Assistant Professor, Mansoura University and Egypt

Mostafa Mahmoud El-Gayar is an Assistant Professor in Information Technology at Mansoura University, Egypt. He holds expertise in Cyber Security, Internet of Things (IoT), Image Processing, Computer Vision, and Machine Learning. He is recognized for his contributions to enhancing security measures in IoT systems, developing intelligent frameworks for machine learning, and deep learning applications in various domains. El-Gayar has made significant strides in the detection of phishing attacks, heart disease prediction, and the detection of deep fake videos. His work is highly regarded for its practical implications in modern technology, and his research continues to influence both academic and industrial communities. He is actively engaged in researching solutions for cybersecurity challenges, including IoT botnet detection, anomaly detection, and semantic-based search engines. El-Gayar’s extensive publication record reflects his significant impact on technology and innovation.

Profile :

Google Scholar

Education :

Mostafa Mahmoud El-Gayar completed his academic journey at Mansoura University, Egypt, where he earned his undergraduate and postgraduate degrees in Computer Science and Information Technology. His academic career is defined by a deep commitment to exploring the intersection of machine learning, artificial intelligence, and cybersecurity. El-Gayar has published extensively in prestigious journals and conferences, earning recognition for his research contributions. His doctoral research focused on areas like image processing, machine learning applications, and their impact on real-world security challenges. Throughout his career, he has continuously engaged in advanced studies to refine his knowledge and skills in the rapidly evolving domains of artificial intelligence and cybersecurity. As an academic leader, El-Gayar mentors students and researchers, fostering an environment of intellectual growth and innovation in his field. His educational foundation, coupled with his ongoing academic pursuits, positions him as a prominent figure in his areas of research.

Experience:

Dr. Mostafa Mahmoud El-Gayar has a distinguished career as an academic professional and researcher, currently serving as an Assistant Professor in Information Technology at Mansoura University, Egypt. His experience spans teaching, research, and consulting in cutting-edge areas of computer science, particularly focusing on cybersecurity, machine learning, and Internet of Things (IoT). Dr. El-Gayar has been actively involved in several research projects aimed at developing innovative solutions for real-world security problems, including IoT botnet attack detection, heart disease prediction, and deep fake detection. He has collaborated with numerous researchers and practitioners from both academia and industry, contributing to the development of advanced algorithms and frameworks. His work has had a significant impact on the academic community, as evidenced by his numerous high-citation publications in top-tier journals and conferences. In addition to his research, Dr. El-Gayar actively participates in academic mentoring, teaching courses, and supervising postgraduate students.

Research Focus :

Dr. Mostafa Mahmoud El-Gayar’s research focus lies at the intersection of Cyber Security, Machine Learning, Internet of Things (IoT), Image Processing, and Computer Vision. His work aims to address some of the most pressing challenges in modern computing, including anomaly detection, phishing attack mitigation, and deep fake video detection. El-Gayar is particularly interested in enhancing the security of IoT networks through the development of robust machine learning-based intrusion detection systems (IDS). He also explores semantic search engines, leveraging advanced algorithms to improve search accuracy and ranking using deep learning techniques. Additionally, El-Gayar is involved in innovative healthcare solutions, such as heart disease prediction using hybrid classifiers and genetic algorithms. His research contributes to safety, privacy, and efficiency across diverse fields, and he continues to push the boundaries of knowledge with his cutting-edge, interdisciplinary research.

Publication Titles :

A Comparative Study of Image Low-Level Feature Extraction Algorithms 📷
HDPF: Heart Disease Prediction Framework Based on Hybrid Classifiers and Genetic Algorithm ❤️🧬
Enhanced Search Engine Using Proposed Framework and Ranking Algorithm Based on Semantic Relations 🔍🔗
Enhancing IoT Botnets Attack Detection Using Machine Learning-IDS and Ensemble Data Preprocessing Technique 📡💻
Efficient Proposed Framework for Semantic Search Engine Using New Semantic Ranking Algorithm 🔎🧠
A Novel Approach for Detecting Deep Fake Videos Using Graph Neural Network 🎥🤖
Resource Allocation in UAV-Enabled NOMA Networks for Enhanced Six-G Communications Systems 🚁📶
Detection Technique and Mitigation Against a Phishing Attack 🔒💻
A Computerized System for SEMG Signals Analysis and Classification 🧠📊
Comparative Study Between Metaheuristic Algorithms for IoT Wireless Nodes Localization 🌐🔍
Semantic Pneumonia Segmentation and Classification for Covid-19 Using Deep Learning Network 🦠💻
Intelligent System for Ranking Big Data in Search Engine 📊🔍
Automatic Generation of Image Caption Based on Semantic Relation Using Deep Visual Attention Prediction 🖼️🧠
A Novel Model for Securing Seals Using Blockchain and Digital Signature Based on QR Codes 🔐📱
A Novel Knowledge-Based Semantic Search Engine 🔍🧠
Smart Collaborative Intrusion Detection System for Securing Vehicular Networks Using Ensemble Machine Learning Model 🚗🛡️
Efficient Real-Time Anomaly Detection in IoT Networks Using One-Class Autoencoder and Deep Neural Network 🖥️💡
Novel Biomarkers for Colorectal Cancer Prediction 🎗️🧬
A Novel Model for Securing Seals Using Blockchain and Digital Signature Based on Quick Response Codes 🔐📲

Menglu Liang | Bayesian methods | Best Researcher Award

Published on 18/01/202518/01/2025 by Popular EngineerLeave a Comment

Dr. Menglu Liang | Bayesian methods | Best Researcher Award

Assistant Professor, University of Maryland, United States

Dr. Menglu Liang is an Assistant Professor of Biostatistics at the University of Maryland, with a strong background in biostatistics, epidemiology, and public health. Her journey into the field of biostatistics began during her studies at Johns Hopkins University, where she first encountered survival analysis in large cohort studies. Dr. Liang’s academic and research career has focused on developing advanced statistical models for real-world health challenges, particularly in the areas of cardiovascular disease, cancer, and public health. She has received extensive training at prestigious institutions, including Beijing University of Chinese Medicine, Peking University, Johns Hopkins University, the University of Minnesota, and Penn State University. Her work has resulted in numerous impactful publications in top-tier journals, and she is highly regarded for her interdisciplinary collaborations with clinicians, epidemiologists, and statisticians to address pressing health issues.

