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 

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🎓 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. 🏆

Antonio Di Stefano | Mathematical Economics | Best Researcher Award

Prof. Dr. Antonio Di Stefano | Mathematical Economics | Best Researcher Award

Full Prof. Pharmaceutical Thecnology and Pharmacoeconomics at University of Chieti-Pescara, Italy

Prof. Dr. Antonio Di Stefano 🎓, a Full Professor at the University of “G. d’Annunzio” Chieti-Pescara 🇮🇹, is a pioneering force in pharmaceutical technology, socioeconomics, and legislation. With dual degrees in Chemistry and Pharmaceutical Technology and Pharmacy, and a Ph.D. in Medicinal Chemistry 🧪, he has led groundbreaking research on dopaminergic and serotoninergic ligands, prodrugs for Parkinson’s and Alzheimer’s diseases 🧠, and advanced nanocarrier drug delivery systems 🚀. His work targets bacterial biofilms and antibiotic resistance through innovative nanoformulations. Author of over 140 high-impact publications, patents, and international presentations 📚🌍, he also serves as CEO of the spin-off “Algo Biotechnologies,” merging academic insight with industrial application 💼🔬. Prof. Di Stefano’s research is both transformative and translational, earning him global recognition and making him an ideal candidate for the Best Researcher Award 🏆. His visionary contributions continue to reshape pharmaceutical frontiers and inspire future innovations.

Professional Profile 

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🎓 Education

Prof. Dr. Antonio Di Stefano holds an exceptional academic foundation rooted in pharmaceutical sciences. He earned his degree in Chemistry and Pharmaceutical Technology (CTF) in 1989 and later completed a Pharmacy degree in 1995 from the University of Camerino 🇮🇹. In 1994, he was awarded a Ph.D. in Medicinal Chemistry, equipping him with deep scientific expertise in drug synthesis and molecular design 🔬. His doctoral studies were pivotal, focusing on novel dopaminergic ligands, paving the way for his future contributions in neuromedicine. The rich blend of chemical, biological, and therapeutic knowledge he acquired during these formative years forms the backbone of his scientific precision and innovation 📘. His education is marked not only by credentials but by an immersive dedication to the evolving complexity of pharmaceutical innovation, making him a robust academic cornerstone and a lifelong scholar of molecular therapeutics.

💼 Professional Experience

Prof. Di Stefano’s illustrious career spans over three decades, marked by academic, research, and entrepreneurial accomplishments. He began as a supervisor in analytical labs for a food company before transitioning into academia through a C.N.R. research fellowship and a postdoctoral position focusing on dopaminergic ligand synthesis 🧪. In 1996, he was appointed Assistant Professor at the University of Chieti-Pescara, steadily rising to Associate Professor in 2003, and achieving Full Professorship in 2011 🎓. His role bridges teaching, research, and leadership within the Department of Pharmacy. He is also the CEO of Algo Biotechnologies, a university spin-off transforming research insights into commercial biotech solutions 🚀. His trajectory showcases a seamless integration of scientific exploration and innovation, industry engagement, and educational mentorship. This robust professional palette amplifies his influence across the pharmaceutical, biomedical, and academic ecosystems, creating a legacy of transformative learning and discovery.

🔬 Research Interest

Prof. Di Stefano’s research focuses on neurodegenerative disease therapies, particularly Parkinson’s and Alzheimer’s, with groundbreaking efforts in prodrug design and nanocarrier systems 🌐. He delves into advanced pharmaceutical formulations such as solid lipid nanoparticles, polymeric delivery systems, and clay-based nanocomposites for targeted therapy and enhanced brain bioavailability 🧠. His interdisciplinary studies also address antimicrobial resistance, utilizing biofilm-disrupting agents and codrug strategies to combat pathogenic bacteria 🦠. By integrating synthetic chemistry with biotechnology, his innovations have led to novel serotonergic ligands and multifunctional drug conjugates. He’s also at the frontier of developing algorithm-driven pharmaceutical selection through his spin-off, pushing the boundaries of digital health and precision medicine 🤖📊. With over 140 publications, his dynamic and translational research portfolio stands at the intersection of chemistry, biology, and pharmacology, continuously propelling forward the future of therapeutic development and patient-centric drug design.

