Prof. Dr. Saleh Albahli | Artificial Intelligence | Best Researcher Award

Prof. Dr. Saleh Albahli | Artificial Intelligence | Best Researcher Award

Qassim University, Saudi Arabia.

Dr. Saleh Albahli is a highly accomplished academic and researcher specializing in Digital Transformation, Data Science, and Artificial Intelligence. Currently an Associate Professor and Vice-Dean of Information Technology Deanship at Qassim University, he is known for spearheading transformative digital initiatives, leading enterprise architecture projects, and contributing to cutting-edge research in machine learning and deep learning. His work is globally recognized, ranking him among the top 2% of scientists in AI research worldwide.

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🎓 Education

Dr. Saleh Albahli holds a Ph.D. in Computer Science with distinction from Kent State University, USA (2016), showcasing his expertise in advanced computational methodologies and research excellence. He earned a Master’s degree in Information Technology with distinction from The University of Newcastle, Australia (2010), highlighting his dedication to mastering cutting-edge IT solutions. His academic journey began with a Bachelor’s degree in Computer Science from King Saud University, Saudi Arabia (2004), laying a strong foundation for his accomplished career in technology and innovation.

💼 Experience

Dr. Saleh Albahli has built an illustrious career, currently serving as an Associate Professor in the Department of IT at Qassim University since 2020, where he contributes to advancing education and research. Concurrently, he holds dual leadership roles as Vice-Dean of IT Deanship and Director of Enterprise Architecture & Digital Transformation at Qassim University, spearheading transformative initiatives to enhance technological frameworks and drive digital innovation.

Previously, Dr. Albahli gained international experience as a Senior System Analyst at Cleveland Clinic, USA (2015–2016), where he developed cutting-edge systems to optimize healthcare operations. He also served as a Lecturer at Kent State University, USA (2015–2016), imparting knowledge and fostering academic growth. Earlier in his career, he worked as an Oracle Developer and Apps DBA at Riyadh Bank and Integrated Telecom Company in Saudi Arabia (2005–2007), honing his technical expertise in database systems and enterprise applications.

🔬 Research Interests

Digital Transformation and its integration with enterprise architecture

Machine Learning and Deep Learning Pipelines

Big Data Analytics, Data Governance, and Predictive Analytics

Artificial Intelligence Applications in healthcare and business

Process Optimization in technology-driven environments

🏆 Awards & Recognitions

Ranked among the top 2% of scientists globally in AI research (2022)

First Place in Digital Transformation (Qiyas) – Qassim University (2022, 2023)

ISO certifications in 22301, 20000, and 27001 for excellence in IT management

📚 Selected Publications 

Efficient Hyperparameter Tuning for Predicting Student Performance with Bayesian Optimization
Albahli, S.
Multimedia Tools and Applications, 2024, 83(17), pp. 52711–52735.
This study introduces a Bayesian optimization approach to enhance hyperparameter tuning for predictive models in educational datasets, achieving improved accuracy and efficiency. (Citations: 4)

MedNet: Medical Deepfakes Detection Using an Improved Deep Learning Approach
Albahli, S., Nawaz, M.
Multimedia Tools and Applications, 2024, 83(16), pp. 48357–48375.
This paper presents MedNet, a novel deep learning framework tailored to detect medical deepfakes, ensuring the integrity of critical healthcare data. (Citations: 4)

Opinion Mining for Stock Trend Prediction Using Deep Learning
Albahli, S., Nazir, T.
Multimedia Tools and Applications, 2024.
Leveraging deep learning techniques, this research focuses on sentiment analysis to predict stock trends, demonstrating robust performance metrics. (Citations: 0)

An Improved DenseNet Model for Prediction of Stock Market Using Stock Technical Indicators
Albahli, S., Nazir, T., Nawaz, M., Irtaza, A.
Expert Systems with Applications, 2023, 232, 120903.
This work proposes enhancements to DenseNet architectures for stock market predictions based on technical indicators, achieving notable predictive accuracy. (Citations: 10)

A Circular Box-Based Deep Learning Model for the Identification of Signet Ring Cells from Histopathological Images
Albahli, S., Nazir, T.
Bioengineering, 2023, 10(10), 1147.
This open-access study develops a circular box-based deep learning model for the accurate detection of signet ring cells in histopathological images, aiding cancer diagnosis.

 

 

 

Mrs. Golshid Ranjbaran | Artificial Intelligence | Best Researcher Award

Mrs. Golshid Ranjbaran | Artificial Intelligence | Best Researcher Award

University of Saskatchewan, Canada.