Profile

Education

Dr. Menglu Liang completed her undergraduate studies in Preventive Medicine at Beijing University of Chinese Medicine, graduating in 2011. She further pursued a Master’s degree in Public Health (MPH) from Peking University, Beijing, in 2014. Her passion for applying statistical methods in public health led her to Johns Hopkins University, where she earned a Master of Science in Epidemiology in 2016. Dr. Liang’s academic path continued with a Master of Science in Statistics from the University of Minnesota in 2019, and she earned her PhD in Biostatistics from Penn State University in 2023. Her doctoral research, titled “Modeling and Dynamic Prediction for Recurrent Time-to-event Data with Competing Risks,” focused on advanced Bayesian techniques for survival analysis and statistical modeling. Dr. Liang’s education across multiple disciplines and prestigious institutions has provided her with a comprehensive foundation in biostatistics, epidemiology, and public health.

Experience

Dr. Menglu Liang has built an impressive academic and professional career, culminating in her current position as an Assistant Clinical Professor of Biostatistics at the University of Maryland. Prior to this, she gained invaluable experience as a Graduate Assistant at Penn State University (2019–2023) and the University of Minnesota (2018–2019), where she developed advanced statistical models and conducted research on cardiovascular disease and clinical epidemiology. Dr. Liang’s early career included roles at Johns Hopkins University, where she worked as a Data Analyst (2016–2017) and a Graduate Assistant (2015–2016), contributing to significant research in epidemiology and biostatistics. Throughout her career, she has demonstrated a commitment to collaborative research and statistical consulting, working closely with clinicians and researchers to tackle complex health issues. Dr. Liang has also served as a mentor to students and researchers, providing guidance in statistical modeling, data analysis, and scientific writing.

Awards and Honors

Dr. Menglu Liang has received numerous awards and honors that recognize her outstanding contributions to biostatistics and public health research. In 2022, she was awarded the prestigious Travel Award by the International Chinese Statistical Association, highlighting her commitment to advancing statistical methods in health research. She was also the recipient of the Statistical Significance Award in the JSM Statistical Significance Competition, which acknowledges innovative research in statistical methodology. Dr. Liang’s scholarly achievements have been recognized through her publications in top-tier journals, where her work on dynamic prediction models and Bayesian statistical methods has garnered significant attention. She has presented her research at various national and international conferences, demonstrating her leadership in advancing the application of statistical techniques to public health and clinical research. Her consistent recognition underscores her academic excellence and her ability to contribute to high-impact research in the field.

Research Focus

Dr. Menglu Liang’s research focuses on the application of advanced statistical methods to public health, epidemiology, and clinical research. Her primary areas of interest include survival analysis, Bayesian hierarchical modeling, and the development of dynamic prediction models for recurrent time-to-event data with competing risks. Her work often integrates complex statistical methods with real-world data to address key health challenges, particularly in cardiovascular disease, cancer, and public health policy. Dr. Liang is particularly interested in the intersection of statistical modeling and clinical research, where she collaborates with clinicians and epidemiologists to improve predictive models and decision-making processes. She has also applied Bayesian network meta-analysis techniques in dental research and developed spatial-temporal models to study the effects of extreme heat on health outcomes. Dr. Liang’s research is driven by the goal of making meaningful contributions to public health through the application of innovative statistical techniques to real-world problems.

Publication Top Notes

Association of a Biomarker of Glucose Peaks, 1,5-Anhydroglucitol, With Subclinical Cardiovascular Disease 🩺📊
Tackling Dynamic Prediction of Death in Patients with Recurrent Cardiovascular Events 💓🔍
Bayesian Network Meta-Analysis of Multiple Outcomes in Dental Research 🦷📈
A Spatial-Temporal Bayesian Model for Case-Crossover Design with Application to Extreme Heat and Claims Data 🌡️📉

Jinxu Yang | Power electronics | Best Researcher Award

Published on 17/01/202517/01/2025 by Popular EngineerLeave a Comment

Dr. Jinxu Yang | Power electronics | Best Researcher Award

postdoctoral, ZJU-Hangzhou Global Scientific and Technological Innovation Center, China

Jinxu Yang is a Postdoctoral researcher at the ZJU-Hangzhou Global Scientific and Technological Innovation Center in Hangzhou, Zhejiang Province. He completed his bachelor’s degree at Shandong University in 2014 and earned his PhD in Electrical Engineering from Zhejiang University in 2022. With a robust academic foundation, he is at the forefront of power electronics research, particularly focusing on the optimization of high-frequency resonant converters and the design of high-efficiency magnetic components. Throughout his career, he has made notable contributions to both theoretical and applied aspects of power electronics, evidenced by numerous published articles and patents. His work bridges the gap between academia and industry, collaborating on national R&D projects, including those related to high-performance power supplies, energy storage systems, and on-board chargers. Jinxu Yang is recognized for his innovative approach and continues to push the boundaries of power electronics technology.

Profile

Google Scholar

Education

Jinxu Yang pursued his higher education in Electrical Engineering, beginning with a bachelor’s degree from Shandong University, which he completed in 2014. During his time at Shandong University, Jinxu laid the groundwork for his deep interest in power electronics. He went on to earn his PhD from Zhejiang University in 2022, where he specialized in the optimization of high-frequency resonant converters and the design of magnetic components. His doctoral research focused on enhancing power electronics systems by addressing critical issues such as size reduction, efficiency improvement, and the mitigation of leakage magnetic fields in magnetic integration. His academic journey was marked by a combination of rigorous theoretical learning and practical research applications, preparing him to become an active contributor to advancements in the field of power electronics. Today, as a postdoctoral researcher, he continues to build on his academic foundation to push forward innovative solutions in this area.

