Sergio Armando Barbosa | Engineering | Best Researcher Award

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Dr. Sergio Armando Barbosa | Engineering | Best Researcher Award

Dr. Sergio Armando Barbosa, University of Virginia, United States

Sergio Armando Barbosa Casas is a dedicated hydrologist and civil engineer with a strong background in groundwater modeling, hydrodynamics, and environmental sustainability. He holds a Ph.D. in Civil Engineering from Brigham Young University and currently serves as a Postdoctoral Research Associate at the University of Virginia. His research focuses on assessing flooding impacts, coastal sustainability, and groundwater resource management using Earth observations and advanced modeling techniques. With over a decade of experience, he has worked with institutions such as IDEAM, CAR, and Aquaveo, contributing to hydrological forecasting, river basin assessments, and flood risk analysis. His work has been published in high-impact journals, and he has presented at global conferences. Fluent in English and Spanish, he actively collaborates with interdisciplinary teams to address climate resilience and water resource challenges. His contributions to academia and research continue to advance sustainable solutions for environmental and hydrological challenges.

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Suitability for the “Research for Best Researcher Award” – Sergio Armando Barbosa Casas

Dr. Sergio Armando Barbosa Casas is an exceptionally qualified candidate for the Research for Best Researcher Award, given his extensive contributions to hydrology, groundwater modeling, and urban flood risk assessment. His research has significantly advanced the understanding of groundwater resource assessment, particularly in West Africa, through Earth observations and modeling. His Ph.D. dissertation at Brigham Young University was a groundbreaking study on groundwater resource assessment, a critical topic for sustainable water management.

Currently serving as a Postdoctoral Research Associate at the University of Virginia, Dr. Barbosa is involved in interdisciplinary research on coastal and urban flooding vulnerabilities, sustainability, and salt intrusion in aquifers. His collaboration with government agencies and stakeholders to develop informed decision-making processes for groundwater management highlights his real-world impact. His prior experience as a hydrologist at IDEAM (Colombian Institute of Hydrology, Meteorology, and Environmental Studies) and a design engineer at CAR (Regional Autonomous Corporation) further demonstrate his expertise in hydrological modeling, flood risk assessment, and environmental sustainability.

🎓 Education

Sergio A. Barbosa Casas earned his Ph.D. in Civil Engineering from Brigham Young University in 2023, where he conducted groundbreaking research on groundwater resource assessment in West Africa using Earth observations and numerical modeling. His dissertation explored the impact of climate change and human activities on groundwater storage and recharge, providing valuable insights into water management strategies for arid regions. Prior to this, he obtained an M.S. in Civil Engineering from the National University of Colombia in 2014, focusing on water resource management and hydrological modeling. His academic journey began with a B.S. in Agricultural Engineering from the same institution in 2009, where he developed expertise in hydraulic systems and watershed management. Throughout his studies, he actively engaged in research projects, collaborated with international teams, and contributed to policy recommendations. His diverse educational background has equipped him with a solid foundation in hydrology, climate resilience, and engineering solutions.

💼 Professional Experience 

Sergio A. Barbosa Casas has amassed extensive experience in hydrology, groundwater modeling, and environmental engineering. Currently, he is a Postdoctoral Research Associate at the University of Virginia, where he leads research on flooding impacts, coastal resilience, and sustainability. Previously, he was a Research Assistant at Brigham Young University, where he developed groundwater models for major aquifers in West Africa, utilizing remote sensing and field data. His industry experience includes working as an Engineering Intern at Aquaveo, where he created 3D groundwater simulations. Additionally, he served as a Hydrologist at IDEAM in Colombia, leading hydrological forecasting and flood risk assessments. As a Design Engineer at CAR, he developed dynamic models to evaluate water quality in the Bogotá River. His expertise spans across academia, government agencies, and private sectors, making him a well-rounded professional in water resource engineering, flood modeling, and climate adaptation strategies.

🏅 Awards and Recognition

Sergio A. Barbosa Casas has received numerous awards and grants for his contributions to hydrology and environmental engineering. He was awarded the Climate Fellows Postdoctoral Program Fellowship at the University of Virginia in 2024. During his Ph.D., he secured the Civil & Construction Engineering Scholarship Society Award (2019-2022). His research excellence earned him the Bill Stolte Best Student Paper Award at the Canadian Water Resources Association National Conference in 2022. Additionally, he has contributed to prestigious projects funded by the National Science Foundation (NSF), with grants exceeding $5 million. His involvement in the NASA/USAID Research Grant on sustainable groundwater management in West Africa further highlights his global impact. Recognized for his interdisciplinary approach and innovative methodologies, his work continues to shape water resource sustainability and climate resilience. His expertise is sought after in academic and professional circles worldwide.