Golshid Ranjbaran is a PhD Candidate in Computer Science at the University of Saskatchewan (USASK), specializing in Artificial Intelligence, Machine Learning, and Interpretability. With a Bachelor's degree in Software Engineering and a Master's in Artificial Intelligence from the Science and Research Branch in Iran, he has accumulated several awards, including the Best Paper Award at the IKT Conference in 2021 and Best Researcher at ITRC in 2022. Golshid's research is aimed at advancing AI methodologies and improving machine learning models for real-world applications. He was also a research associate at the Data Science & Big Data Lab in Seville, Spain, in 2023. 🌐

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Education 🎓

Golshid holds a Bachelor's degree in Software Engineering and a Master's degree in Artificial Intelligence from the Science and Research Branch in Iran. He is currently pursuing a Ph.D. in Computer Science at the University of Saskatchewan (USASK), Canada, where he focuses on AI, machine learning, and interpretability, aiming to bridge the gap between theoretical advancements and practical applications.

Experience 🏢

Golshid has been awarded several prestigious positions and accolades, including a research position at the Data Science & Big Data Lab in Seville, Spain (2023), and was recognized as the Best Researcher at ITRC (2022). He has also contributed to various consultancy projects and industry collaborations, such as working on AI systems at ITRC, smart meters algorithms, and data governance in Iran.

Research Interests 🔍

Enhancing model interpretability through methods like SHAP.

Exploring sentiment analysis for stock market prediction.

Developing augmented techniques for unbalanced tasks in the financial domain.

Improving network security through Moving Target Defense technology.

Investigating Federated Learning for wearable health devices and ontology-based text summarization for efficient information processing.

Awards 🏆

Best Paper Award at the IKT Conference (2021)

Best Researcher Award at the Iran Telecommunication Research Center (ITRC) (2022)

Research Position at the Data Science & Big Data Lab in Seville, Spain (2023)

Nomination for the Gala GSA Award at the University of Saskatchewan (2025).

Selected Publications 📚

C-SHAP: A Hybrid Method for Fast and Efficient InterpretabilityApplied Sciences (Q2 Journal), Published 2025.

Leveraging Augmentation Techniques for Tasks with Unbalancedness within the Financial DomainEPJ Data Science (Q1 Journal), Published 2023.

Investigating Sentiment Analysis of News in Stock Market PredictionInternational Journal of Information and Communication Technology Research, Published 2024.

Unsupervised Learning Ontology-Based Text Summarization Approach with Cellular Learning AutomataJournal of Theoretical and Applied Information Technology, Published 2023.

Analyzing the Effect of News Polarity on Stock Market PredictionProceedings of the 12th International Conference on Information and Knowledge Technology (IKT), Published 2021.

 

 

Assist. Prof. Dr. Yang Liu |Aquaculture | Best Researcher Award

Assist. Prof. Dr. Yang Liu |Aquaculture | Best Researcher Award

Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, China.

Yang Liu is an Assistant Research Fellow at the Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences. He specializes in aquaculture and has dedicated his research career to studying fish physiology, genetics, and aquaculture sustainability. Liu's research is particularly focused on DNA methylation, transcriptome profiling, and lipid metabolism, which play key roles in fish growth, color formation, and heterosis. His contributions significantly advance the field of marine biology, particularly in the development of aquaculture practices.

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Education 🎓

Yang Liu completed his Bachelor's Degree in Aquaculture at Tianjin Agricultural University in China, between 2011 and 2015. This foundation in agricultural sciences paved the way for his advanced studies in the field of aquaculture. He went on to earn his PhD from the Ocean University of China from 2015 to 2020. During his doctoral studies, Yang specialized in aquaculture, genetics, and fish physiology, focusing on understanding the genetic and physiological mechanisms behind fish growth, environmental adaptation, and skin color formation. His work contributed to advancing knowledge in aquaculture practices and the genetic management of marine species, making a significant impact in the field.

Experience 🧑‍🔬

Yang Liu began his postdoctoral research at the Yellow Sea Fisheries Research Institute, part of the Chinese Academy of Fishery Sciences, in 2020. During his postdoc tenure (2020-2022), he focused on advancing research in aquaculture genetics, fish physiology, and environmental adaptation in marine species. His research contributed significantly to understanding the genetic mechanisms that govern traits such as growth rates and environmental resilience in aquatic organisms. Since 2020, he has continued his work at the institute as an Assistant Research Fellow, where he leads various projects in aquaculture, emphasizing genetic improvement and functional genomics in marine species. His contributions to the field have solidified his position as a key researcher at the institute.

