Arturo Benayas Ayuso | Computer Science | Best Researcher Award

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Prof. Arturo Benayas Ayuso | Computer Science | Best Researcher Award

PhD Candidate, Universidad Politécnica de Madrid, Spain

Arturo Benayas Ayuso is a highly skilled Naval Architect with a distinguished career in naval shipbuilding and digital transformation. He currently leads the integration of the “El Cano” platform at NAVANTIA, spearheading Industry 4.0 innovations in ship design, construction, and management. His expertise in integrating PLM systems and IoT into shipbuilding projects has positioned him as a leader in naval digitization. Fluent in multiple languages, Arturo also serves as a lecturer, sharing his knowledge of statistics at Universidad Complutense de Madrid. 🚢💡

Publication Profile

ORCID

Education

Arturo holds a Master’s in Naval Architecture from Universidad Politécnica de Madrid and is currently pursuing a PhD, focusing on IoT applications in ship design, shipbuilding, and management. His academic background, combined with his professional experience, allows him to seamlessly bridge the gap between theory and practice in the maritime industry. 🎓📚

Experience

As the Integration Lead of NAVANTIA’s “El Cano” platform, Arturo manages the digitization and PLM integration of naval shipbuilding processes. His past roles include overseeing the FORAN-PLM integration for Spain’s S80 submarine and collaborating on several high-profile naval projects, including the Royal Navy’s CVF program. His work has consistently focused on improving digital workflows in naval engineering using systems like Windchill and Teamcenter PLM. 🛠️⚙️

Research Focus

Arturo’s research revolves around applying IoT technology to ship design and manufacturing. His work aims to enhance the efficiency of shipbuilding processes by integrating advanced digital tools and IoT into ship management systems. This focus on Industry 4.0 in naval architecture ensures future-ready solutions in naval engineering. 🔍🌐

Awards and Honors

Arturo has contributed significantly to both industry and academia, sharing his insights at conferences like RINA and publishing in prestigious industry magazines. His thought leadership in naval shipbuilding and PLM system integration has earned him recognition within the maritime and technology sectors. 🏅📜

Publications

Integrated Development Environment in Shipbuilding Computer Systems – ICAS 2011, cited in studies related to shipbuilding digitization

Automated/Controlled Storage for an Efficient MBOM Process in Shipbuilding Managing IoT Technology – RINA, 2018, discussed in articles on smart ship management

Data Management for Smart Ship: Reducing Machine Learning Cost in IoS Applications – RINA, 2018, frequently referenced in works on IoT and machine learning integration

Mario Flores | Computational Biology | Next-Generation Science Trailblazer Award

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Assist Prof Dr. Mario Flores | Computational Biology | Next-Generation Science Trailblazer Award

Biomedical, University of Texas at San Antonio, United States

Dr. Mario A. Flores is an Assistant Professor at the University of Texas at San Antonio with a joint appointment in Electrical and Computer Engineering (ECE) and Biomedical Engineering (BME). His research focuses on developing AI models for disease phenotype prediction, biomarker identification, and generating explainable mechanisms of disease progression. Dr. Flores has pioneered several genomics and AI-based tools integrating spatial transcriptomics and Electronic Health Records (EHR) to characterize tumor microenvironments. 💻🔬

Publication Profile

ORCID

 

Education:

🎓 B.S. in Electronics Engineering (Instrumentation) – Metropolitan Autonomous University, 2002. M.S. in Applied Mathematics – University of Texas at San Antonio, 2010. Ph.D. in Electrical Engineering (Computational Biology) – University of Texas at San Antonio, 2015

Experience:

Dr. Flores is an Assistant Professor at the University of Texas at San Antonio since 2020. He has previously held roles as a Postdoctoral Fellow at the National Institutes of Health (NIH) and as a Research Associate at the Greehey Children’s Cancer Research Institute. His expertise spans computational biology, bioinformatics, AI, and deep learning. He has contributed significantly to spatial biology and immuno-oncology, tackling diseases using innovative AI techniques. 🧬🤖

Research Focus:

Dr. Flores’ research delves into AI-driven disease modeling, integrating single-cell RNAseq, EHR, and RNA FISH imaging to study tumor microenvironments. His lab develops tools that predict disease gene dependence and identify dysregulated regulatory elements during disease progression. His ongoing work integrates AI with spatially resolved transcriptomics to study cancer and other complex diseases. 🔍🧠

Awards and Honors:

🏅 NIH Functional Peripheral and Central Vagal Neural Circuits Grant (PI), 2023-2025. Artificial Intelligence/Machine Learning Consortium Hub Specific Pilot Grant (PI), 2023-2025. Keystone Symposia Investigator Travel Award, June 2023

Publications Top Notes:

New tools for spatial biology transcriptomics & proteomics in immuno-oncology – Immuno-Oncology Insights (2023) DOI: 10.18609/ioi.2023.005
Cited by 5 articles.

Looking at the TMEs from the Spatial Transcriptomics Perspective – Advances in Cancer Research and Clinical Imaging (2022)
Cited by 8 articles.

Poster: The Tumor microenvironment of NSCLC – Keystone Symposia (June 2023)
Presented at Keystone Symposia on Single Cell Biology.

Mario Flores | Computational Biology | Next-Generation Science Trailblazer Award

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Assist Prof Dr. Mario Flores | Computational Biology | Next-Generation Science Trailblazer Award

Biomedical, University of Texas at San Antonio, United States

Profile

Google Scholar

Short Bio

Dr. Mario A. Flores is an Assistant Professor at the University of Texas at San Antonio, specializing in artificial intelligence models for disease phenotype predictions, biomarker identification, and explainable mechanisms. His innovative research integrates various AI techniques to enhance our understanding of disease progression, particularly in oncology.

Education

Dr. Flores holds a Bachelor’s degree in Electronics Engineering from the Metropolitan Autonomous University, a Master’s in Applied Mathematics, and a PhD in Electrical Engineering (Computational Biology) from the University of Texas at San Antonio. He completed his postdoctoral fellowship at the National Center for Biotechnology Information (NCBI), NIH.

Experience

Since 2020, Dr. Flores has served as an Assistant Professor with joint appointments in Electrical and Computer Engineering (ECE) and Biomedical Engineering (BME) at UTSA. His prior roles include NIH Postdoctoral Fellow at NCBI and Research Associate at the Greehey Children’s Cancer Research Institute, showcasing his extensive experience in computational biology and bioinformatics.

Research Interests

Dr. Flores’s research focuses on developing AI tools for disease gene dependence prediction, utilizing spatially resolved transcriptomics, single-cell RNA sequencing, and Electronic Health Records (EHRs) to analyze tumor microenvironments. His work aims to bridge gaps in understanding disease mechanisms and improve patient outcomes through precision medicine.

Awards

Dr. Flores has received numerous awards for his research, including funding from the NIH for projects on neural circuits inhibiting pain, and recognition from the AIM-AHEAD Fellowship program, supporting his efforts to address health disparities in minority populations.

Publications Top Notes

Dr. Flores has authored several impactful publications, including:

New tools for spatial biology transcriptomics & proteomics in immuno-oncology, Immuno-Oncology Insights, 2023.

Deep learning tackles single-cell analysis—a survey of deep learning for scRNA-seq analysis, Brief in Bioinformatics, 2022.

Transformer for Gene Expression Modeling (T-GEM): An Interpretable Deep Learning Model for Gene Expression-Based Phenotype Predictions, Cancers, 2022.