Prof. Dr.  Canan G. Nebigil-DĂŠsaubry  – Cardiovascular – Best Researcher Award

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Prof. Dr.  Canan G. Nebigil-DÊsaubry  - Cardiovascular - Best Researcher Award

INSERM, UMR1260 University of Strasbourg - France

Author Profile 

ORCID 

Early academic pursuits 🎓

Canan G. Nebigil-DĂŠsaubry embarked on her academic journey with a pharm.d. from ankara university, where her interest in pharmacology and molecular biology began to take shape. she further pursued a ph.d. at the university of tennessee, delving deeper into molecular signaling pathways. her academic excellence and passion for biomedical research led her to postdoctoral training under nobel laureate professor robert lefkowitz at duke university, where she gained invaluable insights into g protein-coupled receptors (gpcrs), setting the stage for her future research.

Professional endeavors 💼

After completing her postdoctoral training, dr. nebigil-dĂŠsaubry's career flourished as a senior scientist at the national institutes of health (nih) and later at the institute of genetics and molecular and cellular biology (igbmc). her exemplary work earned her an atip/avenir award, enabling her to join the european school of biotechnology (esbs) at the university of strasbourg. currently, she serves as the director of research at cnrs, inserm umr1260 regenerative nanomedicine, where she continues to make significant contributions to cardiovascular and metabolic research.

Contributions and research focus 🔬

Dr. Nebigil-dĂŠsaubry's research primarily explores the role of gpcrs, particularly serotonin and prokineticin receptors, in cardiovascular development and disease. she established the critical Cardiovascular roles of these receptors in heart development and pathology, notably identifying the serotonin 5-ht2b receptor's pivotal role in embryonic cardiac development. her team was also the first to investigate prokineticin signaling in cardiac and metabolic disorders, revealing its potential as a therapeutic target for heart disease, obesity, and diabetes. her groundbreaking discovery of the first non-peptidic pkr1 agonist, is20, marked a significant milestone in cardioprotection and cardio-oncology.

Accolades and recognition 🏆

Dr. Nebigil-dĂŠsaubry's innovative research has earned her numerous accolades, including the prestigious atip/avenir award. her contributions to cardiovascular and metabolic research are Cardiovascular recognized globally, with multiple drug discovery patents to her name. the inclusion of is20 in the international union of basic and clinical pharmacology (iuphar) guide to pharmacology as a selective pkr1 agonist further underscores the significance of her work in the scientific community.

Impact and influence 💡

The impact of dr. nebigil-dĂŠsaubry's research extends beyond academic circles, influencing clinical practices and therapeutic strategies in cardiology and oncology. her identification of the Cardiovascular prokineticin/pkr1 signaling pathway as a regulator of epicardial adipose tissue development has provided new avenues for managing heart failure with preserved ejection fraction (hfpef) and cardiometabolic disorders. her work in cardio-oncology aims to address the pressing need for early biomarkers and cardioprotective therapeutics in chemotherapy-induced heart failure.

Legacy and future contributions 🕊️

Dr. Nebigil-dĂŠsaubry's legacy is one of innovation and excellence in cardiovascular research. her pioneering work in cardiac regeneration and metabolic disease management has laid the foundation for future advancements in precision medicine. with her recent development of a 3d cardiac organoid-tumor system, she is poised to accelerate drug discovery and biomarker identification, ultimately improving patient outcomes and shaping the future of regenerative medicine and cardio-oncology.

Notable Publications 

  • Title: Flavaglines: Their Discovery from Plants Used in Traditional Chinese Medicine, Synthesis, and Drug Development Against Cancer and Immune Disorders
    Author(s): Dong Wang, Mustafa Ali Tezeren, Hussein Abou Hamdan, Peng Yu, Canan Nebigil-DĂŠsaubry, Laurent DĂŠsaubry
    Journal: Current Chinese Chemistry, 2022

  • Title: Prohibitin ligands: a growing armamentarium to tackle cancers, osteoporosis, inflammatory, cardiac and neurological diseases
    Author(s): Dong Wang, Redouane Tabti, Sabria Elderwish, Hussein Abou-Hamdan, Amel Djehal, Peng Yu, Hajime Yurugi, Krishnaraj Rajalingam, Canan G. Nebigil, Laurent DĂŠsaubry
    Journal: Cellular and Molecular Life Sciences, 2020