Experience

Jinxu Yang has accumulated significant experience in the field of power electronics, particularly focusing on high-frequency resonant converters and magnetic integration. After completing his PhD at Zhejiang University in 2022, he joined the ZJU-Hangzhou Global Scientific and Technological Innovation Center as a postdoctoral researcher. His involvement in major national R&D projects has allowed him to apply his knowledge to real-world solutions, including projects in server power supplies, on-board chargers (OBC), and household energy storage systems. Additionally, Jinxu’s work spans multiple industry-academia collaborations, such as developing a 600W communication power supply and a 6.6kW OBC power supply. His consultancy experience further expands his impact, advising on high-performance power supply systems. With 13 journal publications, 5 patents, and significant participation in international conferences, his contributions are well recognized in the scientific community. His career reflects a commitment to both innovation and practical, scalable solutions in the power electronics sector.

Research Focus

Jinxu Yang’s research primarily focuses on optimizing high-frequency resonant converters in power electronics, with particular attention to magnetic components and integration techniques. He has made significant advancements in improving the efficiency, size, and performance of power conversion systems, while addressing challenges such as leakage magnetic fields. His work in power electronics spans multiple areas, including topology and control optimization, high-frequency operation, and the design of magnetic components that enhance system efficiency. Through the development of novel integration methods, Jinxu has been able to reduce the size of magnetic components without sacrificing performance, creating solutions that are both compact and highly efficient. Additionally, his research explores advanced control schemes to optimize the operation of power converters, such as zero-voltage switching (ZVS) and soft switching techniques. By focusing on high-frequency resonant converters and their integration with magnetic components, Jinxu is contributing to the evolution of power supply technology, particularly for applications in energy storage, communications, and automotive sectors.

Publications Top Notes

A simplified real-time digital control scheme for ZVS four-switch buck–boost with low inductor current
External magnetic field minimization for the integrated magnetics in series resonant converter
A novel ZVS Control Scheme for Four-Switch Resonance Inverting bidirectional buck-boost DC/DC Converter for 5G-RF Power Amplifier
Suppressing methods of common-mode noise in LLC resonant DC-DC converters
Modeling and design of integrated inductor and transformer considering superposed flux density in on-board-charger
Linearized ZVS control scheme of a resonant four-switch buck-boost DC/DC converter for inverting voltage solution applications
Soft switching control for a resonant four-switch inverting buck-boost DC/DC converter with wide voltage range
High Density Planar Integrated Magnetics with Two-sided Merged Inductor Windings and Integrated Cores for Resonant DC/DC Converter
High Density Planar Integrated Magnetics with Two-sided Merged Inductor Windings and Cores for Resonant DC/DC Converter
Analysis and design considerations for an improved BCM buck AC-DC LED driver with high output voltage and low total harmonic distortion

Joao Proenca | Sustainability | Excellence in Research

Published on 17/01/202517/01/2025 by Popular EngineerLeave a Comment

Prof. Dr. Joao Proenca | Sustainability | Excellence in Research

Full Professor, University of Porto, Portugal.

João F. Proença, born in Coimbra, Portugal, on April 21, 1963, is a renowned Full Professor at the University of Porto’s School of Economics and Management. He is also the President of the Scientific Department of Business and Management at the University of Porto. Proença’s career spans academia and business leadership, with past roles including Rector of Universidade Europeia and Chief Academic Officer for Laureate International Universities in Portugal. He has held several leadership positions, such as Dean of the School of Economics and Management at the University of Porto. Proença has published over 150 research papers and has been a Visiting Researcher at prestigious institutions worldwide. In addition to his academic achievements, he has also led business operations as CEO and Chairman in various commercial and industrial firms, contributing to both the academic and business communities. He specializes in Marketing, Business Management, and Services Management.

Profile :

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Education :

João F. Proença’s academic journey began with a Bachelor’s in Business and Management Studies from Universidade Católica Portuguesa, Lisbon (1986). He then earned a Master’s in Marketing and Commercial Management from IE Business School in Madrid, Spain (1991), graduating second in his class. Proença further advanced his studies with a PhD in Business Studies from the University of Porto (1999), receiving unanimous approval for his dissertation. He later achieved the title of “Agregação” in Business Studies from the same institution in 2008, a required qualification for a full professor role in Portugal. His educational achievements have laid the foundation for his successful academic career and extensive research in business and management. Proença is committed to fostering excellence in education and research, mentoring students and scholars globally. His academic background plays a pivotal role in shaping his contributions to higher education, business practices, and management studies.

Experience :

João F. Proença boasts an extensive career in both academia and business leadership. As a Full Professor at the University of Porto’s School of Economics and Management, he has held key academic positions, including Director of multiple degree programs and Chairman of the Scientific Board. He was the Dean of the University of Porto’s School of Economics and Management (2010-2015), where he contributed to the institution’s high standing in international rankings. Proença also served as Rector of Universidade Europeia, overseeing multiple campuses, and as Chief Academic Officer for Laureate International Universities in Portugal. In addition to his academic career, Proença has significant business experience, having held executive roles such as CEO and Chairman at companies within the Probos Group, now part of H.B. Fuller. His leadership in business and education has shaped his approach to management and services studies, demonstrating a unique blend of academia and industry expertise.

Research Focus :

João F. Proença’s research primarily revolves around Marketing, Business Management, and Services Management. His work delves into the dynamics of service quality, consumer behavior, and sustainable business practices, with a focus on examining how companies can improve customer relations and operational efficiency. Proença is also interested in the intersection of sustainability and business, particularly in how businesses can integrate sustainable practices into their operations. His research explores innovative service strategies, value co-creation, and the role of business models in promoting long-term sustainability. Additionally, Proença has a particular focus on the influence of technology and digital transformation in services management. He has published numerous articles on service marketing, consumer behavior, and sustainability, contributing valuable insights to the academic community. Proença’s global collaborations and visiting researcher roles at various universities further enrich his research, creating a broader perspective on contemporary challenges in business and management.

