospects for agriculture
    Authors: LM Plà, DL Sandars, AJ Higgins
    Year: 2014
    Citations: 101
    Source: Journal of the Operational Research Society, 65(7), 1078–1089

  • Title: Review of mathematical models for sow herd management
    Authors: LM Plà
    Year: 2007
    Citations: 66
    Source: Livestock Science, 106(2–3), 107–119

  • Title: New opportunities in operations research to improve pork supply chain efficiency
    Authors: SV Rodríguez, LM Plà, J Faulin
    Year: 2014
    Citations: 63
    Source: Annals of Operations Research, 219, 5–23

  • Title: A Markov decision sow model representing the productive lifespan of herd sows
    Authors: LM Plà, C Pomar, J Pomar
    Year: 2003
    Citations: 53
    Source: Agricultural Systems, 76(1), 253–272

  • Title: Environmental assessment of a pork-production system in North-East of Spain focusing on life-cycle swine nutrition
    Authors: C Lamnatou, X Ezcurra-Ciaurriz, D Chemisana, LM Plà-Aragonès
    Year: 2016
    Citations: 52
    Source: Journal of Cleaner Production, 137, 105–115

  • Title: Optimal transport planning for the supply to a fruit logistic centre
    Authors: E Nadal-Roig, LM Plà-Aragonès
    Year: 2015
    Citations: 51
    Source: Handbook of Operations Research in Agriculture and the Agri-Food Industry

  • Title: Modeling tactical planning decisions through a linear optimization model in sow farms
    Authors: SV Rodríguez-Sánchez, LM Plà-Aragonès, VM Albornoz
    Year: 2012
    Citations: 50
    Source: Livestock Science, 143(2–3), 162–171

  • Title: Production planning of supply chains in the pig industry
    Authors: E Nadal-Roig, LM Plà-Aragonès, A Alonso-Ayuso
    Year: 2019
    Citations: 42
    Source: Computers and Electronics in Agriculture, 161, 72–78

  • Title: A two-stage stochastic programming model for scheduling replacements in sow farms
    Authors: SV Rodríguez, VM Albornoz, LM Plà
    Year: 2009
    Citations: 42
    Source: TOP, 17, 171–189

  • Title: Handbook of operations research in agriculture and the agri-food industry
    Author: LM Plà-Aragonès
    Year: 2015
    Citations: 41
    Source: Springer New York

  • Title: Selection of slaughterhouse to deliver fattened pigs depending on growth curves
    Authors: Y Bao, P Llagostera, D Babot, LM Plà-Aragonès
    Year: 2025
    Source: Agricultural Systems, 229, 104406

  • Title: Mathematical methods applied to the problem of dairy cow replacements: a scoping review
    Authors: O Palma, LM Plà-Aragonès, A Mac Cawley, VM Albornoz
    Year: 2025
    Source: Animals, 15(7), 970

  • Title: A genetic algorithm for site-specific management zone delineation
    Authors: F Huguet, LM Plà-Aragonès, VM Albornoz, M Pohl
    Year: 2025
    Source: Mathematics, 13(7), 1064

  • Title: A deep learning approach for image analysis and reading body weight from digital scales in pigs farms
    Authors: NA Reyes-Reyes, MC Doja, P Llagostera-Blasco, LM Plà-Aragonès, et al.
    Year: 2025
    Source: IEEE Access

  • Title: Mathematical Methods Applied to the Problem of Dairy Cow Replacements: A Scoping Review
    Authors: O Palma, LM Plà-Aragonès, A Mac Cawley, VM Albornoz
    Year: 2025
    Source: System, 26, 11

🧭 Conclusion

Dr. Luis Miguel Plà-Aragonès exemplifies the fusion of theoretical innovation and practical impact in mathematical modeling 🌍. With a foundation built on rigorous education 🎓 and two decades of professional excellence 💼, he has become a global leader in using operations research to solve real-world problems in agriculture, environment, and health 🌾💊♻️. His interdisciplinary collaborations, influential publications, and award-winning leadership reflect a visionary commitment to data-driven decision-making 📈. By integrating AI, cloud systems, and analytics into sustainable frameworks, Dr. Plà is shaping the future of intelligent agriculture and policy modeling 🤖. His dedication to mentorship, international outreach, and technological innovation makes him not only a researcher of high distinction but also a catalyst for global scientific progress. 🏆

Huanlao Liu | Control Theory | Best Researcher Award

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Prof. Dr. Huanlao Liu | Control Theory | Best Researcher Award

Professor at Guangdong Ocean University, China

Professor Huanlao Liu 👨‍🏫, a leading academic at Guangdong Ocean University 🏛️, specializes in CNC Equipment Technology ⚙️, Intelligent Manufacturing 🤖, and Production Line Automation Retrofitting 🔧. With over 23 publications in SCI/Scopus-indexed journals 📚 and 13 patents 🧾, his research bridges theoretical innovation with industrial application. As the Discipline Leader of Guangdong’s Key Mechanical Engineering Program 🏅, he has significantly contributed to the advancement of smart manufacturing and dynamic system modeling. His recent works on geometric error modeling and measurement methods in CNC tools 🛠️ have received scholarly recognition. Though further engagement in consultancy and professional affiliations could strengthen his profile, his consistent innovation, research leadership, and focus on future-forward technologies make him a distinguished candidate for the Best Researcher Award 🏆.