🏅 Awards and Honors

Prof. Di Stefano’s impactful scholarship and translational contributions have earned him widespread recognition 🌟. Although specific named awards are not listed, his status as a Full Professor and CEO of a biotech spin-off reflects a highly esteemed professional reputation in academia and industry alike. His invitation to contribute to major journals, books, and international conferences testifies to his global stature and thought leadership 📚🌍. He has been entrusted with directing cutting-edge pharmaceutical research, mentoring young scientists, and leading interdisciplinary collaborations—hallmarks of professional distinction and peer respect 🧑‍🏫. The sustained excellence in his publication record and his role in impactful biotechnological innovations signal an individual whose work is not only academically rigorous but socially and therapeutically consequential. These continuous accolades and responsibilities strongly position him as an influential figure worthy of high honors, including the Best Researcher Award 🏆.

 Conclusion

Prof. Dr. Antonio Di Stefano exemplifies the gold standard of academic brilliance, research innovation, and translational science 💡. His career bridges molecular chemistry, pharmaceutical technology, and entrepreneurial biotechnology—demonstrating a visionary approach to modern healthcare challenges 🔄. Through pioneering work in nanomedicine, prodrug synthesis, and neurodegenerative disorder therapeutics, he has contributed meaningfully to both foundational science and practical clinical applications. His commitment to student mentorship, peer collaboration, and industrial advancement underlines a holistic and human-centric academic philosophy 🧑‍🔬. Beyond scholarly excellence, his role as a biotech leader showcases his commitment to real-world impact and innovation scalability 🚀. Prof. Di Stefano is a compelling candidate for the Best Researcher Award, a title befitting his dedication, achievements, and profound influence on global pharmaceutical research. His continued contributions promise to shape the future of drug development and patient care in unprecedented ways.

Publications Top Notes

🧠 Synthesis and Characterization of Memantine-Loaded Niosomes for Enhanced Alzheimer’s Disease Targeting

Authors: H. Türkez, S. Oner, O. Caglar, A. Di Stefano, A. Mardinoğlu
Year: 2025
Source: Pharmaceutics 🧴🧬
🔗 Open access
📌 A precision-targeted approach in Alzheimer’s therapy via smart vesicle design.


🧪 Targeting Alzheimer’s Disease with Novel Dual-Function 3,5-Diaryl-4,5-Dihydro-1H-Pyrazole-1-Carbothioamide Derivatives

Authors: A. Katsogiannou, D. Karta, A. Di Stefano, S. Vassiliou, I. Cacciatore
Year: 2024
Source: European Journal of Medicinal Chemistry Reports 🧠💊
📌 A dual-acting molecular strategy to modulate neurodegeneration.


🩹 CAPE Derivatives: Multifaceted Agents for Chronic Wound Healing

Authors: M.F. Balaha, A. Cataldi, A. Ammazzalorso, A. Przekora-Kuśmierz, V. Di Giacomo
Year: 2024
Citations: 3
Source: Archiv der Pharmazie 🧫🌿
📌 Plant-inspired therapeutic scaffolds with regenerative properties.


💧 From Self-Assembly to Healing: Engineering Ultra-Small Peptides into Supramolecular Hydrogels for Controlled Drug Release

Authors: M.P. Dimmito, L. Marinelli, I. Cacciatore, A. Di Stefano, P. Caliceti
Year: 2024
Citations: 4
Source: International Journal of Pharmaceutics 🌐🧵
📌 Supramolecular innovations for smart therapeutic delivery.


🔥 Advancements in Inflammatory Bowel Disease Management: From Traditional Treatments to Monoclonal Antibodies and Future Drug Delivery Systems

Authors: A. Di Rienzo, L. Marinelli, M.P. Dimmito, A. Di Stefano, I. Cacciatore
Year: 2024
Source: Pharmaceutics (Review) 🧬🧃
📌 Exploring past, present, and futuristic gastrointestinal therapeutics.


🧵 Self-Assembling Peptides (SAPs) as Powerful Tools for the Preparation of Antimicrobial and Wound-Healing Nanostructures

Authors: M.P. Dimmito, L. Marinelli, I. Cacciatore, A. Rapino, A. Di Stefano
Year: 2024
Citations: 1
Source: Pharmaceutics (Review) 🧫🧵
📌 Modular nanostructures to combat infections and promote tissue repair.


🌿 Exploring the Therapeutic Potential of Cinnamoyl Derivatives in Attenuating Inflammation in Lipopolysaccharide-Induced Caco-2 Cells

Authors: M. Reale, E. Costantini, L. Aielli, A. Di Stefano, I. Cacciatore
Year: 2024
Source: Future Medicinal Chemistry 🌿🧪
📌 Cinnamoyl-based anti-inflammatory molecules spotlighted in intestinal models.