Publications:

Sustainable Campus Operations in Higher Education Institutions: A Systematic Literature Review 🌱🎓
The Influence of Perceived Risk on Mobile Shopping Cart Abandonment 📱🛒
How Farmers Present a Sustainable Product to Socially Responsible Consumers—An Approach to Local Organic Agriculture 🌾🌍
The Influence of Service Quality on the Consulting Relationship 🤝💼
The Influence of Sustainability on Psychological Ownership in Services Based on Temporary Access ♻️💡
Determinants of the Purchase of Secondhand Products: An Approach by the Theory of Planned Behaviour 🔄🛍️
Motivations for Peer-to-Peer Accommodation: Exploring Sustainable Choices in Collaborative Consumption 🏠🤝
Sustainability in the Coffee Supply Chain and Purchasing Policies: A Case Study Research ☕🌍
The Use of Positive and Negative Appeals in Social Advertising: A Content Analysis of Television Ads for Preventing HIV/AIDS 📺⚖️
Tourism Co-Creation in Place Branding: The Role of Local Community 🏞️👥

Samaneh Abdi Qezeljeh | Energy and Sustainability | Best Researcher Award

Published on 17/01/202517/01/2025 by Popular EngineerLeave a Comment

Ms. Samaneh Abdi Qezeljeh | Energy and Sustainability | Best Researcher Award

PhD Researcher, Technische Universität Darmstadt, FG SLA, Germany

Samaneh Abdi Qezeljeh is a passionate researcher in the field of mechanical engineering, currently pursuing her Ph.D. at the Technical University of Darmstadt. With a solid academic background and a CGPA of 17.51/20 in her Master’s studies, she has made notable contributions to fluid mechanics, heat transfer, and energy conservation. Samaneh’s research interests encompass fluid-structure interaction (FSI), computational fluid dynamics (CFD), turbulence, bio-mechanics, and numerical simulations. Throughout her academic career, she has earned recognition for her excellent performance, ranking 5th in her Master’s cohort and 3rd in her Bachelor’s program. Her work has been published in high-impact journals such as Energies and the International Journal of Multiphase Flow. Samaneh is also highly skilled in various engineering software, including Comsol Multiphysics, Ansys-Fluent, and SolidWorks. Alongside her research, she has tutored undergraduate and graduate students at the University of Tabriz.

Profile

Education

Samaneh Abdi Qezeljeh obtained her Bachelor’s degree in Mechanical Engineering from Seraj Higher Education Institute, Tabriz, Iran, where she ranked 3rd in her class. She excelled academically with a CGPA of 17.63/20 (excluding thesis) and earned a thesis grade of 19.75/20. Her thesis focused on Incompressible Flow Simulation in a Backward-Facing Step with an Elastic Wall, highlighting her expertise in computational fluid dynamics (CFD). Samaneh continued her academic journey by pursuing a Master of Science (M.Sc.) in Mechanical Engineering with a focus on Energy Conservation at the University of Tabriz, where she achieved a CGPA of 17.51/20. Her Master’s thesis, titled “Investigation of Different Fluids on the Performance of Organic Rankine Cycle with and Without Preheater,” reflects her research interests in energy systems. Currently, she is enrolled in the Ph.D. program at Technical University of Darmstadt, focusing on fluid mechanics and thermal load peak treatment.

Experience

Samaneh Abdi Qezeljeh has gained valuable practical experience through her internship at I.D.E.M Co. (Iranian Diesel Engine Manufacturing Co.), where she worked in the Research and Development (R&D) department from July to August 2017. During this internship, Samaneh was involved in the design and modification of engines, particularly focusing on optimizing engine performance. This hands-on experience enhanced her understanding of real-world mechanical engineering challenges and deepened her knowledge of energy systems. In her academic career, Samaneh has contributed to the advancement of fluid mechanics and energy conservation research at the Technical University of Darmstadt. As a Ph.D. student, she is currently working on the study of thermal load peak treatment in turbulent aerosol flows. She has also tutored undergraduate and graduate students at the University of Tabriz, focusing on SolidWorks and CFD software, sharing her expertise and mentoring future engineers.

Research Focus

Samaneh Abdi Qezeljeh’s research focuses primarily on fluid mechanics, heat transfer, and energy systems, with a particular emphasis on computational fluid dynamics (CFD) and fluid-structure interaction (FSI). Her work also explores bio-mechanics, turbulence modeling, and numerical simulations to address real-world engineering problems. As a Ph.D. candidate at the Institute for Fluid Mechanics and Aerodynamics at Technical University of Darmstadt, Samaneh’s current research project, titled “Study of Thermal Load Peak Treatment in the Air Gap Utilizing Turbulent Aerosol Flows”, is investigating ways to optimize thermal performance in energy systems. Her previous work on the Organic Rankine Cycle has further solidified her interest in energy conservation techniques and sustainable energy solutions. Samaneh has also studied incompressible fluid flows in her Master’s thesis and has explored advanced fluid simulations, focusing on the interaction between fluids and structural elements.

Publication Top Notes

José Maria Rodrigues da Luz | Fermentation and Sensory Analysis | Outstanding Scientist Award

Published on 17/01/202517/01/2025 by Popular EngineerLeave a Comment

Dr. José Maria Rodrigues da Luz | Fermentation and Sensory Analysis |Outstanding Scientist Award

Postdoctorate, FEDERAL UNIVERSITY OF VIÇOSA, Brazil

José Maria Rodrigues da Luz is a distinguished Brazilian biochemist, microbiologist, and researcher. He holds a Ph.D. in Agricultural Microbiology from Universidade Federal de Viçosa (UFV), Brazil, and currently holds a postdoctoral position at the same institution. With an extensive academic background, José Maria has contributed significantly to the fields of biochemistry and microbiology, focusing on fungi, mycorrhizal interactions, and biotechnological applications. His work in microbiology and biochemistry has garnered international recognition. He has also held teaching positions at Universidade Federal de Alagoas and Instituto Federal de Educação, Ciência e Tecnologia. His research interests center around environmental sustainability, such as utilizing fungi for biodegradation and waste management. Furthermore, his expertise extends to agricultural applications, including the development of biotechnological processes for enhancing coffee and mushroom production.

