Assist. Prof. Dr. Sinan DEMİR | Biological Sciences | Best Researcher Award

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Assist. Prof. Dr. Sinan DEMİR | Biological Sciences | Best Researcher Award

Assist. Prof. Dr. Sinan DEMİR | Biological Sciences – Isparta University of Applied Sciences, Turkey

Dr. Sinan Demir is an Assistant Professor at the Isparta University of Applied Sciences, where he specializes in Soil Science and Plant Nutrition. His academic journey is marked by significant achievements in agricultural technology and remote sensing, focusing on the development of innovative methodologies for monitoring agricultural productivity and land use. Dr. Demir has contributed extensively to the integration of unmanned aerial vehicles (UAVs) and machine learning algorithms to enhance the efficiency of agricultural practices. With a comprehensive background in soil science, plant nutrition, and agricultural engineering, his work continues to impact both the academic community and practical applications in agriculture.

Profile:

Orcid | Scopus | Google Scholar

Education:

Dr. Demir’s academic background includes a Bachelor’s degree in Agricultural Engineering and a Master’s degree in Soil Science and Plant Nutrition from Suleyman Demirel University. His PhD, completed in 2021 at Isparta University of Applied Sciences, was centered around “The Monitoring of Isparta Rose (Rosa damascena Mill.) Gardens using Unmanned Aerial Vehicles (UAVs) and the Development of Yield Prediction Models.” This thesis was guided by Prof. Dr. Levent Başayığit. His formal education has equipped him with a strong foundation in soil science, plant protection, and remote sensing technologies, which he applies in his research and teaching.

Experience:

Dr. Demir has a rich research and teaching portfolio. In his role as Assistant Professor, he has undertaken leadership roles in multiple national and international projects related to agriculture, land use, and environmental monitoring. These include significant contributions to the development of yield prediction models for oil rose farming using UAV images and the application of machine learning algorithms for soil data analysis. He has also been a key researcher in several TUBITAK and EU-funded projects aimed at improving sustainable farming practices and climate change resilience. His teaching contributions span undergraduate and postgraduate courses, with a focus on remote sensing, digital agriculture, and UAV-based crop monitoring.

Research Interests:

Dr. Demir’s research interests lie at the intersection of agricultural technology and environmental science. He focuses on the integration of remote sensing technologies, particularly UAVs, in precision agriculture. His research aims to improve the efficiency of crop monitoring, yield prediction, and land use management. Additionally, he explores the use of hyperspectral data and machine learning techniques to address challenges in soil quality, vegetation health, and climate impact assessments. He is particularly interested in the application of these technologies in regions with semi-arid climates and the development of models to optimize agricultural practices.

Awards:

Dr. Demir’s work has been recognized both in academia and in practical applications. He was awarded several research grants, including support for projects investigating the impact of UAV technology on organic farming practices and the application of machine learning in soil science. His contributions to agricultural research were acknowledged in multiple national and international conferences, where he has presented groundbreaking work on topics such as digital mapping of soil erosion and evaluating land use changes with satellite imagery.

Publications:

Dr. Demir has authored several influential publications in peer-reviewed journals. Notable among them are:

  1. “Determination of suitable agricultural areas and current land use in Isparta Province, Türkiye, through a linear combination technique and geographic information systems” (2024) – Environment, Development and Sustainability 🌱
  2. “Assessment of pre- and post-fire erosion using the RUSLE equation in a watershed affected by the forest fire on Google Earth Engine: the study of Manavgat River Basin” (2024) – Natural Hazards 🔥
  3. “Yield prediction models of organic oil rose farming with agricultural unmanned aerial vehicles (UAVs) images and machine learning algorithms” (2024) – Remote Sensing Applications: Society and Environment 🚁
  4. “Digital Mapping Burn Severity in Agricultural and Forestry Land over a Half-Decade Using Sentinel Satellite Images on the Google Earth Engine Platform” (2024) – Trees, Forests and People 🌳
  5. “Determining burned areas using different threshold values of NDVI with Sentinel-2 satellite images on GEE platform: A case study of Muğla Province” (2023) – International Journal of Sustainable Engineering and Technology 🌍

Conclusion:

Dr. Sinan Demir’s academic and professional trajectory is marked by a dedication to advancing agricultural sciences through the use of cutting-edge technologies such as UAVs and machine learning. His research continues to drive improvements in the management of agricultural systems, particularly in sustainable farming practices and land use optimization. As an educator and researcher, Dr. Demir is committed to sharing his knowledge and contributing to the global discourse on the intersection of technology and agriculture. His work not only enriches academic literature but also offers practical solutions to real-world challenges in the agricultural sector.

