Lluis Miquel | Operations Research | Mathematical Modeling Breakthrough Award

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. 🏆

Bin Wang | Operations Research | Excellence in Innovation

Prof. Dr. Bin Wang | Operations Research | Excellence in Innovation

Professor at Anhui University of Chinese Medicine, China

Dr. Bin Wang 🎓, a distinguished researcher at the Key Laboratory of Xin’an Medicine, Anhui University of Chinese Medicine 🏛️, specializes in the scientific exploration of Traditional Chinese Medicine (TCM) 🌿. With a Ph.D. in Organic Chemistry from the University of Science and Technology of China 🧪, his innovative work focuses on the identification, structural analysis, and quality control of immunologically active polysaccharides. Dr. Wang has published extensively in high-impact journals 📚, contributing over 15 peer-reviewed articles that bridge traditional remedies with modern analytical techniques. His research enhances the functional food potential and pharmacological understanding of herbal medicines. Passionate about integrating chemistry, medicine, and health 🌱⚗️, Dr. Wang’s work is shaping the future of evidence-based TCM. His dedication and scientific excellence make him a valuable contributor to global health innovation 🌍💡.

Professional Profile 

Scopus Profile
ORCID Profile

🎓 Education

Dr. Bin Wang earned his Ph.D. in Organic Chemistry 🧪 from the University of Science and Technology of China, under the mentorship of Prof. Zhiyong Wang. Prior to that, he completed his M.S. in Physical Chemistry ⚛️ at Hunan University with Prof. Bingxin Cai and his B.S. in Chemistry 🧫 from West Anhui University. His solid academic foundation spans organic synthesis, analytical methods, and chemical applications in traditional medicine. With a cross-disciplinary background, Dr. Wang has consistently blended theory with real-world medicinal chemistry, setting the stage for his career in Traditional Chinese Medicine (TCM) research. This strong educational journey reflects his commitment to scientific rigor and innovation in the biochemical understanding of herbal medicine 🌿🔬.

 🏛️ Professional Experience

Currently serving at the Key Laboratory of Xin’an Medicine, Ministry of Education, Anhui University of Chinese Medicine 🏛️, Dr. Bin Wang plays a pivotal role in advancing analytical methods for TCM. As a research leader, he directs high-impact studies focused on polysaccharide identification and bioactivity analysis 📈. Over the years, he has collaborated with leading pharmacologists, chemists, and clinicians, bridging traditional herbal wisdom with modern scientific validation. Dr. Wang’s career reflects his strong academic leadership, lab excellence, and mentorship of emerging scholars 🧑‍🔬. His expertise is also frequently sought after in interdisciplinary projects and national-level TCM development initiatives, contributing to policy, product innovation, and public health impact across China 🇨🇳🔍.

🔬 Research Interest

Dr. Wang’s research lies at the intersection of natural product chemistry and bioactive polysaccharides from traditional Chinese medicinal herbs 🌿. His key interests include the structural elucidation of complex sugars, their pharmacological effects, and quality control of herbal ingredients using modern chromatographic and spectroscopic tools 💊📊. He’s particularly known for applying advanced techniques like UHPLC-QTOF/MS, response surface methodology, and chemometric modeling to evaluate antioxidant, anti-inflammatory, and immune-modulating properties. With a focus on TCM modernization, Dr. Wang aims to unlock therapeutic pathways and improve herbal drug standardization for global health applications 🌍⚗️. His work not only improves clinical outcomes but also supports the credibility of traditional practices in contemporary pharmacological science.

🏅 Awards & Honors

Dr. Wang’s contributions have earned him widespread recognition 🏆 across the fields of TCM and analytical chemistry. He has co-authored impactful papers in renowned journals such as Frontiers in Nutrition, RSC Advances, and International Journal of Biological Macromolecules 📚. His polysaccharide research has been instrumental in achieving breakthrough formulations and enhanced bioactivity testing methods. Though not all honors may be publicly listed, his consistent presence in high-indexed publications, involvement in critical national research projects, and peer respect underscore his role as an innovator 🌟. His growing citation record and influence in the modernization of TCM validate his candidacy for honors such as “Excellence in Innovation” and other research distinction awards 🥇.

🧠 Research Skills

Dr. Wang possesses a comprehensive skill set that spans organic synthesis, natural product extraction, mass spectrometry, and chromatographic fingerprinting 🔬. He is highly proficient in using HPLC, UV, UHPLC-QTOF/MS, LC-MS/MS, and chemometric tools to analyze the structural and functional properties of TCM polysaccharides. His strong command over statistical validation techniques (like response surface methodology and Lambert–Beer Law integration 📈) has made his analytical protocols highly reproducible. Beyond lab work, he excels at scholarly writing, cross-disciplinary team leadership, and method development for quality assurance in herbal pharmacology 🌿💼. These skills enable him to transform ancient remedies into scientifically verified therapeutics, making him a torchbearer for evidence-based traditional medicine 🌟.

Publications Top Note 📝

  • Discrimination of Polygonatum Species via Polysaccharide Fingerprinting: Integrating Their Chemometrics, Antioxidant Activity, and Potential as Functional Foods

    • Authors: Z. Liu, W. Zhang*, Bin Wang*

    • Year: 2025

    • Source: Foods, Article 14(13):2385. DOI: 10.3390/foods14132385

  • Mitsunobu Reaction: Assembling C–N Bonds in Chiral Traditional Chinese Medicine

    • Authors: X. Zhou, L. Xu, Z. Ma, J. Cui, B. Wang*

    • Year: 2025

    • Source: RSC Advances, Vol. 15, p. 5167–5189. DOI: 10.1039/D4RA08573F

  • Simultaneous Determination of Naphthalimide-Labeled Monosaccharides in P. cyrtonema Polysaccharides Utilizing HPLC‑UV

    • Authors: J. Du, X. Zhou, L. Chen, L. Xu, B. Wang*

    • Year: 2025

    • Source: Analytical Methods, Vol. 17, pp. 1196–1205.