  • Title: SFPH proteins as therapeutic targets for a myriad of diseases
    Author(s): Dong Wang, Redouane Tabti, Sabria Elderwish, Amel Djehal, Nora Chouha, Franck Pinot, Peng Yu, Canan G. Nebigil, Laurent Desaubry
    Journal: Bioorganic and Medicinal Chemistry Letters, 2020

  • Title: Flavaglines as natural products targeting eIF4A and prohibitins: From traditional Chinese medicine to antiviral activity against coronaviruses
    Author(s): Canan G. Nebigil, Christiane Moog, StĂŠphan Vagner, Nadia Benkirane-Jessel, Duncan Smith, Laurent DĂŠsaubry
    Journal: European Journal of Medicinal Chemistry, 2020

  • Title: Prokineticin signaling in heart-brain developmental axis: Therapeutic options for heart and brain injuries
    Author(s): Laurent DĂŠsaubry, Anumantha Kanthasamy, Canan G. Nebigil
    Journal: Pharmacological Research, 2020

Dr. Michael Bekele Maru  – Civil Engineering – Best Paper Award

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Dr. Michael Bekele Maru  - Civil Engineering - Best Paper Award

Sungkyunkwan University, Suwon Campus,2nd Engineering Complex,26220 - South Korea 

Author Profile 

GOOGLE SCHOLAR 

🎓 Early academic pursuits

Michael Bekele maru embarked on his academic journey at addis ababa university in ethiopia, where he earned a b.sc in civil, architectural, and environmental system engineering. his undergraduate thesis focused on the structural design of a multi-story building, laying the foundation for his future endeavors in structural engineering. his quest for advanced knowledge led him to sungkyunkwan university in south korea, where he pursued a combined m.sc and ph.d. in civil, architectural, and environmental system engineering. under the guidance of professor seunghee park, michael's dissertation on enhancing lidar data processing for building facade segmentation and 3d reconstruction showcased his innovative approach to integrating technology with civil engineering.

💼 Professional endeavors

Michael's professional journey began as a site engineer with addis gedle general contractor, where he honed his skills in quality supervision, project monitoring, and construction planning. his role as a project engineer at nasew construction plc further expanded his expertise in project synchronization, scheduling, and quality assurance. transitioning to academia, michael served as a graduate researcher at sungkyunkwan university's smart construction it lab, where he contributed significantly to optical sensor applications in structural health monitoring. currently, as a postdoctoral researcher at the same institution, he continues to explore cutting-edge technologies for structural assessment and digital twin applications.

🔬 Contributions and research focus

Michael's research is characterized by its innovative use of lidar technology, computer vision, and augmented reality in structural health monitoring. his work on algorithmic-based damage Civil Engineering detection, 3d reconstruction techniques, and point cloud analysis has advanced the field significantly. he has developed detailed 3d models for crack detection, utilized lidar for shape change analysis, and integrated ar applications for real-time structural assessments. his ongoing projects include camera-lidar feature-based fusion for bridge monitoring, close-up imaging for crack assessment, and semantic-driven 3d model generation using ar.

🏆 Accolades and recognition

Michael's contributions to structural health monitoring have earned him recognition within the academic and engineering communities. his innovative research has been showcased in Civil Engineering numerous conferences and publications, highlighting his expertise in lidar technology, computer vision, and ar integration. his work has not only enhanced structural assessment methodologies but also set new standards for efficiency and accuracy in the field.

💡 Impact and influence

Michael's research has had a profound impact on the field of structural health monitoring, particularly in the integration of advanced technologies for damage detection and assessment. his Civil Engineering development of 3d reconstruction techniques and point cloud analysis has improved the accuracy and efficiency of structural evaluations, influencing both academic research and practical applications in civil engineering.

🌍 Legacy and future contributions

Michael Bekele maru's legacy is one of innovation, precision, and technological integration in civil engineering. his work continues to inspire future researchers and engineers, setting a benchmark for excellence in structural health monitoring. as he advances in his career, michael aims to further explore the potential of digital twins, augmented reality, and deep learning in structural assessments, contributing to safer and more efficient infrastructure management worldwide.