Research Interests 🔬

Genetic Mechanisms & DNA Methylation 🧬
A significant part of Yang's research explores DNA methylation and how it influences various biological processes. His studies on lipid metabolism and the antioxidant pathway in species like the Plectropomus leopardus (a type of grouper) reveal how these genetic factors play a role in skin color formation. This research has practical applications in improving fish aesthetics and marketability.

Lipid Metabolism & Hybrid Fish Heterosis 🐟
Yang's research also investigates the role of lipid metabolism in promoting heterosis (hybrid vigor) in Jinhu grouper. His findings provide valuable knowledge on how lipid pathways contribute to the enhanced performance of hybrid fish species, aiding in the development of more resilient and higher-yielding aquaculture species.

Genetic Mapping for Growth Traits 📊
Yang is also engaged in genetic mapping and QTL (quantitative trait loci) mapping, focusing on identifying the genetic basis of growth-related traits in hybrid fish species such as the Yunlong grouper. His work in this area provides foundational data to optimize breeding programs for faster-growing and more robust fish.

Salinity Regulation in Marine Life 🌊
Another aspect of Yang's research includes understanding how fish adapt to changing environmental conditions, particularly salinity regulation in species like spotted sea bass. Through his work on the Na+/H+ exchanger gene family, Yang aims to uncover the genetic mechanisms behind fish's ability to withstand salinity fluctuations, which has significant implications for marine aquaculture in different environmental conditions.

Selected Publications 📑

Liu Y., Wang L., Li Z., et al. (2025). DNA methylation and transcriptome profiling reveal the role of the antioxidant pathway and lipid metabolism in Plectropomus leopardus skin color formation. Antioxidants, 14: 93.

Liu Y., Wang L., Li Z., et al. (2024). DNA methylation and subgenome dominance reveal the role of lipid metabolism in Jinhu grouper heterosis. International Journal of Molecular Sciences, 25: 9740.

Liu Y., Tian Y., Wang L., et al. (2022). Construction of high-density linkage maps and QTL mapping for growth-related traits in F1 hybrid Yunlong grouper (Epinephelus moara♀ × E. lanceolatus♂). Aquaculture, 548: 737698.

Liu Y., Wang H., Wen H., et al. (2020). First high-density linkage map and QTL fine mapping for growth-related traits of spotted sea bass (Lateolabrax maculatus). Marine Biotechnology, 22: 526-538.

Liu Y., Wen H., Qi X., et al. (2019). Genome-wide identification of the Na+/H+ exchanger gene family in Lateolabrax maculatus and its involvement in salinity regulation. Comparative Biochemistry & Physiology Part D: Genomics & Proteomics, 29: 286-298.

 

 

 

Mr. Kai Yang | Ship | Best Researcher Award

Mr. Kai Yang | Ship | Best Researcher Award

College of Shipbuilding Engineering, Harbin Engineering University, China.

Kai Yang is a dedicated engineering professional with expertise in ship structural calculations and vibration and noise control. He is currently engaged in the professional drawing review of inland waterway ship hulls at Harbin Engineering University and the China Classification Society-Harbin Branch. With a strong foundation in maritime safety, he is conducting research on the safety of ships navigating in inland ice areas. His innovative contributions include technical regulations for hovercraft and significant work on ship vibration and noise control.

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Education 🎓

Kai Yang holds a Master's degree in Engineering. His academic journey has been shaped by his focus on ship structural calculations and vibration control, enabling him to undertake complex projects related to ship safety.

Experience 🛠️

Kai currently works at the College of Shipbuilding Engineering at Harbin Engineering University and the China Classification Society-Harbin Branch. He has contributed significantly to professional drawing reviews for inland waterway ships and has accumulated experience in technical regulations for hovercraft. His expertise also spans vibration and noise control in maritime engineering.

Research Interests 🔬

Kai Yang's research is primarily dedicated to enhancing ship safety, with a special emphasis on navigating ships through inland ice areas. His work aims to address the unique challenges posed by icy waters and ensure the safety of ships operating in such extreme environments.

Exploration of Hovercraft Technology 🌬️
Kai is actively researching hovercraft technology, focusing on overcoming the technical difficulties associated with fully cushioned hovercraft. His contributions aim to improve the design and operation of hovercraft for various maritime applications.

Ship Vibration and Noise Control 🔊
Kai Yang is also exploring advanced methods in ship vibration and noise control. His work involves developing effective solutions to minimize vibration and noise, improving the overall operational efficiency and comfort of ships.

Technical Solutions and Innovations 💡
Throughout his research, Kai is dedicated to developing technical solutions that can tackle the various challenges faced in ship navigation, hovercraft technology, and vibration/noise control. His goal is to create safer, quieter, and more efficient maritime technologies.