🧬 Aptamers-Based Strategies for the Treatment of Microbial Infections

Authors: A. Di Rienzo, L. Marinelli, A. Di Stefano, G. Vicaretti, I. Cacciatore
Year: 2024
Citations: 3
Source: Pharmaceutics (Review) 🧫🔬
📌 Nucleic acid therapeutics redefining pathogen combat strategies.


🧠 Anticancer Potential of Novel Cinnamoyl Derivatives against U87MG and SHSY-5Y Cell Lines

Authors: N. Gouleni, A. Di Rienzo, S. Oner, S. Vassiliou, I. Cacciatore
Year: 2024
Citations: 1
Source: Anti-Cancer Agents in Medicinal Chemistry 🧬💥
📌 Neuro-oncology meets natural product innovation.


🌶️ Solid Lipid Nanoparticles for Efficient Delivery of Capsaicin-Rich Extract: Potential Neuroprotective Effects in Parkinson’s Disease

Authors: L. Marinelli, M.P. Dimmito, I. Cacciatore, S. Fulle, A. Di Stefano
Year: 2024
Citations: 6
Source: Journal of Drug Delivery Science and Technology 🌶️🧠
📌 Nanocarrier-mediated neuromodulation using spice-derived actives.

Ka-Hou Chan | Game Theory | Best Researcher Award

Dr. Ka-Hou Chan | Game Theory | Best Researcher Award

Researcher at Macao Polytechnic University, China

Dr. Ka-Hou Chan is a distinguished researcher specializing in algorithm analysis, video coding optimization, image processing, parallel computing, neural networks, and computer graphics. He earned his Ph.D. in Computer Applied Technology from Macao Polytechnic University in 2023, following his M.Sc. in Software Engineering from the University of Macau and a B.Sc. in Software Technology and Application from Macau University of Science and Technology. With extensive experience in academia and research, he has contributed significantly to real-time video captioning, humanoid vision, and deep analysis of surveillance videos. Dr. Chan has been involved in major funded research projects and has published extensively in high-impact journals, focusing on AI-driven video processing and machine learning applications. His expertise and innovative contributions make him a strong candidate for the Best Researcher Award, demonstrating excellence in advancing computational methodologies and applications in artificial intelligence, video compression, and neural network optimization.

Professional Profile 

Google Scholar
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Education

Dr. Ka-Hou Chan obtained his Ph.D. in Computer Applied Technology from Macao Polytechnic University in 2023, where he specialized in algorithm analysis, video coding optimization, and neural networks. Before that, he earned his M.Sc. in Software Engineering from the University of Macau, gaining expertise in software design, AI-driven applications, and real-time computing. His academic journey began with a B.Sc. in Software Technology and Application from Macau University of Science and Technology, where he developed a strong foundation in programming, computer vision, and data analysis. Throughout his academic career, Dr. Chan engaged in rigorous research, contributing to cutting-edge advancements in image processing, deep learning, and computational optimization. His interdisciplinary academic background has shaped his ability to tackle complex computational problems, making him a key contributor to AI-driven video analytics and intelligent computing. His education has provided him with the theoretical knowledge and practical skills to drive innovation in artificial intelligence and software technologies.

Professional Experience

Dr. Ka-Hou Chan has amassed extensive experience in academia and research, focusing on artificial intelligence, video compression, and neural network optimization. He has been actively involved in several major research projects related to deep learning applications in video processing and surveillance analysis. As a researcher, he has contributed to the development of real-time video captioning, humanoid vision systems, and AI-driven multimedia analytics. He has also collaborated with international institutions and industry partners to improve the efficiency of video coding and parallel computing models. His work extends beyond research, including teaching engagements where he mentors students in AI, computer vision, and computational algorithms. Dr. Chan has also served as a reviewer for high-impact journals, assessing groundbreaking research in artificial intelligence and image processing. His professional contributions demonstrate his commitment to pushing the boundaries of AI and machine learning, bridging the gap between theoretical advancements and real-world applications.

Research Interest

Dr. Ka-Hou Chan’s research interests lie at the intersection of artificial intelligence, video processing, and deep learning. His primary focus is on algorithm optimization for real-time video captioning, surveillance video analysis, and AI-driven image enhancement. He has made significant contributions to video coding efficiency, exploring novel compression techniques to enhance transmission and storage capabilities. Additionally, his work in neural network optimization seeks to improve computational efficiency for AI models applied in image recognition, motion detection, and intelligent video analytics. Dr. Chan is also interested in the application of parallel computing and high-performance computing techniques to enhance deep learning training processes. His research is highly interdisciplinary, integrating computer vision, software engineering, and AI methodologies to solve complex computational problems. Through his innovative work, he aims to advance the field of intelligent computing, contributing to the next generation of AI-driven multimedia applications and enhancing real-time data processing capabilities.