🌍 Research Skills On Engineering

Sergio A. Barbosa Casas is an expert in hydrological modeling, groundwater resource management, and climate resilience. His research integrates Earth observations, GIS, and remote sensing with hydrodynamic and groundwater modeling tools such as MODFLOW, HEC-RAS, and TUFLOW. He specializes in analyzing flood risks, coastal vulnerabilities, and sustainable water management strategies. His technical skills include numerical simulations, Python programming, and machine learning applications in hydrology. He has worked extensively with stakeholders, translating complex hydrological data into actionable policies. His work on urban flooding, saltwater intrusion, and groundwater sustainability has been published in high-impact journals and presented at global conferences. With a keen interest in data-driven solutions for climate adaptation, he collaborates across disciplines to develop innovative approaches for managing water resources in changing environments. His research continues to influence sustainable development, providing practical solutions for water security challenges.

Publication Top Notes

  • Deep learning-based downscaling of global digital elevation models for enhanced urban flood modeling

    • Author(s): Zanko Zandsalimi, Sergio A. Barbosa, Negin Alemazkoor, Jonathan L. Goodall, Majid Shafiee-Jood
    • Citation: Journal of Hydrology, 2025-06
    • DOI: 10.1016/j.jhydrol.2025.132687
    • Year: 2025

  • Exploring infiltration effects on coastal urban flooding: Insights from nuisance to extreme events using 2D/1D hydrodynamic modeling and crowdsourced flood reports

    • Author(s): Sergio A. Barbosa, Yidi Wang, Jonathan L. Goodall
    • Citation: Science of The Total Environment, 2025-03
    • DOI: 10.1016/j.scitotenv.2025.178908
    • Year: 2025

  • Exploiting Earth Observations to Enable Groundwater Modeling in the Data-Sparse Region of Goulbi Maradi, Niger

    • Author(s): Sergio A. Barbosa, Norman L. Jones, Gustavious P. Williams, Bako Mamane, Jamila Begou, E. James Nelson, Daniel P. Ames
    • Citation: Remote Sensing, 2023-11-01
    • DOI: 10.3390/rs15215199
    • Year: 2023

  • Exploiting Earth Observations to Enable Groundwater Modeling in the Data-Sparse Region of Goulbi Maradi, Niger (Preprint)

    • Author(s): Sergio A. Barbosa, Norman L. Jones, Gustavious P. Williams, Bako Mamane, Jamila Begou, E. James Nelson, Daniel P. Ames
    • Citation: Preprint, 2023-08-30
    • DOI: 10.20944/preprints202308.2021.v1
    • Year: 2023

  • Correction: Barbosa et al. Evaluating Groundwater Storage Change and Recharge Using GRACE Data: A Case Study of Aquifers in Niger, West Africa. Remote Sens. 2022, 14, 1532

    • Author(s): Sergio A. Barbosa, Sarva T. Pulla, Gustavious P. Williams, Norman L. Jones, Bako Mamane, Jorge L. Sanchez
    • Citation: Remote Sensing, 2023-03-03
    • DOI: 10.3390/rs15051435
    • Year: 2023

Karthik K | Engineering | Best Researcher Award

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Dr. Karthik K | Engineering | Best Researcher Award

Dr. Karthik K, Vellore Institute of Technology, Vellore, India

Karthik K is an accomplished academician and researcher specializing in computer vision, deep learning, and medical imaging. With over a decade of experience in teaching and research, he has contributed significantly to the field of artificial intelligence in healthcare applications. Currently serving as an Assistant Professor Sr Grade I at Vellore Institute of Technology, Vellore, he has previously worked at St. Joseph Engineering College and NITK, Surathkal. His research is backed by strong academic credentials, numerous publications, and active collaborations with esteemed institutions like NITK, NITPy, and VIT AP. Karthik has received the VIT Seed Grant for AI-driven cricket commentary generation and has applied for prestigious research grants. His contributions to automated medical scan quality enhancement and content-based medical image retrieval have been widely recognized. An active IEEE and IAENG member, he continues to drive innovation in AI and deep learning for intelligent healthcare applications.

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Evaluation of Dr. Karthik K for the Research for Best Researcher Award

Dr. Karthik K, currently an Assistant Professor Sr. Grade I at the Vellore Institute of Technology (VIT), has demonstrated strong research contributions in the fields of computer vision, deep learning, and medical imaging. His research spans content-based medical image retrieval, automated radiography report retrieval, and deep learning-based medical scan quality enhancement, which have direct applications in intelligent healthcare systems. With six journal publications in SCI and Scopus-indexed journals, along with 145 citations, his academic impact is notable.

In addition to his research, Dr. Karthik has published book chapters, submitted a patent, and collaborated with reputed institutions such as NITK, NITPy, and VIT AP. His contributions to AI-driven healthcare applications, particularly in medical image classification and enhancement, showcase his innovative approach to solving real-world medical challenges. Furthermore, his ongoing VIT Seed Grant project on AI-generated cricket commentary and a DST-SURE research grant under review indicate his continued commitment to advancing AI applications across multiple domains.