Selected Publications 📚

Research on Torsional Vibration of Inland Waterway Vessel Propulsion Shafting Under Ice Load
Yang, K., Feng, G.
Journal of Wuhan University of Technology (Transportation Science and Engineering), 2024, 48(3), pp. 486–490
This study investigates the torsional vibration of the propulsion shafting of inland waterway vessels subjected to ice load, aiming to enhance the design and safety of vessels navigating in icy waters.

Summary of Safety Research on Ships Sailing in Inland Ice Area
Yang, K., Feng, G.
Proceedings of the International Offshore and Polar Engineering Conference, 2024, 1, pp. 2123–2128
This paper summarizes critical safety research on ships operating in inland ice areas, emphasizing technological advancements and safety measures for navigating in harsh ice conditions.

Research on Temperature Distribution in Container Ship with Type-B LNG Fuel Tank Based on CFD and Analytical Method
Liu, J., Feng, G., Wang, J., Xu, C., Yang, K.
Brodogradnja, 2024, 75(3), 75302
This paper explores the temperature distribution within container ships equipped with Type-B LNG fuel tanks, applying CFD and analytical methods to optimize ship design for fuel safety and efficiency.

 

 

 

Mr. Xiaogang Liu | Molecular Biology | Best Researcher Award

Mr. Xiaogang Liu | Molecular Biology | Best Researcher Award

Beijing Institute of Technology, China.

Dr. Xiaogang Liu is a dedicated Lecturer at the Zhuhai Campus of Beijing Institute of Technology. With a strong foundation in Biochemistry and Molecular Biology, he specializes in Chemical Biology. His research primarily focuses on Computational Chemistry to study pH-Responsive Fluorescent Probes and develop related software. In addition to his research contributions, he is passionate about teaching and mentoring students in the areas of Molecular Biology and Immunology.

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Education 🎓

Xiaogang Liu earned his Bachelor’s Degree in Biochemistry from Shanxi University, where he laid the groundwork for his extensive studies in the fields of Biochemistry and Molecular Biology. During his time at Shanxi University, he gained a solid understanding of the core principles of biochemical processes and molecular interactions, which set the stage for his later academic pursuits. His education at Shanxi University sparked his passion for Chemical Biology, ultimately shaping his career in research and teaching.

Experience 💼

Dr. Liu has taken on multiple roles in research and academia. Currently, as a Lecturer at Beijing Institute of Technology, he actively teaches and supervises students while also conducting research in Bioinformatics and Chemical Biology. His work focuses on exploring computational methodologies to understand complex chemical systems and biological molecules.

Research Interests 🔬

Chemical Biology: Investigating pH-Responsive Fluorescent Probes

Computational Chemistry: Developing software to support chemical biology research

Bioinformatics: Exploring the intersection of biology and computing to enhance molecular biology applications
Dr. Liu's research also delves into the integration of Computational Chemistry and Chemical Biology to advance understanding in fields like fluorescence sensing, probe design, and software development.

Selected Publications 📚

Computational Chemistry Study of pH-Responsive Fluorescent Probes and Development of Supporting Software
Journal: Molecules (2025), Volume: 30(2), Article 273
Contributors: Xiaogang Liu

Large Scale Virtual Screening for Finding Inhibitor against the RNA-dependent RNA Polymerase from Herbal Medicine for SARS-Cov-2 Therapy
Proceedings of the 11th International Conference on Biomedical Engineering and Bioinformatics (2022)
Contributors: Xiaogang Liu, Zirong Liang, Shiye Wu, Ying Wang, Binquan Gou

Virtual Screening for Finding Inhibitor Against the Main Protease of SARS-Cov-2 from the FDA-Approved Drugs Database
International Conference on Biomedical and Intelligent Systems (IC-BIS 2022) (2022-12-06)
Contributors: Xiaogang Liu, Shiye Wu, Zitong Zhu, Ying Wang, Binquan Gou

Teaching Reform and Application of Cell Biology in Bioengineering Specialty
Science & Technology Information (2021-12-13)
Contributors: Xiaogang Liu

 

 

Prof. Dr. Heng Zhang | Radar | Best Researcher Award

Prof. Dr. Heng Zhang | Radar | Best Researcher Award

Department of Space Microwave Remote Sensing System, Aerospace Information Research Institute, Chinese Academy of Sciences, China.

Dr. Heng Zhang, a dedicated scholar and Member of IEEE, specializes in bistatic synthetic aperture radar imaging and interferometry. With a strong academic foundation and professional journey rooted in innovation, he has contributed extensively to aerospace information research and advanced radar technologies.