Notable Publications 

  • Title: Comparison of depth camera and terrestrial laser scanner in monitoring structural deflections
    Author(s): MB Maru, D Lee, KD Tola, S Park
    Journal: Sensors, 2020

  • Title: Beam deflection monitoring based on a genetic algorithm using LiDAR data
    Author(s): MB Maru, D Lee, G Cha, S Park
    Journal: Sensors, 2020

  • Title: Improved building facade segmentation through digital twin-enabled RandLA-Net with empirical intensity correction model
    Author(s): MB Maru, Y Wang, H Kim, H Yoon, S Park
    Journal: Journal of Building Engineering, 2023

  • Title: Unsupervised domain adaptation-based crack segmentation using transformer network
    Author(s): DA Beyene, MB Maru, T Kim, S Park, S Park
    Journal: Journal of Building Engineering, 2023

  • Title: Improved building MEP systems semantic segmentation in point clouds using a novel multi-class dataset and local-global vector transformer network
    Author(s): Shuju Jing, Gichun Cha, Michael Bekele Maru, Byoungjoon Yu, Seunghee Park
    Journal: Journal of Building Engineering

Mr. Manoranjan Sahoo – Electrical Power system – Best Researcher Award

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Mr. Manoranjan Sahoo - Electrical Power system - Best Researcher Award

National institute of technology, Rourkela - India 

Author Profile 

ORCID

⚡ Early academic pursuits

Manoranjan Sahoo’s journey in electrical engineering began with a bachelor’s degree from g.i.t.a., bhubaneswar, where he specialized in electrical engineering, graduating with a cgpa of 7.3 in 2016. motivated by a deep passion for power systems, he pursued an m.tech in power system engineering at n.i.t. silchar, where he achieved a commendable cgpa of 8.3 in 2020. his academic dedication culminated in his doctoral studies at n.i.t. rourkela, where he submitted his thesis with an impressive cgpa of 8.6, demonstrating his expertise in power systems and machine learning applications.

🔧 Professional endeavors

Manoranjan’s professional trajectory includes significant teaching and research contributions. he has taught foundational and advanced courses such as basic electrical lab, electrical machine lab, and power system simulation lab, empowering students with practical and theoretical knowledge. his hands-on expertise with advanced tools like matlab/simulink, python, and real-time simulation platforms such as opal-rt reflects his technical proficiency. his roles have consistently bridged academia and applied research, ensuring impactful learning environments for aspiring engineers.

🌐 Contributions and research focus

His research spans critical areas in power systems, focusing on grid integration, deregulated power markets, and dynamic stability studies. his ph.d. work centers on developing machine-learning-based methods for detecting low-frequency oscillatory modes in power systems using phasor measurement units (pmus). he has also Electrical Power system delved into the challenges of dealing with bad data in pmu signals, implementing both supervised and unsupervised learning techniques. his m.tech project explored optimal bidding strategies in deregulated power markets, while his b.tech work focused on photovoltaic array integration, showcasing a blend of theoretical rigor and practical innovation.

🏅 Accolades and recognition

Manoranjan’s academic journey is marked by his consistent achievements, including a strong cgpa record in his higher education pursuits. his contributions to the Electrical Power system field of power systems and machine learning are highly regarded, reflecting his commitment to excellence in research and innovation. the successful submission of his doctoral thesis stands as a testament to his expertise and diligence in addressing complex problems in electrical engineering.

🌍 Impact and influence

Through his research, Manoranjan has contributed to enhancing the reliability and efficiency of modern power systems. his innovative approaches to tackling Electrical Power system challenges such as low-frequency oscillations in power systems have the potential to influence wide-area monitoring systems worldwide. his commitment to teaching ensures the dissemination of advanced knowledge and practices to the next generation of engineers, amplifying his impact on the field.

🚀 Legacy and future contributions

Manoranjan’s work in power systems and his integration of machine learning into electrical engineering research pave the way for innovative solutions in energy management and stability. his technical expertise and academic contributions position him as a thought leader in modern power systems, ensuring a legacy of impactful research and practical applications in a rapidly evolving energy landscape. with his dedication and skillset, he is poised to make significant advancements in the field, contributing to the global shift towards smarter and more sustainable power systems.

Notable Publications 

  • Title: A Partitioning Around Medoids (PAM) Based Sequential Clustering Approach for Model Order Estimation of Low-Frequency Oscillations in Wide Area Measurement System
    Authors: Manoranjan Sahoo, Shekha Rai
    Journal: Sādhanā
  • Title: Model Order Estimation for Low-Frequency Oscillations in Power Systems by an Advanced K-Mean Clustering Approach
    Authors: Manoranjan Sahoo, Jangam Sandeep, Shekha Rai
    Journal: Electric Power Systems Research