Profile

Scopus
Orcid

Education

José Maria Rodrigues da Luz has a robust academic foundation in Biological Sciences. He completed his undergraduate degree in Biochemistry from Universidade Federal de Viçosa (UFV), Brazil, in 2007. He went on to earn a Master’s and Ph.D. in Agricultural Microbiology at UFV, under the mentorship of Maria Catarina Megumi Kasuya. His Ph.D. research, which earned him a grant from the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), delved into the biodegradation of plastics and lignocellulolytic enzymes, with a focus on developing sustainable agricultural solutions. In addition to his primary education, José Maria pursued postdoctoral studies at UFV, expanding his research on fermentation processes and microbiology applications in agriculture, environmental sustainability, and biotechnology. These postdoctoral opportunities were funded by prominent agencies like CAPES and CNPq, reflecting his continued commitment to advancing knowledge in his field.

Experience

José Maria Rodrigues da Luz has amassed a wealth of experience in both academia and research. His professional career includes roles at Universidade Federal de Alagoas (UFAL), where he worked as a visiting professor, imparting knowledge in fields such as agroecology, biochemistry, and microbiology. Additionally, he has contributed significantly to research projects at UFV, focusing on areas such as fungal biotechnology, biodegradation, and environmental sustainability. He has been involved in several research projects exploring the potential of fungi, such as Pleurotus ostreatus, for waste management and agricultural applications. Furthermore, José Maria has collaborated on projects examining microbial diversity in coffee production and the biotechnological processes involved. His extensive research output and involvement in teaching have cemented his reputation as an expert in his field. He has also held managerial positions at TecnMol, a civil association in biochemistry, further diversifying his experience in the scientific community.

Research Focus

José Maria Rodrigues da Luz’s research focuses on the intersection of biochemistry, microbiology, and environmental sustainability. His primary areas of interest include the use of fungi, such as Pleurotus ostreatus and Pisolithus, in the degradation of waste, particularly plastic materials and agricultural residues. His work emphasizes the application of lignocellulolytic enzymes and the biotechnological potential of mycorrhizal fungi in improving agricultural sustainability. Additionally, he is involved in the fermentation processes of coffee, exploring the microbial communities and their role in enhancing the sensory quality of the coffee beverage. José Maria’s research also covers the bioactivity of compounds like ergosterol and β-glucan produced by fungi, as well as the development of green polymers from lignocellulosic materials. His work in sustainable waste management, biodegradation, and improving food and agricultural production underscores his commitment to finding innovative solutions to global environmental and agricultural challenges.

Publication

Genetic diversity of the fungal community that contributes to the sensory quality of coffee beverage after carbonic maceration and fermentation 🍄☕
Intestinal microbial diversity of swines fed with different sources of lithium 🐖🔬
Arbuscular mycorrhizal fungi community in coffee cultivation under different agroforestry management systems in the Maciço de Baturité region, Brazil 🌱🌍
Mid-infrared spectroscopy and physicochemical analyses in the characterization of coffee roasting stages 🔬☕
Chemical and sensorial profile of Coffea arabica cultivars fermented by different post-harvest processing methods ☕🔬
Production of milk-coagulating protease by fungus Pleurotus djamor through solid-state fermentation using wheat bran as the low-cost substrate 🍄🧀
Diversity of potential nitrogen-fixing bacteria from rhizosphere of Coffea arabica L. and Coffea canephora L. 🌱🔬
Production, characterization, and application of a new chymotrypsin-like protease from Pycnoporus sanguineus 🍄💧
Bacterial community and sensory quality from coffee are affected along fermentation under carbonic maceration 🍵🍄
Lentinula edodes lignocellulolases and lipases produced in Macaúba residue and use of the enzymatic extract in the degradation of textile dyes 🍄🌿

Anatolij Prykarpatski | supersymmetric models of quantum physics | Excellence Award (Any Scientific field)

Published on 17/01/202517/01/2025 by Popular EngineerLeave a Comment

Prof. Dr. Anatolij Prykarpatski | supersymmetric models of quantum physics | Excellence Award (Any Scientific field)

Prof. Dr. Anatolij Prykarpatski, Lviv Polytechnic National University, Ukraine

Anatolij K. Prykarpatsky is a prominent Ukrainian mathematician and physicist, specializing in mathematical physics. He holds a Ph.D. and Habilitation degree in Mathematics and Physics. With a distinguished career as a full professor at Lviv Polytechnic National University in Ukraine, he has contributed extensively to applied mathematics, mathematical physics, and dynamical systems. Prof. Prykarpatsky has been a visiting professor at renowned institutions like the New Jersey Institute of Technology (USA), Massachusetts Institute of Technology (MIT), and Hacettepe University (Turkey). His work spans differential equations, algebraic methods, quantum mathematics, and nonlinear dynamical systems. Fluent in several languages, including English, Polish, and Russian, his contributions are recognized globally, having collaborated with researchers across Europe, the USA, and Russia. His dedication to teaching and research makes him a respected figure in the field of mathematical physics.

Profile :

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Education :

Anatolij K. Prykarpatsky earned his Master’s degree in Physics from Ivan Franko Lviv State University in 1975. He later pursued a graduate program in Mathematical Physics at the Institute of Mathematics of the National Academy of Sciences of Ukraine, where he completed his Ph.D. in 1980. His dissertation focused on the integrability of ordinary Riccati and partial differential equations in mathematical physics. In 1987, he received his Habilitation degree, with a thesis on nonlinear dynamical systems of statistical and mathematical physics. His academic journey was further enriched through research at the Laboratory of Theoretical Physics at the Joint Institute for Nuclear Research in Dubna, Russia. Prof. Prykarpatsky’s advanced studies have shaped his multidisciplinary expertise in mathematics and physics, enabling him to explore complex systems and contribute significantly to scientific advancements in various fields, including quantum mathematics and dynamical systems.

Experience :

Prof. Anatolij K. Prykarpatsky has a distinguished academic career, serving as a full professor in the Department of Computational Mathematics at Lviv Polytechnic National University, Ukraine, since 1995. His international experience includes multiple visits as a professor to prestigious institutions such as the New Jersey Institute of Technology (USA), Massachusetts Institute of Technology (MIT), and Hacettepe University (Turkey). His teaching expertise covers a range of courses in mathematical physics, dynamical systems, algebra, and operator theory. He has advised numerous graduate and Ph.D. students across Europe, Ukraine, and Russia. His involvement in various international collaborations, alongside his extensive research background, has earned him a reputation as a leading figure in his field. Throughout his career, Prof. Prykarpatsky has made significant contributions to the development of mathematical theories and applied methodologies, particularly in nonlinear dynamics and quantum mathematics, establishing a solid academic legacy.

