Jordi Rodeiro | Computer Science | Best Researcher Award

Mr. Jordi Rodeiro | Computer Science | Best Researcher Award

 👤 Mr. Jordi Rodeiro, Institut de Recerca Sant Joan de Déu, Spain

Jordi Rodeiro Boliart is an accomplished International Computer Engineering and Sports Science graduate with a Master’s in Data Science and ongoing doctoral studies in Artificial Intelligence at La Salle Bonanova, Barcelona. Jordi is a dynamic professional blending a robust academic foundation with practical expertise. He is dedicated to leveraging data science and AI in health research, particularly autism prediction. With a deep passion for problem-solving and innovation, Jordi has conducted significant work in basketball analytics, biomedical data analysis, and medical imaging. His projects have included building Python tools, web applications, and dashboards that streamline decision-making. Jordi’s multilingual fluency in Catalan, Spanish, and English (C1) and his adaptability, critical thinking, and leadership skills underscore his commitment to excellence. As a mental health researcher, programming professor, and basketball coach, Jordi excels at interdisciplinary collaboration, fostering innovation, and making meaningful contributions to both academia and real-world applications.

Professional Profile

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🌟  Summary of Suitability for the Award

Jordi Rodeiro Boliart demonstrates an exceptional combination of academic excellence, multidisciplinary expertise, and impactful research, making him a strong candidate for the Research for Best Researcher Award. His academic journey spans multiple disciplines, including International Computer Engineering, Sports Science, and Data Science, culminating in a PhD in Artificial Intelligence and Autism Prediction. His diverse background equips him with a unique perspective in integrating technology, data science, and health research to address complex societal challenges.

Jordi’s research outputs reflect significant contributions to both applied and theoretical domains. Notably, his final master’s thesis focused on analyzing basketball data to enhance coaching strategies, while his degree project in the biomedical field led to a published scientific paper.

🎓 Education

Jordi Rodeiro Boliart boasts an impressive academic journey beginning with a dual degree in International Computer Engineering (La Salle, UPC) and Sports Science (INEFC Barcelona, UB). He further honed his expertise with a Master’s in Data Science (La Salle Bonanova, Barcelona), culminating in award-winning academic recognition. Currently pursuing a Ph.D. in Artificial Intelligence with a focus on autism prediction, Jordi demonstrates a commitment to cutting-edge research. His educational highlights include a final master’s thesis analyzing basketball data to enhance coaching strategies and a degree project in metabolomics published in a peer-reviewed journal. Jordi has also contributed to projects in medical imaging, such as using x-rays for illness detection. His academic journey is enriched by attending technology seminars at globally renowned institutions like Harvard and MIT, along with specialized training in leadership and organizational behavior. Jordi’s blend of technical and interdisciplinary studies defines his innovative, research-oriented career trajectory.

💼   Professional Experience

Jordi Rodeiro Boliart has a versatile professional background spanning research, teaching, and leadership. As a mental health researcher at Parc Sanitari Sant Joan de Déu, Jordi applies statistics and data science to critical health data, contributing to global assemblies and conferences. He serves as a university professor at La Salle Barcelona, teaching programming, mathematics, and IT software. As a data science intern at Sener, Jordi specialized in Power BI dashboards and analyzing corporate metrics. His engineering research internship included creating biomedical tools for metabolomic analysis, leading to a published paper. Jordi’s sports background complements his tech expertise, with roles as a basketball coach and coordinator, focusing on player development and team strategy. His earlier internships at Alfred Smart Systems and other engineering roles solidified his Python and gateway programming skills. Jordi’s diverse experiences exemplify his ability to integrate technology, data science, and education for impactful contributions.

🏅Awards and Recognitions

Jordi Rodeiro Boliart’s contributions have been widely recognized through various awards and honors. He received the prestigious Malaspina Award as part of the Empower consortium in 2023 and was a HackB finalist in the same year. Jordi was acknowledged with an academic excellence certificate for the best master’s record in Data Science (2023) and emerged as the LS Future Lab – Impact Challenge Hackathon winner in 2022. He represented his university as a National Model United Nations delegate in New York (2022) and participated in an international cooperation project in Perú. Jordi’s outstanding research on metabolomics earned him the opportunity to present at the Metabolomics 2022 conference. Beyond academia, Jordi is a certified Level II basketball coach, an FCBQ leadership trainee, and a master-certified Gannon Baker basketball coach. These accolades reflect his exceptional abilities in technical innovation, leadership, and interdisciplinary collaboration.