  • Structural Characteristics and Biological Activity of a Water-Soluble Polysaccharide HDCP‑2 from Camellia sinensis

    • Authors: Q. Sun, J. Du, Z. Wang, X. Li, R. Fu, H. Liu, N. Xu*, G. Zhu*, B. Wang*

    • Year: 2024

    • Source: International Journal of Biological Macromolecules, 277:134437.

  • Structural Characterization and Antioxidant Activity of Processed Polysaccharides PCP‑F1 from Polygonatum cyrtonema

    • Authors: Y. Zhao, Z. Wang, R. Fu, R. Xie*, B. Wang*, Q. Li*

    • Year: 2023

    • Source: Frontiers in Nutrition, 10:1272977.

  • A Novel Method for Pre‑Column Derivatization of Saccharides from Polygonatum cyrtonema by Integrating Lambert–Beer Law and RSM

    • Authors: H. Liu, Y. Zhao, L. Chen, J. Du, H. Guo*, B. Wang*

    • Year: 2023

    • Source: Molecules, 28:2186.

  • Structural Characterization and Anti‑Inflammatory Activity of a Novel Polysaccharide PKP2‑1 from Polygonatum kingianum

    • Authors: Z. Wang, H. Liu, R. Fu, J. Ou*, B. Wang*

    • Year: 2023

    • Source: Frontiers in Nutrition, 10:1156798.

  • Comprehensive Evaluation and Anti‑Inflammatory Activity of “Zhi” Polygonatum cyrtonema Produced by Classical Steaming

    • Authors: Z. Wang, R. Xie*, B. Wang*

    • Year: 2023

    • Source: Pharmacological Research – Modern Chinese Medicine, 6:100229.

  • Synthesis of Naphthalimide-Type Chemosensor and Its Application in Quality Evaluation for Polygonatum sibiricum Red

    • Authors: Z. Wang, Q. Sun, Y. Zhao, J. Du, B. Wang*

    • Year: 2022

    • Source: Frontiers in Chemistry, 10:969014.

  • A Novel Method for Investigating the Mechanism of Anti‑Rheumatoid Arthritis Activity of Angelica pubescentis Radix by UHPLC–QTOF/MS & Network Pharmacology

    • Authors: Z. Wang, H. Liu, Y. Cao, T. Zhang, H. Guo*, B. Wang*

    • Year: 2022

    • Source: Biomedical Chromatography, 36:e5389.

  • Polygonatum sibiricum Polysaccharide Prevents Depression-Like Behaviors by Reducing Oxidative Stress, Inflammation, and Cellular & Synaptic Damage

    • Authors: F. Shen, Z. Song, P. Xie, L. Li, B. Wang*, D. Peng*, G. Zhu*

    • Year: 2021

    • Source: Journal of Ethnopharmacology, 275:114164.

  • Screening Q‑Markers of TCMs from RA Rat Plasma via UHPLC‑QTOF/MS for Wu-Wei-Wen-Tong Capsule

    • Authors: H. Jiang, J. Liu*, Y. Wang, L. Chen, H. Liu, Z. Wang, B. Wang*

    • Year: 2021

    • Source: Journal of Mass Spectrometry, 56:e4711.

  • Effects of Borneol on Release of Compound Danshen Colon-Specific Osmotic Pump Capsule: In Vitro & Beagle Pharmacokinetics

    • Authors: L. Shao, C. Sun, W. Lu, J. Chen, D. Su, S. Gao, S. Chen, W. Fang, Y. Liu, B. Wang*, R. Hu*

    • Year: 2020

    • Source: AAPS PharmSciTech, 21:316.

  • UHPLC‑UV + UHPLC‑QTOF/MS Fingerprint for Nao‑Luo‑Xin‑Tong: Multi‑Wavelength Setting for TCM Prescription Composition

    • Authors: L. Wang, Y. Wang, G. Tong, Y. Li, M. Lei, H. Wu, B. Wang*, R. Hu*

    • Year: 2019

    • Source: Analytical Methods, 11:6092.

  • Simultaneous Analysis of Coumarin Derivatives in Radix Angelicae pubescentis by HPLC‑DAD‑ESI‑MSn

    • Authors: B. Wang*, X. Liu, A. Zhou, M. Meng, Q. Li*

    • Year: 2014

    • Source: Analytical Methods, 6:7996–8002.

🧾 Conclusion

Dr. Bin Wang stands out as a visionary scientist whose work bridges tradition and innovation 🌿🔬. With a robust academic background, high-impact publications, and cutting-edge research in TCM polysaccharides, he’s making vital contributions to herbal medicine modernization. His integration of advanced analytical chemistry with clinical relevance ensures that traditional practices meet contemporary scientific standards ⚖️. As a mentor, researcher, and innovator, Dr. Wang embodies the excellence, curiosity, and impact that define 21st-century research leadership 🌍. He is a strong contender for honors like the Excellence in Innovation Award, reflecting his commitment to translational research and sustainable health science development 🌱🏅.