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Education 📚

Dr. Heng Zhang embarked on his academic journey by earning a B.S. degree in Electronic Information Science from Nanjing University, Nanjing, China, in 2013, where he gained a strong foundation in electronic systems and information processing. He further pursued a Ph.D. in Communication and Information Systems from the University of Chinese Academy of Sciences, Beijing, China, in 2018, specializing in advanced communication technologies and radar systems. His rigorous education laid the groundwork for his impactful research in bistatic synthetic aperture radar imaging and interferometry.

Experience 🛠️🌌

Since 2018, Dr. Heng Zhang has been serving as a Researcher at the Aerospace Information Research Institute, part of the Chinese Academy of Sciences, Beijing. In this role, he has been at the forefront of pioneering advancements in radar imaging and interferometry, contributing to the development of cutting-edge technologies. His work emphasizes innovation and precision, driving forward the capabilities of bistatic synthetic aperture radar systems to address complex scientific and industrial challenges.

Research Interests 🔍🌐

Bistatic Synthetic Aperture Radar Imaging: Exploring novel approaches to radar image acquisition and processing.

Interferometry: Advancing techniques for precise measurement and analysis in aerospace applications.

Selected Publications 📄📚

High-Resolution High-Squint Large-Scene Spaceborne Sliding Spotlight SAR Processing via Joint 2D Time and Frequency Domain Resampling
Ren, M., Zhang, H., Yu, W.
Remote Sensing, 2025, 17(1), 163

Key Technologies for Spaceborne SAR Payload of LuTan-1 Satellite System
Deng, Y., Wang, Y., Liu, K., Zhang, H., Wang, J.
Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 2024, 53(10), pp. 1881–1895

Orthogonal Waveform Design with Fractional Programming on the Ambiguity Suppression of SAR Systems
Deng, Y., Zhang, Y., Zhang, Z., Wang, W., Zhang, H.
Science China Information Sciences, 2024, 67(9), 192305

An Innovative Internal Calibration Strategy and Implementation for LT-1 Bistatic Spaceborne SAR
Jiao, Y., Liu, K., Yue, H., Zhang, H., Zhao, F.
Remote Sensing, 2024, 16(16), 2965

Refined InSAR Mapping Based on Improved Tropospheric Delay Correction Method for Automatic Identification of Wide-Area Potential Landslides
Li, L., Wang, J., Zhang, H., Xiang, W., Fu, Y.
Remote Sensing, 2024, 16(12), 2187

 

 

Mr. Jin Qilin  | Computer vision | Best Researcher Award

Mr. Jin Qilin  | Computer vision | Best Researcher Award

Hohai University, China.

Qilin Jin is a passionate researcher specializing in the application of artificial intelligence and software engineering. With a focus on integrating AI with real-world engineering challenges, he has made significant strides in areas such as sonar image analysis, defect detection, and structural monitoring. His innovative work has been recognized through impactful publications and contributions to the scientific community.

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🎓 Education

Qilin Jin is currently pursuing a Ph.D. in Computer Science, specializing in the applications of artificial intelligence and software engineering to solve complex real-world problems. His doctoral research focuses on leveraging advanced AI algorithms for defect detection and structural analysis. He holds a Master's Degree in Engineering, where his studies centered on intelligent systems and structural monitoring, providing a strong foundation for his innovative contributions to these fields.

💼 Experience

Qilin Jin is an accomplished researcher with extensive experience in developing AI-driven solutions tailored for industrial and engineering applications. His work focuses on creating innovative methods for defect detection and segmentation, leveraging cutting-edge artificial intelligence technologies to enhance accuracy and efficiency. As a dedicated collaborator, Qilin actively contributes to multidisciplinary projects, combining expertise from various domains to address complex challenges in structural monitoring and intelligent systems.

🔍 Research Interests

Artificial Intelligence Applications: Advanced algorithms for defect detection and structural analysis.

Software Engineering: Innovative methods to enhance engineering software development.

Deep Learning: Leveraging deep neural networks for real-time segmentation and detection tasks.

🏆 Awards and Recognitions

Young Innovator Award for contributions to AI-based defect detection in sonar imaging.

Recognized for excellence in research by leading journals like Applied Sciences and Journal of Sound and Vibration.