🌍  Research Skills On Computer Science

Jordi Rodeiro Boliart excels in applying advanced research methodologies to interdisciplinary challenges. His expertise includes data science, artificial intelligence, and object-oriented programming. Jordi has developed sophisticated tools for biomedical research, basketball analytics, and mental health studies. His doctoral research focuses on autism prediction through AI, combining statistical analysis and data visualization techniques. Jordi’s proficiency spans Python, MATLAB, MySQL, and Power BI, with skills in machine learning and medical image processing. He has designed Python programs to predict basketball outcomes, web apps for metabolomics, and diagnostic tools for x-rays. Jordi’s critical thinking, decision-making, and integrity define his research approach. His ability to present findings, such as at the Metabolomics 2022 conference, underscores his communication and analytical skills. Jordi’s research bridges academia and practical applications, demonstrating a commitment to addressing complex problems in health and technology.

📖 Publication Top Notes

1. The longitudinal relationship among physical activity, loneliness, and mental health in middle-aged and older adults: Results from the Edad con Salud cohort
  • Authors: Jordi Rodeiro, Beatriz Olaya, Josep Maria Haro, Aina Gabarrell-Pascuet, José Luis Ayuso-Mateos, Lea Francia, Cristina Rodríguez-Prada, Blanca Dolz-del-Castellar, Joan Domènech-Abella
  • Year: 2024
  • Citation: DOI: 10.1016/j.mhpa.2024.100667
2. The association of material deprivation with major depressive disorder and the role of loneliness and social support: A cross-sectional study
  • Authors: Joan Domènech-Abella, Carles Muntaner, Jordi Rodeiro, Aina Gabarrell-Pascuet, Josep Maria Haro, José Luis Ayuso-Mateos, Marta Miret, Beatriz Olaya
  • Year: 2024
  • Citation: DOI: 10.1016/j.jad.2024.09.071
3. Feasibility of an occupational e-mental health intervention for enhancing workplace mental health (EMPOWER RCT): Effectiveness and lessons learned (Preprint)
  • Authors: Carlota de Miquel, Christina M. Van der Feltz-Cornelis, Leona Hakkaart-van Roijen, Dorota Merecz-Kot, Marjo Sinokki, Jordi Rodeiro, Jennifer Sweetman, Kaja Staszewska, Ellen Vorstenbosch, Daniele Porricelli et al.
  • Year: 2024
  • Citation: DOI: 10.2196/preprints.66041
4. Trends of use of drugs with suggested shortages and their alternatives across 52 real-world data sources and 18 countries in Europe and North America
  • Authors: Marta Pineda-Moncusí, Alexandros Rekkas, Álvaro Martínez Pérez, Angela Leis, Carlos Lopez Gomez, Eric Fey, Erwin Bruninx, Filip Maljković, Francisco Sánchez-Sáez, Jordi Rodeiro et al.
  • Year: 2024
  • Citation: DOI: 10.1101/2024.08.28.24312695
5. CloMet: A Novel Open-Source and Modular Software Platform That Connects Established Metabolomics Repositories and Data Analysis Resources
  • Authors: Jordi Rodeiro, Ester Vidaña-Vila, Joan Navarro, Roger Mallol
  • Year: 2023

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Milos Kojic | Computational Modeling | Research Excellence Award

Prof Dr Milos Kojic | Computational Modeling | Research Excellence Award

Professor of Nanomedicine at Houston Methodist Research Institute in United States

Dr. Milos Kojic is a distinguished scientist specializing in finite element methods, numerical inelastic analysis, and biomechanics. His groundbreaking contributions span mechanical engineering and bioengineering, with a focus on developing computational models that address complex biomechanical problems. He earned his Ph.D. in Mechanical Engineering from Rice University and has held prominent positions at leading institutions, including the Methodist Hospital Research Institute and Harvard School of Public Health. Dr. Kojic is also a professor and director at the BIOIRC Research and Development Center, where he continues to innovate in computational mechanics. Throughout his career, he has received numerous prestigious awards and led significant international projects. His work has transformed the way researchers model nonlinear structural analysis and biomechanical systems, positioning him as a leader in the field of computational modeling.