🎓 Education 

Karthik K has built a strong academic foundation in the fields of computer science and engineering. He pursued his Bachelor’s and Master’s degrees with a focus on artificial intelligence, deep learning, and medical imaging. His research interests led him to work as a Research Fellow at NITK Surathkal, where he contributed to the DST-ECR-funded project on deep learning frameworks for intelligent healthcare applications. During his tenure, he gained extensive expertise in content-based medical image retrieval and automated medical scan enhancements. His academic journey has been marked by continuous learning and contributions to research, with publications in renowned journals and conferences. Karthik’s passion for AI-driven innovations is evident in his scholarly work, patents, and ongoing research projects. His educational background has laid the foundation for his teaching and research career, equipping him with the knowledge and skills to drive advancements in AI, deep learning, and medical imaging applications.

💼 Professional Experience 

Karthik K brings over 10 years of experience in academia and research. He is currently an Assistant Professor Sr Grade I at Vellore Institute of Technology, Vellore, where he specializes in AI, computer vision, and medical imaging. Prior to this, he was an Assistant Professor at St. Joseph Engineering College, Vamanjoor, Mangaluru (2020–2023) and an Assistant Lecturer at NITK, Surathkal (2015–2017). His professional journey includes a research fellowship at NITK Surathkal, where he worked on a DST-ECR-funded project developing deep learning frameworks for intelligent healthcare. Karthik has contributed significantly to AI-driven innovations, collaborating with institutions like NITK, NITPy, and VIT AP. His expertise extends to consultancy projects, editorial appointments, and patents. He has published extensively in SCI and Scopus-indexed journals and remains actively involved in advancing deep learning applications for medical imaging, making significant contributions to academia and industry collaborations.

🏅 Awards and Recognition

Karthik K has been recognized for his contributions to artificial intelligence and medical imaging research. He received the VIT Seed Grant (2023–2025) for his innovative project on AI-driven cricket commentary generation. Additionally, he has applied for the DST-SURE research grant, currently under review. His work in content-based medical image retrieval and deep neural networks for healthcare applications has been acknowledged in multiple international journals and conferences. Karthik has published several book chapters with ISBN numbers, showcasing his expertise in AI and deep learning. He actively collaborates with esteemed institutions and has been invited for editorial appointments in reputed journals. His research contributions have earned him membership in professional organizations such as IEEE and IAENG. With over 145 citations in SCI and Scopus-indexed publications, his work continues to impact the field of intelligent healthcare applications. His commitment to research excellence makes him a strong contender for prestigious awards.

🌍 Research Skills On Engineering

Karthik K possesses extensive research skills in computer vision, deep learning, and medical imaging. His expertise includes developing AI-driven frameworks for intelligent healthcare applications, enhancing medical scan quality, and implementing deep neural networks for automated medical image retrieval. He has successfully led research projects, including a DST-ECR-funded initiative at NITK Surathkal and ongoing consultancy projects. His ability to integrate AI with real-world healthcare challenges has resulted in significant innovations such as ViewNet for scan orientation and automated radiography report retrieval. Karthik’s research has been published in SCI and Scopus-indexed journals, contributing to the broader scientific community. He is skilled in grant writing, patent filing, and interdisciplinary collaborations, with active partnerships with NITK, NITPy, and VIT AP. His research acumen, combined with hands-on experience in deep learning and AI applications, positions him as a leader in advancing intelligent healthcare solutions through cutting-edge technology.

 📖 Publication Top Notes

  • Title: A deep neural network model for content-based medical image retrieval with multi-view classification
    Authors: K Karthik, SS Kamath
    Citation: 60
    Year: 2021
  • Title: A hybrid feature modeling approach for content-based medical image retrieval
    Authors: K Karthik, SS Kamath
    Citation: 16
    Year: 2018
  • Title: COVIDDX: AI-based Clinical Decision Support System for Learning COVID-19 Disease Representations from Multimodal Patient Data
    Authors: V Mayya, K Karthik, KS Sowmya, K Karadka, J Jeganathan
    Citation: 13
    Year: 2021
  • Title: Analysis and prediction of fantasy cricket contest winners using machine learning techniques
    Authors: K Karthik, GS Krishnan, S Shetty, SS Bankapur, RP Kolkar, TS Ashwin, …
    Citation: 13
    Year: 2021
  • Title: MSDNet: A deep neural ensemble model for abnormality detection and classification of plain radiographs
    Authors: K Karthik, S Sowmya Kamath
    Citation: 12
    Year: 2023
  • Title: Deep neural models for automated multi-task diagnostic scan management—quality enhancement, view classification and report generation
    Authors: K Karthik, S Kamath
    Citation: 12
    Year: 2021
  • Title: Automatic quality enhancement of medical diagnostic scans with deep neural image super-resolution models
    Authors: K Karthik, SS Kamath, SU Kamath
    Citation: 6
    Year: 2020
  • Title: An automated robotic arm: a machine learning approach
    Authors: NSK Rao, NJ Avinash, HR Moorthy, K Karthik, S Rao, S Santosh
    Citation: 5
    Year: 2021
  • Title: Automated view orientation classification for x-ray images using deep neural networks
    Authors: K Karthik, S Kamath
    Citation: 3
    Year: 2021
  • Title: GAN-Based Encoder-Decoder Model for Multi-Label Diagnostic Scan Classification and Automated Radiology Report Generation
    Authors: R Kumar, K Karthik, SS Kamath
    Citation: 3