Awards and Honors

Dr. Ka-Hou Chan has received several accolades for his outstanding contributions to artificial intelligence, video processing, and algorithm development. His research achievements have been recognized in high-impact academic awards and prestigious AI symposiums. He has been the recipient of multiple research grants and funding awards, supporting his groundbreaking work in neural networks and video coding optimization. Dr. Chan has also been acknowledged for his excellence in academia, receiving best paper awards for his contributions to AI-driven image processing and deep learning-based video analytics. His research has been cited widely, further cementing his impact in the field. Additionally, he has served as an invited speaker at AI awards, sharing his insights on computational intelligence and algorithmic advancements. His dedication to research excellence and innovation has established him as a leading figure in AI-driven multimedia applications, earning him a strong reputation within the scientific and academic communities.

Conclusion

Dr. Ka-Hou Chan is a highly accomplished researcher specializing in artificial intelligence, video processing, and neural network optimization. With a robust academic background and extensive research experience, he has made significant contributions to AI-driven multimedia analytics, enhancing real-time video captioning and intelligent surveillance systems. His work in algorithm optimization and deep learning has paved the way for advancements in computer vision, video compression, and computational intelligence. Recognized through numerous awards and research grants, Dr. Chan continues to push the boundaries of AI innovation, impacting both academia and industry. His interdisciplinary expertise, combined with his commitment to research excellence, positions him as a leader in intelligent computing and software engineering. As he continues to explore the frontiers of AI and machine learning, Dr. Chan remains dedicated to developing cutting-edge solutions that revolutionize video analytics, deep learning applications, and high-performance computing.

Publications Top Noted

  • Multimodal Cross Global Learnable Attention Network for MR Images Denoising with Arbitrary Modal Missing

    • Authors: Mingfu Jiang, Shuai Wang, Ka-Hou Chan, Hing-Chiu Chang, Tao Tan
    • Year: 2025
    • Source: Computerized Medical Imaging and Graphics
  • GAT-Based Bi-CARU with Adaptive Feature-Based Transformation for Video Summarisation

    • Authors: Ka-Hou Chan, Sio-Kei Im
    • Year: 2024
    • Source: Technologies
  • Local Feature-Based Video Captioning with Multiple Classifier and CARU-Attention

    • Authors: Sio-Kei Im, Ka-Hou Chan
    • Year: 2024
    • Citations: 1
    • Source: IET Image Processing
  • Faster Intra-Prediction of Versatile Video Coding Using a Concatenate-Designed CNN via DCT Coefficients

    • Authors: Sio-Kei Im, Ka-Hou Chan
    • Year: 2024
    • Citations: 1
    • Source: Electronics (Switzerland)
  • Neural Machine Translation with CARU-Embedding Layer and CARU-Gated Attention Layer

    • Authors: Sio-Kei Im, Ka-Hou Chan
    • Year: 2024
    • Citations: 4
    • Source: Mathematics
  • Dynamic Estimator Selection for Double-Bit-Range Estimation in VVC CABAC Entropy Coding

    • Authors: Sio-Kei Im, Ka-Hou Chan
    • Year: 2024
    • Citations: 2
    • Source: IET Image Processing
  • CABAC-Based ROI Encryption with Mask R-CNN for VVC Codec

    • Authors: Sio-Kei Im, Ka-Hou Chan
    • Year: 2024
    • Source: Conference Paper
  • Light-Field Image Super-Resolution with Depth Feature by Multiple-Decouple and Fusion Module

    • Authors: KH Chan, SK Im
    • Year: 2024
    • Citations: 4
    • Source: Electronics Letters, Volume 60 (1), e13019
  • Parallel Dense Video Caption Generation with Multi-Modal Features

    • Authors: X Huang, KH Chan, W Ke, H Sheng
    • Year: 2023
    • Citations: 4
    • Source: Mathematics, Volume 11 (17), 3685
  • Distributed Spatial Transformer for Object Tracking in Multi-Camera

    • Authors: SK Im, KH Chan
    • Year: 2023
    • Citations: 4
    • Source: 2023 25th International Conference on Advanced Communication Technology
  • A Propagation Model for Package Loss Refinement in VVC

    • Authors: SK Im, KH Chan
    • Year: 2022
    • Citations: 4
    • Source: Electronics Letters, Volume 58 (20), 759-761
  • 2021 IEEE 4th International Conference on Computer and Communication Engineering Technology (CCET)

    • Authors: KH Chan, G Pau, SK Im
    • Year: 2021
    • Citations: 4
    • Source: IEEE