Profile

Education 

Dr. Milos Kojic’s academic journey is marked by prestigious achievements in engineering and mechanics. He earned his Ph.D. in Mechanical Engineering from Rice University, Houston, Texas, where his thesis focused on the “Influence of Fluid Pressure Gradient on Plasticity of Porous Media,” a pioneering work that has had a lasting impact in the field. Prior to that, Dr. Kojic completed his M.S. in Mechanics from the University of Belgrade, Serbia, specializing in natural sciences and mathematics. His foundational education began at the University of Kragujevac, Serbia, where he earned his B.S. in Mechanical Engineering. Dr. Kojic’s education was supported by scholarships and awards, including a Fulbright Foundation grant for his Ph.D. studies. These academic milestones laid the foundation for his contributions to computational mechanics and bioengineering, equipping him with the theoretical knowledge and research skills necessary for his groundbreaking work in finite element and discrete particle methods.

Experience

Dr. Milos Kojic has an extensive career spanning over five decades in academia and research. Currently, he serves as a Scientist Full Member and Professor of Nanomedicine at the Methodist Hospital Research Institute in Houston, Texas, and an Adjunct Professor in the Department of Computer Science at the University of Houston. He is also the Director of the Research and Development Center for Bioengineering ‘BIOIRC’ in Serbia, where he leads pioneering research in biomechanics. Dr. Kojic has held various prominent academic positions, including Visiting Professor at the University of Texas Health Science Center and Senior Research Scientist at Harvard School of Public Health. His work also includes decades of experience at the University of Kragujevac, where he taught courses in mechanics and led research in finite element analysis. Dr. Kojic’s diverse experiences highlight his role as an influential figure in computational modeling and bioengineering research.

Awards and Honors

Dr. Milos Kojic’s career is adorned with numerous prestigious awards and honors that recognize his contributions to computational mechanics, bioengineering, and education. His early academic achievements were acknowledged with a scholarship for his B.S. in Mechanical Engineering and a Fulbright Foundation Scholarship during his Ph.D. studies. Among his many accolades, Dr. Kojic received the Gold Medal from the Serbian Engineering Society in 2001 and the St. Sava Award for Life Achievements in 2020 for his contributions to the University of Kragujevac. His exceptional research in nonlinear finite element analysis has earned him recognition both locally and internationally, including the Plaque St. George from the City of Kragujevac in 2019. These honors, along with numerous research grants and industry awards, reflect his dedication to advancing the fields of engineering and biomechanics while fostering the development of future generations in these disciplines.

Research Focus

Dr. Milos Kojic’s research focuses on advancing computational methods in biomechanics, finite element analysis, and nonlinear structural modeling. His groundbreaking work in finite element methods (FEM) and discrete particle methods (DPM) has transformed numerical simulations in both mechanical and biomedical applications. He has developed novel approaches for analyzing inelastic materials, coupled problems, and biomechanical systems, with a particular interest in elasticity, plasticity, and rigid body mechanics. Dr. Kojic has also contributed significantly to the development of software tools that implement these methods, making it easier for researchers to solve complex engineering and bioengineering problems. His research on multiscale modeling of biological systems, including tissue mechanics and perfusion in cancerous tissues, has broadened the applicability of computational models in medical research. Dr. Kojic’s current focus includes the integration of machine learning with traditional computational mechanics, opening new avenues for predictive modeling in biomechanics and bioengineering.

Publication Top Notes

🧬 An Insight into Perfusion Anisotropy within Solid Murine Lung Cancer Tumors (2024)

🖥️ On the Generality of the Finite Element Modeling Physical Fields in Biological Systems (2024)

🧠 Comparison of Data-Driven and Physics-Informed Neural Networks for Surrogate Modelling (2024)

💊 Modeling Critical Interaction for Metastasis Between Circulating Tumor Cells and Platelets (2023)

❤️ Application of In Silico Trials for Drug Effects on Cardiomyopathy-Diseased Heart Cycle (2023)

🩺 Machine Learning and Physical Based Modeling for Cardiac Hypertrophy (2023)

🧠 Cardiac Hypertrophy Simulations Using Echocardiography-Based Models (2023)

🫁 A Multiscale Multiphysics Finite Element for Lung (2023)

💪 Optimization of Physics-Informed Neural Networks for Huxley’s Muscle Model (2023)

💻 Data-driven and Physics-informed Muscle Model Surrogates for Cardiac Cycle Simulations (2023)