🖋️ Publications

  1. Jin, Qilin, Han Qingbang, Qian Jianhua, et al. "Drainage Pipeline Multi-Defect Segmentation Assisted by Multiple Attention for Sonar Images," Applied Sciences, 2025, 15(2): 597.
    Cited by 5 articles.
  2. Jin Qilin, Han QingBang, Su NaNa, et al. "A deep learning and morphological method for concrete cracks detection," Journal of Circuits, Systems, and Computers, 2023, 4.
    Cited by 3 articles.
  3. Wu Yang, Han QingBang, Jin Qilin, et al. "LCA-YOLOv8-Seg: An Improved Lightweight YOLOv8-Seg for Real-Time Pixel-Level Crack Detection of Dams and Bridges," Applied Sciences, 2023, 13: 10583.
    Cited by 7 articles.
  4. Han YuFeng, Han QingBang, Zhang ShiGong, Su NaNa, Jin Qilin, Shan MingLei. "Semianalytical numerical iterative analysis for a one-dimensional second harmonic wave," Journal of Sound and Vibration, 2022, 8.
    Cited by 2 articles.

 

 

 

Dr. Gianluca Sesso | Psychopharmacology | Best Researcher Award

Dr. Gianluca Sesso | Psychopharmacology | Best Researcher Award

IRCCS Stella Maris Foundation Hospital, Italy.

Dr. Gianluca Sesso is a distinguished researcher in the fields of neuroscience and psychiatry. He completed his MD, graduating Magna Cum Laude from the University of Pisa in 2017. Dr. Sesso furthered his expertise by pursuing post-graduate studies in Neuroscience at the Ecole des Neurosciences in Paris. His research spans various aspects of neuropsychiatric conditions, with a particular focus on mood disorders, emotional dysregulation, and self-injury behaviors in adolescents. He has contributed significantly to the scientific community with multiple publications in high-impact journals, aiming to enhance our understanding of psychiatric disorders and their pharmacological management.

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Education 🎓

Dr. Gianluca Sesso began his academic journey with a Scientific High School Diploma from Liceo Scientifico Statale ‘L. Mascheroni’, Bergamo in 2010, where he earned a perfect score of 100/100. He then pursued his MD at the University of Pisa from 2010 to 2017, graduating Magna Cum Laude, which marked a significant milestone in his medical and scientific education. Following this, Dr. Sesso furthered his expertise through a Post-Graduate Program in Neuroscience at the Ecole des Neurosciences in Paris (2016–2017), where he participated in a rigorous research program with laboratory rotations. This diverse academic foundation provided him with a strong theoretical and practical background in neuroscience and psychiatry, laying the groundwork for his subsequent research endeavors.

Experience 💼

Dr. Sesso's academic journey includes a Postdoctoral Fellowship at the University of Peking and several research leadership roles. He has published widely on topics ranging from antisocial personality disorder and disruptive behavior disorders to bipolar disorder and autism spectrum conditions. He also worked closely with youth populations, addressing mood disorders and the impact of psychostimulants on ADHD treatments.

Research Interests 🔬

Mood Disorders: Investigating the underlying neurobiological mechanisms of mood disorders, with a focus on treatments that can better address emotional regulation and impulsivity.

Bipolar Disorder: Exploring the comorbidities associated with bipolar disorder and identifying novel pharmacological interventions to enhance patient care.

ADHD: Studying the social cognition and empathy deficits in individuals with ADHD, with a particular interest in treatment effects using psychostimulants.

Self-Injurious Behaviors: Examining the links between mood dysregulation and non-suicidal self-injury in adolescents, with an emphasis on the role of temperament and psychopharmacological management.

Publications Top Notes 📚

Clinical and Biological Correlates of Emotional Dysregulation in Children and Adolescents: A Transdiagnostic Approach to Developmental Psychopathology
Journal: Brain Sciences (2024)

Clozapine Treatment for Aggressive Behaviors in Youths with Neurodevelopmental Disorders
Journal: Journal of Child and Adolescent Psychopharmacology (2024)

Efficacy of Methylphenidate for Internet Gaming Disorder and Internet Addiction in Patients with Attention-Deficit/Hyperactivity Disorder
Journal: Current Pharmaceutical Design (2024)

Emotional Dysregulation and Sleep Problems: A Transdiagnostic Approach in Youth
Journal: Clinics and Practice (2024)

Internet Gaming Disorder in Children and Adolescents with Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder
Journal: Brain Sciences (2024)

 

 

Dr. Michela Longhi | Metamaterials | Best Researcher Award

Dr. Michela Longhi | Metamaterials | Best Researcher Award

Niccolò Cusano University, Italy,

Michela Longhi is an Italian researcher and engineer specializing in electromagnetics, artificial materials, and wireless systems. She holds multiple positions, including Associate Editor of the Nonlinear Engineering - Modeling and Application Journal and Partner of LabChain. Throughout her career, she has gained extensive experience in R&D engineering, particularly in the fields of RF devices, antennas, and electromagnetic fields, contributing significantly to the design and optimization of high-performance materials and systems. She has a PhD in Electromagnetic Engineering from the University of Rome "Tor Vergata," and has held numerous positions in prestigious institutions such as ETH Zurich, Microwave Vision Group, and Niccolò Cusano University. 🌍

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Education 🎓

Michela Longhi earned her PhD in Electromagnetic Engineering (European Label) from the University of Rome "Tor Vergata", where she conducted research at the Pervasive Electromagnetics Lab between November 2015 and October 2018. During her doctoral studies, she focused on the design and prototyping of RF devices for short-range sensing, specifically in drone applications, with real-world implications for Smart City infrastructure, precision agriculture, and supply chains.