Awards and Honors :

Anatolij K. Prykarpatsky has received several prestigious awards in recognition of his groundbreaking work in mathematics and physics. In 1982, he was honored with a Diploma from the National Academy of Sciences (NAS) in Mathematical Physics, Kyiv. He received the Ostrovsky Republican Award in Science and Technology in 1984. In 2003, he was awarded the Silver Order “For the Service” by the President of the Polish Republic. Prof. Prykarpatsky’s scientific excellence was further recognized by the Western Scientific Centre of NAS of Ukraine in 2003. In 2009, he received the N. Bogolubov Award in Statistical and Mathematical Physics from NAS Ukraine. In 2019, he was awarded the prestigious State Prize in Science and Technology of Ukraine. These accolades reflect his significant contributions to the advancement of scientific knowledge, particularly in the fields of nonlinear dynamical systems, mathematical physics, and quantum mathematics.

Research Focus :

Prof. Anatolij K. Prykarpatsky’s research focuses on a wide range of topics within mathematical physics, emphasizing nonlinear dynamical systems, quantum mathematics, and differential geometric methods. His work in dynamical systems theory explores the mathematical properties and integrability of complex systems, particularly through functional-operator methods. He also investigates the role of algebraic structures in mathematical physics, with particular interest in Lie groups and algebras. His exploration of quantum mathematics in computer science has led to contributions in the areas of quantum deformations, statistical physics, and integrable Hamiltonian systems. Prof. Prykarpatsky’s research also extends into applied mathematics, including operator theory, ergodic theory, and mathematical analysis. His approach combines rigorous mathematical frameworks with practical applications, making significant strides in understanding the behavior of physical systems. His recent work has explored the supersymmetry of integrable systems, conformal Lie superalgebras, and related quantum mechanical structures.

Publications Titles with Emojis:

On Superization of Nonlinear Integrable Dynamical Systems 📊🔬
Some Remarks on the Inverse Problem in the Variational Calculus 🧩📐
On Superization of Nonlinear Integrable Dynamical Systems (Preprint) 🔄💡
Supersymmetric Integrable Hamiltonian Systems and Their Factorized Semi-Supersymmetric Generalizations 🌀🔒
On Some Aspects of the Courant-Type Algebroids and Integrable Systems ⚙️📚
On the Quantum Deformations of Associative Sato Grassmannian Algebras 🧪🧬
Раціональна факторизація гамільтонових потоків 🔬🌐
Symplectic Geometry Aspects of the Kardar–Parisi–Zhang Equation 🏛️🌪️
Special Issue Editorial “Symmetry of Hamiltonian Systems” 📘📈
Dark Type Dynamical Systems: The Integrability Algorithm 🌑🧮
Quantum Current Algebra in Action 🔮⚡
Entropy and Ergodicity of Boole-Type Transformations 🔄📉
On the Finite Dimensionality of Closed Subspaces 🔢📐
On the Bogolubov’s Chain of Kinetic Equations 🔗📉
Quantum Current Algebra Symmetry and Description of Kinetic Equations 🧬💥

Abdulkafi Mohammed Saeed | Mathematics | Best Researcher Award

Published on 17/01/202517/01/2025 by Popular EngineerLeave a Comment

Prof. Dr. Abdulkafi Mohammed Saeed | Mathematics | Best Researcher Award

Director of the Postgraduate Program in the Mathematics Department at Qassim University, Qassim University, Saudi Arabia

Prof. Dr. Abdulkafi Mohammed Saeed is a highly experienced professor of Applied Mathematics at Qassim University, Saudi Arabia, with a research focus on Numerical Partial Differential Equations, Fluid Dynamics, and Fractional Calculus. He earned his Ph.D. in Applied Mathematics from Universiti Sains Malaysia and has over 15 years of teaching experience. Prof. Saeed has published more than 130 papers in leading international journals, contributed to various research conferences, and collaborated extensively with global researchers. Additionally, he has expertise in academic quality management and accreditation, having been involved in the quality assurance processes of several mathematics programs. Prof. Saeed also offers his services as a reviewer for numerous reputable journals, making significant contributions to the academic community. He is proficient in multiple languages and programming tools, including MATLAB and C++.

Profile

Education

Prof. Dr. Abdulkafi Mohammed Saeed holds a Ph.D. in Applied Mathematics from Universiti Sains Malaysia (2011), focusing on Partial Differential Equations. He completed his Master’s degree in Applied Mathematics from Hyderabad Central University in India (2005) and obtained his Bachelor’s degree in Mathematics, Physics, and Computer Science from Hodeidah University, Yemen (1998). His educational background laid the foundation for his expertise in applied mathematics, particularly in differential equations, fluid dynamics, numerical analysis, and computational methods. Prof. Saeed’s academic journey also includes significant post-doctoral work at the University of Sciences Malaysia, further enhancing his research capabilities. He has continued to develop his academic career through his teaching roles and extensive research contributions in the field.

Experience

Prof. Dr. Abdulkafi Mohammed Saeed has over 15 years of experience in academia, particularly in teaching and research in Applied Mathematics. He has taught a wide range of undergraduate and postgraduate courses in differential equations, numerical analysis, fluid dynamics, and computational mathematics at Qassim University, Saudi Arabia. In addition to his teaching role, he holds several leadership positions, such as Head of Quality Assurance at Qassim University’s Department of Mathematics. He has also served as a consultant for the university’s quality unit and been involved in program development, ensuring academic excellence in mathematics education. Prof. Saeed has been a reviewer for numerous prestigious journals and a member of editorial boards. His post-doctoral research at Universiti Sains Malaysia and his early academic career in Yemen also contribute to his broad and diverse experience in the field.