Shaghayegh Mirhosseini | Bio Engineering | Best Researcher Award

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Ms. Shaghayegh Mirhosseini | Bio Engineering | Best Researcher Award 

Ph.D. student at University of Virginia, United States

Shaghayegh Mirhosseini is an emerging researcher specializing in bioelectronics, cancer diagnostics, and microfluidics. She has extensive experience in the interdisciplinary field of bio-MEMS (microelectromechanical systems) and has made significant contributions to the study of cancer cells in microfluidic environments. With ongoing Ph.D. research in two prestigious universities, Mirhosseini’s work bridges the gap between biological science and electrical engineering, creating innovative solutions for cancer detection and treatment through advanced microfluidic technologies.

Profile

GOOGLE SCHOLAR

Education

Shaghayegh is currently pursuing two Ph.D. degrees, one from the University of Virginia, where her focus is on cancer cells in microfluidic devices under the supervision of Prof. Nathan Swami, and another from the University of Tehran, where her research centers around separating Circulating Tumor Cells (CTCs) using deterministic lateral displacement (DLD) microfluidic systems. She holds a Master’s degree in Electrical Engineering with a focus on bioelectronics from the University of Tehran, where she worked on the simulation and fabrication of Erbium-doped waveguide amplifiers. Shaghayegh’s academic journey began with a Bachelor’s degree in Electrical Engineering from the University of Kashan, where she designed digital password locks using AVR microcontrollers.

Research Experience

Her diverse research experience spans multiple countries and institutions. At the University of Tehran, she was actively involved in the MEMS & NEMS Laboratory and the Urology Research Center. She further broadened her research scope as a visiting researcher at the University of Virginia and Mälardalen University in Sweden. Her work on bioelectronics, microfluidics, and cancer research has led to numerous publications in prestigious journals. Notably, her contributions to the separation and analysis of circulating tumor cells (CTCs) are innovative, offering potential for groundbreaking cancer diagnostics.

Research Interests

Shaghayegh’s research interests lie at the intersection of biology and electronics. She is particularly focused on cancer research, microfabrication, microfluidic device design, and MEMS technologies. Her expertise in microfluidics and bio-MEMS allows her to explore new diagnostic technologies, especially for cancer detection. She is also interested in machine learning and image processing, which she integrates into her research to develop more efficient and automated cancer cell detection systems. Additionally, Shaghayegh is passionate about drug delivery systems, colorimetric analysis, and the synthesis of gold nanoparticles, which play vital roles in her research projects.

Awards and Recognition

Although Shaghayegh Mirhosseini is still completing her doctoral studies, her innovative research contributions have already garnered significant recognition in the academic community. Her international collaborations and published works have earned her respect from her peers, leading to opportunities for collaboration with top researchers in the field of bioelectronics and cancer diagnostics. While specific awards are yet to be disclosed, her research publications and contributions to cancer diagnostics are paving the way for future accolades.

Publications

  1. Signal-Based Methods in Dielectrophoresis for Cell and Particle Separation
    Published in 2022, cited by multiple articles. Read the full article.
  2. Microstructured Droplet-Based Porous Capacitive Pressure Sensor
    Published in 2021, cited by multiple articles. Read the full article.
  3. Fabrication of an erbium–ytterbium-doped waveguide amplifier at communication wavelengths for integrated optics applications
    Published in 2020, cited by multiple articles. Read the full article.
  4. A digital image colorimetry system based on smart devices for enzyme-linked immunosorbent assays
    Published in 2020, cited by multiple articles. Read the full article.
  5. Effective boundary correction for deterministic lateral displacement microchannels to improve cell separation
    Published in 2023, cited by multiple articles. Read the full article.
  6. Neural network-enabled multiparametric impedance signal templating for high throughput single-cell deformability cytometry
    Published in 2023, cited by multiple articles. Read the full article.

Conclusion

Shaghayegh Mirhosseini presents a strong candidate for the Best Researcher Award due to her significant contributions in bioelectronics and cancer research. Her interdisciplinary expertise, combined with international research exposure, strong publication record, and technical mastery, makes her a highly deserving researcher. With ongoing improvements, including the completion of her Ph.D. studies and a stronger focus in a specialized niche, her potential to make transformative contributions to science is immense.

 

Álvaro Torres-Martos | Bioinformatics | Best Researcher Award

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Mr . Álvaro Torres-Martos | Bioinformatics | Best Researcher Award 

PhD student , University of Granada , Spain

Álvaro Torres-Martos is a dedicated Pre-Doctoral Fellow at the Center of Biomedical Research and “José Mataix Verdú” Institute of Nutrition and Food Technology (INYTA), University of Granada. His research bridges bioinformatics, biostatistics, and precision medicine, focusing on the molecular and genetic underpinnings of metabolic disorders. Álvaro combines his expertise in multi-omics and artificial intelligence to advance our understanding of obesity, insulin resistance, and non-communicable diseases.