In addition to her PhD, Michela completed an International PhD at ETH Zurich, working with the Autonomous Systems Lab from November 2017 to May 2018. Here, she gained hands-on experience in the development of intelligent robotic systems capable of autonomous operation in complex and dynamic environments, which further enriched her research and broadened her expertise in electromagnetics and robotics.

Michela also holds a Master’s Degree in Electronic Engineering from the University of Rome "Tor Vergata", where she developed a strong foundation in electromagnetic materials, RF engineering, and wireless communications.

Experience 💼

Michela Longhi is an accomplished researcher and academic, currently serving as an Associate Editor for the Nonlinear Engineering - Modeling and Application Journal and a Partner at LabChain, focusing on blockchain and innovation. She is also a founding member of the URSI WIRS and a Commission Member for the MUR Public Concourse. Since 2021, Michela has held roles as a Post-Doctoral Researcher and Professor at Niccolò Cusano University, specializing in upper limb exoskeletons and electromagnetic materials. She has extensive experience in RF engineering and system design from her time at Microwave Vision Group (MVG) and CNR, where she worked on advanced EMC technologies and neuromodulation research.

Research Interests 🔬

Antenna Design and Telecommunications

Michela has made significant contributions to antenna design, particularly in the context of 5G communication, telecommunications, and aerospace. Her work in these areas has helped advance the development of high-performance antennas and EMC technologies for a variety of industries.

Smart City and Precision Agriculture

In recent years, Michela has focused on the development of upper-limb exoskeletons for medical and assistive purposes, as well as innovations in electromagnetic materials tailored for smart city infrastructure and precision agriculture. These advancements aim to improve urban living and agricultural practices by integrating cutting-edge RF technologies into everyday applications.

Exoskeleton Development

A key part of Michela's research is the development and optimization of upper-limb exoskeletons, which have promising applications in rehabilitation and assistive technologies. Her work seeks to enhance mobility and quality of life for individuals with physical impairments through advanced electromagnetic and robotic systems.

Awards 🏆

Founding Member, URSI WIRS (Women in Radio Science), (2023 - Present)

IEEE WIE Communication Team, IEEE Women in Engineering (2023 - Present)

MUR Commission Member, Ministero dell’Università e della Ricerca (2021-2022)

Publications Top Notes📚

Optimization Tools for the Design of Meta-Covers for Linear Antenna with Beam- and Null-Steering Capabilities
Published in: Applied Sciences, 2025-01-08

A Statistical Approach for Robust Metasurfaces and Metasurface-Based RIS Engineering
Published in: IEEE Transactions on Antennas and Propagation, 2024-06

Phase-Gradient Huygens’ Metasurface Coatings for Dynamic Beamforming in Linear Antennas
Published in: IEEE Transactions on Antennas and Propagation, 2023

Array Synthesis of Circular Huygens Metasurfaces for Antenna Beam-Shaping
Published in: IEEE Antennas and Wireless Propagation Letters, 2023-11

A Statistical Approach for Robust Metasurfaces and Metasurface-Based RIS Engineering
Preprint: 2023-10-12

 

 

Dr. Natascia Bruni | Chemistry | Best Researcher Award

Dr. Natascia Bruni | Chemistry | Best Researcher Award

Candioli Pharma srl, Italy.

Natascia Bruni is an experienced regulatory compliance and quality management professional with over two decades of experience in the pharmaceutical and feed supplements industries. Currently, she serves as the Compliance Unit Director, Qualified Person, and QPPV at Acel Pharma srl, where she plays a pivotal role in ensuring regulatory compliance, managing product registrations, and overseeing pharmacovigilance activities. Throughout her career, Natascia has worked across various sectors, including pharmaceutical companies (human and veterinary), focusing on quality assurance, regulatory affairs, and strategic business compliance. She is well-versed in navigating complex regulatory landscapes and has made substantial contributions to corporate governance, legal risk management, and quality audits.