Awards and Honors

Prof. Dr. Abdulkafi Mohammed Saeed has received numerous awards and recognitions for his academic contributions. He was awarded scholarships by the Government of Yemen for his Master’s and Ph.D. studies at Hodeidah University and Universiti Sains Malaysia. Prof. Saeed’s research excellence earned him the “Hadiah Sanggar Sanjung” award in 2011 and 2012 for publishing impactful articles in ISI journals. He also won the third prize in the 1st Postgraduate Quran Recitation Competition at Universiti Sains Malaysia in 2010. These honors reflect his exceptional academic achievements and contributions to the field of applied mathematics. Additionally, Prof. Saeed’s work has been recognized by multiple academic organizations, contributing to his reputation as a leader in the mathematics community.

Research Focus

Prof. Dr. Abdulkafi Mohammed Saeed’s research primarily focuses on Applied Mathematics, with a particular emphasis on Partial Differential Equations (PDEs), Fluid Dynamics, and Fractional Calculus. His work spans numerical modeling, applied and computational mathematics, and the use of functional analysis to solve complex mathematical problems. Prof. Saeed has made significant contributions to the understanding of fluid flow, thermoelasticity, and mathematical computing. His research also includes investigating fractional PDEs and their real-world applications. He has published over 130 papers in international journals and has collaborated with numerous global researchers. Prof. Saeed’s interest in mathematical modeling and numerical methods has driven advancements in computational techniques, particularly in areas related to fluid dynamics and thermoelasticity. He continues to explore new mathematical approaches and models to address complex phenomena in science and engineering.

Publications (Single-line format with emojis):

“Analysis of the Thomson and Troian velocity slip for the flow of ternary nanofluid past a stretching sheet” 🧑‍🔬📑
“Thermophoretic particle deposition effect on a squeezed flow of radiative Jeffrey fluid past a sensor surface with uniform heat source/sink and chemical reaction” 🔬💧
“The series solutions of fractional foam drainage and fractional modified regularized long wave problems” 📚🌊
“A new solution of the nonlinear fractional logistic differential equations utilizing efficient techniques” 🔢📈
“Bioconvective Hybrid Flow with Microorganisms Migration and Buongiorno’s Model under Convective Condition” 🌱💨
“Significance of Hall current and Ion slip in a three-dimensional Maxwell nanofluid flow over rotating disk with variable characteristics and gyrotactic microorganisms” 🔄💡
“Comparative study of hybrid nanofluid flows over a bidirectional stretched surface with the impact of Hall current and ion slip” 🔬⚡
“Model-based comparison of hybrid nanofluid Darcy-Forchheimer flow subject to quadratic convection and frictional heating with multiple slip conditions” 🖥️🌡️
“Wall jet nanofluid flow with thermal energy and radiation in the presence of power-law” 💨☀️
“Buckling and dynamic behavior of uniform and tapered woven carbon/jute fiber reinforced polyester hybrid composite beams” 🌍🔧

Claudia Torresi | Virology | Women Researcher Award

Published on 17/01/202517/01/2025 by Popular EngineerLeave a Comment

Ms. Claudia Torresi | Virology | Women Researcher Award

Laboratory Technician, Experimental Zooprophylactic Institute of Umbria and Marche “Togo Rosati”, Italy

Claudia Torresi is an accomplished virologist with a focus on infectious diseases in animals. With extensive experience in diagnostic and molecular research, she works at the Istituto Zooprofilattico Sperimentale dell’Umbria e delle Marche (IZSUM) as a Collaboratore Tecnico Professionale. Specializing in the genetic analysis of viral diseases like African Swine Fever, Pestivirus, and Bovine Retrovirus, Claudia has contributed to numerous research projects and publications. Her work is pivotal in the epidemiology and diagnosis of viral infections in livestock, particularly in the context of the African Swine Fever crisis in Italy. Over the years, Claudia has collaborated on studies that explore the genetic diversity of viruses and their transmission dynamics, providing crucial insights for veterinary public health. Her passion for advancing molecular biology techniques in virology has earned her recognition within the scientific community.

Profile

Orcid

Education

Claudia Torresi holds a Master’s degree in Public Veterinary Health and Food Hygiene from the University of Perugia (2011–2012). She also completed her Master’s in Agricultural and Environmental Biotechnology at the University of Perugia, graduating with honors (2006–2008). Earlier, she completed a Bachelor’s degree in Biotechnology (2003–2006), focusing on agricultural biotechnology. Claudia’s academic journey is complemented by international exposure, including a study visit to the National Veterinary Institute in Uppsala, Sweden, for a fellowship in 2014, where she gained expertise in applying Next Generation Sequencing (NGS) technologies to the study of African Swine Fever virus. Her advanced education and research training have provided her with a strong foundation in molecular biology, virology, and epidemiology, which she continuously applies in her professional career.

Experience

Claudia Torresi has been working at the Istituto Zooprofilattico Sperimentale dell’Umbria e delle Marche (IZSUM) since 2009, initially as a research assistant and later as a Collaboratore Tecnico Professionale. Over the years, her research has focused on animal viral diseases, particularly African Swine Fever, Pestivirus, and Bovine Retrovirus. Claudia’s main responsibilities include conducting diagnostic activities using molecular biology techniques and engaging in research to better understand the genetic diversity and evolution of these viruses. She has been actively involved in projects aimed at enhancing diagnostic tools, providing epidemiological support during outbreaks, and applying bioinformatics to virus genomics. Additionally, Claudia has contributed significantly to the understanding of African Swine Fever’s persistence in traditional Italian cured meat products. Her work has garnered recognition, especially for its impact on improving disease control strategies in veterinary medicine.

Research Focus

Claudia Torresi’s research focuses on the molecular epidemiology, genetic characterization, and evolution of viral diseases that affect livestock, particularly African Swine Fever (ASF), Pestivirus, and Retroviruses. Her work extensively uses Next Generation Sequencing (NGS) technologies to explore the genetic diversity of these viruses, with an emphasis on tracking virus strains and understanding their mutation patterns. She has been instrumental in studying the survival of ASF virus in cured meats and investigating the virus’s genetic makeup in Italy. Claudia also contributes to the study of zoonotic diseases and the genetic variability of viruses like Bovine Kobuvirus and Border Disease Virus, which are critical for understanding their transmission dynamics and developing effective diagnostic and control strategies. Her research aims to improve veterinary diagnostics, support epidemiological studies, and help manage viral outbreaks in animal populations, ultimately contributing to better public health outcomes.