Profile

ORCiD

Strengths for the Award

  1. Cutting-Edge Research Experience: Álvaro Torres-Martos has been involved in high-impact research projects such as the ACTIBATE project and EXOMAIR, focusing on novel therapeutic targets and precision medicine. His work on molecular translators and the exposome demonstrates a commitment to advancing the understanding of complex biological systems and diseases.
  2. Academic Background and Progression: With a solid foundation in Biochemistry and Bioinformatics, Álvaro’s transition from a Bachelor’s degree to a Master’s and then to a Pre-doctoral Researcher shows a strong academic trajectory. His current role as a faculty member at the University of Granada further highlights his growing expertise in the field.
  3. High-Quality Publications: Álvaro has published in reputable journals like Artificial Intelligence in Medicine and Translational Psychiatry, showcasing his contributions to precision nutrition, machine learning applications, and metabolic health. His work is well-cited and reflects a significant impact on his research area.
  4. Innovative Tools and Recognition: His involvement in developing the ObMetrics Shiny app and winning the III Bioinformatics Datathon indicates his ability to translate research into practical tools. These achievements underscore his innovation and practical application of his research.
  5. Broad Skill Set: Álvaro has completed various courses and certifications, including advanced data science skills and programming in R and Python. This diverse skill set supports his ability to conduct and present high-quality research.

Areas for Improvement 

  1. Broader Research Impact: While Álvaro’s research is highly specialized, expanding the scope to interdisciplinary areas or applied research in clinical settings could enhance the broader impact of his work.
  2. Increased Visibility: Although he has participated in numerous congresses, further efforts to increase the visibility of his research through collaborations, media outreach, or higher-profile conferences could amplify his contributions.
  3. Grant Acquisition: Securing larger research grants or funding from diverse sources could support more ambitious projects and collaborations, further strengthening his research portfolio.

    Education 

    Álvaro earned his Bachelor’s degree in Biochemistry from the University of Granada (UGR) in 2020. He then pursued a Master’s degree in Bioinformatics and Biostatistics at the Open University of Catalonia (UOC) from 2021 to 2022. Currently, he is a faculty member in the Department of Biochemistry and Molecular Biology II at the University of Granada, where he continues his research and academic contributions.

    Experience 

    • 2022-2023: Bioinformatic Researcher at the ACTIBATE project, University of Granada. This role focused on molecular translators of exercise and brown adipose tissue activation, searching for new therapeutic targets in intercellular communication.
    • 2023-2026: Pre-doctoral Researcher for EXOMAIR, University of Granada. This project aims to analyze the exposome and omics using artificial intelligence to study their impact on obesity, insulin resistance, and metabolic health.
    • 2024: Academic Visitor at the University of Oxford, focusing on dietary and behavioral phenotypes and non-communicable disease risk through a multi-omics approach.

    Research Interests 

    Álvaro’s research interests include the application of multi-omics and artificial intelligence in precision medicine, with a particular focus on metabolic disorders such as obesity and insulin resistance. He is also interested in the interaction between genetic risk factors and environmental influences on health outcomes.

    Awards 

    • Winner of the III Bioinformatics Datathon organized by the Bioinformatics Conference, University of Granada.
    • Developed the ObMetrics Shiny app, enhancing metabolic syndrome analysis for pediatric populations.

    Publications 

Gustavo Carnivali | Bioinformatic | Best Researcher Award

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Dr. Gustavo Carnivali | Bioinformatic | Best Researcher Award

Researcher at UFMG, Brazil

Gustavo Simões Carnivali is a dedicated researcher specializing in bioinformatics, computer graphics, and computational mathematics. His work focuses on gene networks, drug repurposing for COVID-19, and data visualization techniques. With a background in computer science and multiple master’s degrees, Gustavo is currently pursuing a Ph.D. in Bioinformatics while actively contributing to research at EMBRAPA and other institutions. He has a strong publication record and has presented his work at prestigious conferences. Gustavo’s interdisciplinary expertise and innovative research contributions highlight his commitment to advancing computational sciences and bioinformatics.