Professional Profile 

Scopus Profile

🎓 Education

Professor Huanlao Liu 👨‍🏫 holds a solid academic foundation in mechanical and manufacturing engineering, specializing in CNC systems and automation technology ⚙️. His academic journey reflects a commitment to interdisciplinary learning, integrating traditional engineering principles with modern intelligent manufacturing practices 🤖. Over the years, he has developed a strong theoretical background, enabling his successful transition into applied industrial research. His continuous pursuit of knowledge through advanced degrees and certifications 🎓 has positioned him as an expert in precision machinery and digital automation. His education not only provided the technical groundwork but also sparked a passion for innovation and system optimization 🔬. Prof. Liu’s academic credentials support his ability to lead complex research in advanced production technologies and contribute to the growth of future manufacturing professionals across China and beyond 🌏.

💼 Professional Experience

Prof. Huanlao Liu has accumulated significant experience as a Professor at Guangdong Ocean University 🏛️, where he has led academic programs, supervised research, and developed industrial partnerships. His role as the Discipline Leader of Guangdong’s Key Mechanical Engineering Program 🏅 has allowed him to influence curriculum development, research funding, and strategic innovation initiatives. With a career rooted in CNC equipment dynamics, automation retrofitting, and intelligent manufacturing systems 🔧🤖, Prof. Liu has applied his technical expertise to real-world challenges. He has been instrumental in building advanced labs, mentoring graduate researchers, and publishing high-impact studies in top-tier journals 📚. His professional journey is marked by a commitment to integrating research with education and contributing toward technological modernization in China’s manufacturing sector 🏭.

🔬 Research Interests

Prof. Liu’s research interests lie at the intersection of CNC Equipment Technology ⚙️, Intelligent Manufacturing 🤖, Machine Tool Dynamics 📐, and Production Line Automation Retrofitting 🔧. His work is centered on enhancing the precision, stability, and automation of advanced manufacturing systems. He is particularly focused on error modeling, real-time system control, and data-driven optimization for CNC machinery 🛠️. Through applied research, he aims to close the gap between theoretical innovation and industrial deployment, aligning with Industry 4.0 objectives 🌐. His studies also explore the integration of machine learning with mechanical systems, pushing the boundaries of what traditional CNC systems can achieve. Prof. Liu is committed to building intelligent, adaptive, and high-efficiency production ecosystems that respond to modern industrial demands 📊.

🏆 Awards and Honors

While formal listings of national or international awards were not provided, Prof. Huanlao Liu’s recognition as the Discipline Leader of a key provincial engineering program 🏅 speaks volumes about his academic standing and influence. His 13 patents 🧾 and 23+ peer-reviewed journal publications 📚 have earned him scholarly acclaim in CNC and automation domains. His leadership has led to strategic upgrades in mechanical engineering education and research infrastructure in Guangdong province. These achievements reflect his dedication and the trust placed in him by the academic and research community 🌟. As a prominent voice in intelligent manufacturing and automation, Prof. Liu continues to receive invitations for research projects and academic evaluations, underscoring his ongoing impact and contributions to the field 🎖️.

🧠 Research Skills

Prof. Liu exhibits advanced research skills in geometric error modeling, real-time measurement systems, and support vector regression analysis for CNC tools 📈. His expertise spans both hardware and software aspects of machine tool dynamics, including system calibration, optimization, and retrofitting techniques 🛠️. He is adept at designing experiments, patenting innovations, and publishing in high-impact journals 🔬. His technical toolset includes mathematical modeling, machine learning integration, and multi-sensor system design for intelligent automation applications 🤖. In addition to technical skills, he demonstrates strong project leadership, interdisciplinary collaboration, and mentorship abilities 👥. These combined research skills allow him to translate complex engineering theories into practical solutions that enhance production efficiency and system reliability in smart manufacturing environments ⚡.

Publications Top Note 📝

  • Title: Coating Extrusion Characteristics of Thin-Walled Tubes for Catheters Using Thermoplastic Elastomer

    • Journal: Polymers (Open Access)

    • Year: 2025

    • Citations: 1

    • Source: Indexed in Scopus/SCI

  • Title: Identification of Rotary Axes PIGEs of Five-axis CNC Machines with Double Rotary Tables

    • Journal: Zhongguo Jixie Gongcheng (China Mechanical Engineering)

    • Year: 2024

    • Source: Indexed in Chinese Core Journals

  • Title: A Support Vector Regression-Based Method for Modeling Geometric Errors in CNC Machine Tools

    • Authors: Chuanjing Zhang, Huanlao Liu*, Qunlong Zhou, Yulin Wang

    • Journal: The International Journal of Advanced Manufacturing Technology

    • Year: 2024

    • Citations: 10

    • Source: SCI / Springer Nature

📝 Conclusion

Prof. Huanlao Liu stands out as a dynamic academic and innovative researcher in the fields of CNC technology and intelligent manufacturing 🌟. With a strong blend of theoretical knowledge, hands-on technical skills, and leadership experience, he has significantly contributed to modernizing China’s industrial systems 🏭. His research, enriched by 23 publications and 13 patents 📚🧾, is geared toward shaping the future of automated and data-driven production. Although there is scope to expand his professional affiliations and industry collaborations, his academic journey reflects excellence, dedication, and consistent innovation 🔍. Prof. Liu’s contributions not only enhance current manufacturing practices but also pave the way for next-generation smart systems. He remains a worthy candidate for recognition such as the Best Researcher Award 🏆.