Publication Top Notes

Genome-Wide Approach Identifies Natural Large-Fragment Deletion in ASFV Strains Circulating in Italy During 2023 🦠
Genetic Characterization of African Swine Fever Italian Clusters in the 2022–2023 Epidemic Wave 🐖
Molecular Detection and Genetic Characterization of Bovine Kobuvirus (BKV) in Diarrhoeic Calves 🐄
Genomic Epidemiology and Heterogeneity of SRLV in Italy from 1998 to 2019 🔬
First Genomic Evidence of Dual African Swine Fever Virus Infection in Sardinia 🦠
The evolution of African swine fever virus in Sardinia (1978 to 2014) 🌍
Survival of African swine fever virus (ASFV) in various traditional Italian dry-cured meat products 🧀
Complete Genome Sequence of an African Swine Fever Virus Isolate from Sardinia 🐖
Characterization of a novel full-length bovine endogenous retrovirus, BERV-β1 🦠
Genetic characterization of border disease virus (BDV) isolates from small ruminants in Italy 🐑

Donovan Birky | Interpretable Machine Learning for Material Modeling | Best Researcher Award

Published on 17/01/202517/01/2025 by Popular EngineerLeave a Comment

Mr. Donovan Birky | Interpretable Machine Learning for Material Modeling | Best Researcher Award

Graduate Research Assistant , University of Utah ,United States

Donovan Birky is a PhD candidate in Mechanical Engineering at the University of Utah, with a passion for applying computational techniques and machine learning to solve complex material modeling problems. His expertise spans finite element simulation, machine learning for constitutive model development, uncertainty quantification, and high-performance computing. He has contributed to innovative research in areas like plasticity modeling, microstructure-sensitive damage models, and uncertainty analysis. Birky has collaborated with prominent institutions like Sandia National Labs, where he worked on material damage models and neural networks for material science applications. His work has resulted in multiple impactful publications in renowned journals and conferences. Outside of research, Birky has excelled academically, earning recognition such as the Rhode Baker Most Outstanding Student award and multiple placements on the Dean’s List. His interdisciplinary work bridges material science, engineering, and machine learning, with a focus on real-world applications in industry.

Profile

Education

Donovan Birky is currently pursuing a PhD in Mechanical Engineering at the University of Utah, where he has maintained a GPA of 3.93/4.00 since 2020. In Fall 2022, he received his Master of Science degree in Mechanical Engineering from the same institution. As part of his doctoral research, Birky is a member of the Materials Prognosis from Integrated Modeling and Experiment (M’) Lab, contributing to the development of advanced material damage models using machine learning. Prior to his graduate studies, Birky earned a Bachelor of Science in General Engineering from Fort Lewis College, Durango, CO, graduating with a GPA of 3.92/4.00. During his time at Fort Lewis, he was awarded the Rhode Baker Most Outstanding Student award for Physics and Engineering and was consistently on the Dean’s List. Birky also contributed as a STEM tutor for the TRIO Student Success Center, further demonstrating his dedication to academic excellence.

Experience

Donovan Birky has significant research experience as a Graduate Research Assistant at the University of Utah since 2020, working in the Materials Prognosis from Integrated Modeling and Experiment (M’) Lab. His research focuses on the integration of machine learning with material modeling to develop damage models for advanced materials. His previous internships at Sandia National Laboratories have further refined his skills in computational mechanics and material science. In 2021 and 2022, Birky worked on projects developing grain growth and pore growth datasets, using Sierra finite element codes for machine learning applications. He also contributed to the development of a material model calibration tool. Birky’s research at Fort Lewis College, funded by Sandia National Labs, centered on applying AI and machine learning to solve structural dynamics problems. His work at both academic and research institutions showcases his ability to tackle complex engineering challenges using cutting-edge computational techniques and high-performance computing.

Research Focus

Donovan Birky’s research is centered around computational material modeling and machine learning, with a particular focus on improving the accuracy and interpretability of constitutive models used in material science. His work integrates advanced techniques such as finite element simulation, genetic programming-based symbolic regression (GPSR), and uncertainty quantification to develop more robust models for material damage and plasticity. Birky is also interested in creating microstructure-sensitive deformation models that can better predict material behavior under varying conditions. A key aspect of his research is the application of high-performance computing for running large-scale simulations and training machine learning models, enhancing model reliability and efficiency. His work includes developing yield surface models for porous metals and improving existing damage models, like the Gurson model, through symbolic regression. Birky’s research aims to bridge the gap between fundamental material science and industry, offering tools for product design and certification in real-world engineering applications.

Publications

Predicting the dynamic response of a structure using an artificial neural network 📊💻 (2022)
Complementing a continuum thermodynamic approach to constitutive modeling with symbolic regression 📐🔬 (2023)
Generalizing the Gurson model using symbolic regression and transfer learning to relax inherent assumptions 🔄⚙️ (2023)
Physics-Informed Machine Learning for the Development of Microstructure-Sensitive Deformation and Damage Models 🧬🔍 (2021)
Methods for Generating Interpretable Yield Surface Models With UQ Based on Data With Multiple Sources of Uncertainty 📈📚 (2024)
Interpretability and Generalizability of Constitutive Models using Symbolic Regression 🤖📏 (2024)
Uncertainty Quantification for Interpretable Constitutive Models using Genetic Programming-based Symbolic Regression 🎲💡 (2023)
Interpretable machine learning for uncertain, microstructure-dependent constitutive models 🔍🧪 (2023)
Physics-informed Machine Learning for Development of Interpretable, Improved Material Damage Models 🔬🔧 (2022)
A Data-driven Approach for Improving the Existing Gurson Material Damage Model Using Genetic Programming for Symbolic Regression 📊📉 (2022)
Improved Plasticity and Damage Models By Symbolic Regression of Microscale Finite Element Simulations 🧠📐 (2021)
Efficient Clustering of the Dynamic Response of a Structure Subject to Impulse Loading ⚡📊 (2021)
Learning Implicit Yield Surface Models with Uncertainty Quantification for Noisy Datasets 🌐🔍 (2021)
Applying genetic programming symbolic regression to solid mechanics 🔧🧠