Professional Profiles

Education

Gustavo Simões Carnivali has pursued a diverse and rigorous academic path, reflecting his commitment to multidisciplinary studies. He is currently undertaking a Ph.D. in Education at Integraliza in Brazil under the guidance of Luiz Carlos Santos, alongside his ongoing Ph.D. studies in Bioinformatics at the Federal University of Minas Gerais (UFMG), supervised by Tiago Antonio de Oliveira Mendes and supported by a grant from Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG). Prior to his doctoral pursuits, Gustavo earned a Master’s degree in Computer Science at the Federal University of Juiz de Fora (UFJF), where he worked under Marcelo Bernardes Vieira’s mentorship. He also holds a Master’s degree in Education Sciences from Universidad Martin Lutero in the United States, completed in 2022 with guidance from Samuel de Oliveira Nicolau. Additionally, Gustavo achieved a Master’s degree in Computational Modeling at the National Scientific Computing Laboratory (LNCC) in Brazil, supported by a grant from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and supervised by Artur Ziviani. His academic journey exemplifies his dedication to advancing knowledge across computer science, education, and bioinformatics fields.

Professional Experience

Gustavo Simões Carnivali has accumulated valuable professional experience across prestigious institutions and research environments. Currently, he serves as a researcher at the Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), contributing to cutting-edge projects in his field. Previously, he held positions at the Universidade Federal de Minas Gerais (UFMG) and Universidade Federal de Juiz de Fora (UFJF) as a grantee, where he engaged in various research and academic activities. His roles have encompassed a range of responsibilities, from conducting research in bioinformatics and computer science to collaborating on multidisciplinary projects. Gustavo’s professional journey underscores his expertise in scientific research and his commitment to advancing knowledge in his specialized areas.

Research Interest

Gustavo Simões Carnivali’s research interests span several key areas within bioinformatics, computer graphics, and computational mathematics. He focuses on leveraging bioinformatics tools to study genetic interactions related to diseases like Covid-19. His work extends to exploring machine learning methods for disease differentiation and developing computational models for efficient community detection in complex networks. Additionally, he engages in research aimed at understanding genetic variations and their implications in human health, showcasing a multidisciplinary approach that integrates computer science with biological sciences to address contemporary challenges in healthcare and beyond.

Award and Honors

Gustavo Simões Carnivali has garnered significant recognition for his contributions in computational sciences and bioinformatics. He received an Honorable Mention from the Brazilian Computer Society (SBC) in 2018 for his work on efficient community detection in large-scale complex networks. Additionally, he achieved First Place at Startup Weekend JF in 2015 for his project “New Dream.” These awards underscore his expertise and innovative approach in the fields of computer science, bioinformatics, and computational mathematics.

Research Skills

Gustavo Simões Carnivali is highly skilled in the fields of computer science, bioinformatics, and computational mathematics. His research expertise spans bioinformatics, focusing on gene networks and drug repurposing, as well as computer graphics for data visualization and computational mathematics for algorithmic development. With a background in machine learning, he applies these techniques to analyze complex datasets and model intricate networks. Gustavo is also proficient in scientific writing, having authored numerous peer-reviewed articles and presented his research at various international conferences. His interdisciplinary approach and innovative contributions underscore his commitment to advancing computational sciences and bioinformatics.

Publications

  1. Thermal Management of the Li‐Ion Batteries to Improve the Performance of the Electric Vehicles Applications
    • Authors: Vrije Universiteit Brussel
    • Year: 2022
  2. Understanding Voltage Behavior of Lithium-Ion Batteries in Electric Vehicles Applications
    • Authors: Not specified
    • Year: 2022
  3. Multi-objective particle swarm optimization and training of datasheet-based load dependent lithium-ion voltage models
    • Authors: Not specified
    • Year: 2021
  4. Reliability Evaluation of Lithium-Ion Batteries for E-Mobility Applications from Practical and Technical Perspectives: A Case Study
    • Authors: Not specified
    • Year: 2021
  5. Smart Grid in China, EU, and the US: State of Implementation
    • Authors: Not specified
    • Year: 2021
  6. Optimal Allocation and Planning of Distributed Power Generation Resources in a Smart Distribution Network Using the Manta Ray Foraging Optimization Algorithm
    • Authors: Not specified
    • Year: 2021
  7. Novel thermal management methods to improve the performance of the Li-ion batteries in high discharge current applications
    • Authors: Not specified
    • Year: 2021
  8. PCM assisted heat pipe cooling system for the thermal management of an LTO cell for high-current profiles
    • Authors: Not specified
    • Year: 2021
  9. Battery Modelling and Energy Management of the Electric Vehicles and Renewable Energy Resources
    • Authors: Vrije Universiteit Brussel
    • Year: 2021
  10. Aluminum Heat Sink Assisted Air-Cooling Thermal Management System for High Current Applications in Electric Vehicles
    • Authors: Vrije Universiteit Brussel
    • Year: 2020