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Education 🎓

Natascia Bruni's educational background demonstrates her deep expertise in both scientific and management fields, which has greatly contributed to her successful career in regulatory affairs and quality management. She completed her degree in Chemistry (Nuclear) at the University of Turin from 1991 to 1996, earning the highest distinction with a final vote of 110/110 con lode. This solid foundation in chemistry equipped her with a thorough understanding of chemical processes and analytical methods, which would later be pivotal in her regulatory and quality assurance roles in the pharmaceutical industry.

In addition to her scientific education, Natascia pursued specialized training in Regulatory Affairs and Pharmacovigilance for Drugs between 2001 and 2002, sharpening her skills in the complex regulatory frameworks governing drug safety and compliance. This training became essential in her role as a Qualified Person and QPPV in various pharmaceutical companies, where she led efforts to ensure products met both safety and regulatory standards.

Furthermore, Natascia completed a Business Management Course from 2015 to 2018, which enhanced her leadership, strategic planning, and operational management abilities. This course helped her integrate business and regulatory perspectives, allowing her to lead teams and drive organizational success in compliance-related activities.

Natascia also deepened her technical expertise by attending the School in Technology Enhanced Chemical Synthesis from 1996 to 1999, where she learned advanced techniques in chemical synthesis that continue to inform her work in pharmaceutical and feed supplement regulatory processes. Her multi-disciplinary education has provided a strong foundation for her leadership role in compliance and regulatory affairs, combining scientific rigor with strategic management skills.

Experience 💼

Compliance Unit Director - Qualified Person - QPPV (2012–Present), Acel Pharma srl (Candioli Group), Beinasco (Torino)
Responsible for ensuring the regulatory compliance of raw materials and finished products, overseeing registration/approvals, and managing import/export activities. Works closely with various departments to ensure that all products sold comply with national and international regulations.

Quality Unit Manager & Qualified Person (2007–2012), Olon Spa (Fidia Group), Rodano (MI) and Settimo Torinese (To)
Led the harmonization of QA/QC and regulatory procedures across two sites, ensuring GMP and regulatory compliance for the company’s product portfolio. Managed communications with health authorities and conducted quality audits for suppliers.

Chemistry Department Responsible (1997–1999), Antibiotic Spa, Settimo Torinese (To)
Conducted independent research and developed experimental procedures within the research project scope.

Researcher (1996–1997), Antibiotic Spa, Settimo Torinese (To)
Developed analytical methods and processes in the field of pharmaceutical research.

Research Interests 🔬

Regulatory Compliance in Pharmaceutical Products 📜

Natascia is particularly interested in the regulatory compliance of both raw materials and finished products in the pharmaceutical industry. Her work emphasizes the critical importance of navigating complex regulatory frameworks and ensuring that all pharmaceutical products, especially those used in veterinary medicine, comply with the highest standards of food safety, quality control, and marketing.

Pharmacovigilance & Product Registration 💊

A key area of Natascia's research is in pharmacovigilance, particularly focusing on the monitoring and reporting of adverse effects for drugs, ensuring products maintain safety and compliance throughout their lifecycle. She explores the processes involved in product registration, striving to streamline the approvals and regulatory checks necessary for market entry, particularly in international markets.

Process Improvement Methodologies 🔧

Natascia is also keen on exploring process improvement methodologies within the regulatory compliance space. Her work in this area aims to enhance operational efficiency, reduce legal risks, and strengthen internal control structures. By continuously improving regulatory and operational processes, she contributes to creating a safer and more efficient regulatory environment for pharmaceutical companies, particularly in the feed supplement and veterinary drug sectors.

Awards 🏅

University Senate Award: Best Academic Graduate (1996)
Awarded for excellence in academic performance by the Presidency Council of the Italian Chamber.

OPTIME Award: Best Experimental Dissertation of the Year (1996)
Recognized by the Industrial Union for outstanding research work.

Publications 📚

"Molecular Characterization of the Gorgonzola Cheese Mycobiota and Selection of a Putative Probiotic Saccharomyces cerevisiae var. boulardii for Evaluation as a Veterinary Feed Additive" Published in Applied Microbiology, 2024, 4(2), pp. 650–664.

"Efficacy of a Dietary Supplement in Dogs with Osteoarthritis: A Randomized Placebo-Controlled, Double-Blind Clinical Trial"
Published in PLoS ONE, 2022, 17(2), e0263971.

"Chronic Kidney Disease and Dietary Supplementation: Effects on Inflammation and Oxidative Stress", Published in Veterinary Sciences, 2021, 8(11), 277.
"Chronic Intestinal Disorders in Humans and Pets: Current Management and the Potential of Nutraceutical Antioxidants as Alternatives", Published in Animals, 2022, 12(7), 812.