Muhammad Waseem | Econometrics | Young Scientist Award

Posted on 31/05/202531/05/2025 by Research Scientist

Mr Muhammad Waseem | Econometrics | Young Scientist Award

Research Assistant , COMSATS University Islamabad , Pakistan

An enthusiastic 🌱 economics researcher with an M.Phil. in Economics, this individual is passionate about sustainable development, macroeconomic policy, and trade 📈. With hands-on experience in advanced econometric techniques such as GMM, Panel ARDL, and Threshold Models 🧠, they skillfully apply tools like Stata and EViews 💻. Their work focuses on institutional quality, environmental economics 🌍, and policy-making grounded in evidence. Currently pursuing an M.S. in Economics at COMSATS University Islamabad 🎓, they are actively engaged in research training and mentorship, striving to contribute to impactful economic analysis and policy innovation ✍️📊.

Professional Profile

SCOPUS

Education & Experience

🎓 Completed BS Economics from Abdul Wali Khan University Mardan (2019–2023) and currently pursuing an MS in Economics at COMSATS University Islamabad (2023–ongoing). Gained hands-on experience through internships and research assistance roles at PIDE 📚, COMSATS 🏛️, and Habib Bank Limited 🏦. Their roles involved data cleaning, econometric estimation, literature reviews, thesis guidance 📑, and policy analysis. With a strong grip on statistical software such as Stata and EViews 💻, they bring both academic rigor and practical exposure to every research project they contribute to.

Professional Development

📊 As a research assistant under the Ba-Ikhtiyar Nau Jawan Internship Program at COMSATS, this scholar contributed to academic mentoring, econometric analysis, and class presentations. At PIDE, they developed practical expertise in data interpretation, report writing, and policy implications 🧾. Their internship at Habib Bank Limited added financial sector exposure 🏦. These experiences enriched their analytical thinking, problem-solving skills, and communication 📢. By continuously participating in workshops and collaborative research environments, they are committed to evolving as a well-rounded economist and policy contributor 🤝📈.

Research Focus

Their research revolves around panel data analysis 📊, with a focus on international trade, sustainability, and institutional quality 🌍. They explore the dynamic interactions between macroeconomic policy, development economics, and environmental sustainability ♻️. Methodologically, they specialize in GLS, GMM, fixed/random effects, panel cointegration, and threshold models 📉. Their work aims to inform evidence-based policymaking by integrating economic theory with statistical rigor 🧠. Using tools like Stata and EViews 💻, they conduct in-depth analyses that highlight both global and local dimensions of development, trade flows, and governance effectiveness 🔬.

Awards & Honors

🏆 While specific awards were not listed, their consistent academic performance and selection for competitive roles such as research assistantships at PIDE and COMSATS signal recognition of their talent 📚. Being chosen for the Ba-Ikhtiyar Nau Jawan Internship Program reflects trust in their research capability and leadership in economic inquiry 🌟. Their role in mentoring undergraduate students in econometrics and thesis development demonstrates academic excellence 👩‍🏫. Further accolades are anticipated as they continue to contribute to impactful research and policy discussions both nationally and globally 🌐📈.

Publication Top Notes

1. High Removal Efficiency of Arsenite from Aqueous Solution by Cobalt Ferrite Functionalized Sawdust Driven Activated Carbon

Citation:
Naz, H., Khalid, Z., Arif, S., Ahmed, M. N., & Waseem, M. F. (2025). High removal efficiency of arsenite from aqueous solution by cobalt ferrite functionalized sawdust driven activated carbon. Inorganic Chemistry Communications.

Summary:
This study presents a novel approach to arsenite removal from water using activated carbon derived from sawdust, functionalized with cobalt ferrite nanoparticles. The composite material demonstrated high adsorption capacity and efficiency, offering a sustainable solution for arsenic-contaminated water treatment.

2. Highly Ordered and Uniform Growth of Magnetite Nanoparticles on the Surface of Amberlyst-15: Lead Ions Removal Study

Citation:
Gillani, Z., Zain-Ul-Abdin, Khalid, Z., Waseem, M. F., & Haq, S. U. (2024). Highly ordered and uniform growth of magnetite nanoparticles on the surface of Amberlyst-15: Lead ions removal study. Journal of Inorganic and Organometallic Polymers and Materials. https://doi.org/10.1007/s10904-024-03453-1

Summary:
The research focuses on synthesizing magnetite nanoparticles uniformly grown on Amberlyst-15 resin for efficient lead ion removal from aqueous solutions. The composite material exhibited enhanced adsorption properties, making it a promising candidate for water purification applications.

3. Enhanced Role of Flower Shaped Curcumin Loaded ZnO/Ag₂O Nanocomposites for Biological Applications

Citation:
Mukhtar, A., Aruge, S., Tariq, A., Haq, S. U., & Waseem, M. F. (2025). Enhanced role of flower shaped curcumin loaded ZnO/Ag₂O nanocomposites for biological applications. BioNanoScience.

Summary:
This study explores the synthesis of flower-shaped ZnO/Ag₂O nanocomposites loaded with curcumin, aiming to enhance their biological activities. The nanocomposites demonstrated significant antimicrobial and anticancer properties, suggesting their potential in biomedical applications.

4. **Role of Co and Ni Ferrites in the Fabrication of Saccharum officinarum Bioadsorbents for Removing As(III)**

Citation:
Sattar, A., Hussain, S. I., Bibi, F., Iqbal, N., & Waseem, M. F. (2025). Role of Co and Ni ferrites in the fabrication of Saccharum officinarum bioadsorbents for removing As(III). Separation and Purification Technology.

Summary:
The research investigates the incorporation of cobalt and nickel ferrites into Saccharum officinarum (sugarcane) based bioadsorbents for arsenic (As(III)) removal. The modified bioadsorbents showed improved adsorption capacities, offering an eco-friendly solution for arsenic remediation.

5. **Green Hydrothermal Synthesis of Nickel and Zinc-Doped Nickel Ferrite Nanoparticles Using Dalbergiella welwitschii Extracts and Their Biological Studies**

Citation:
Modupe, O. U., Olatunde, S. O., Waseem, M. F., Alsaiari, A. A. A., & Razzokov, J. (2024). Green hydrothermal synthesis of nickel and zinc-doped nickel ferrite nanoparticles using Dalbergiella welwitschii extracts and their biological studies. Heliyon, 11(1), e40759. https://doi.org/10.1016/j.heliyon.2024.e40759

Summary:
This study reports the green synthesis of nickel and zinc-doped nickel ferrite nanoparticles using Dalbergiella welwitschii extracts. The nanoparticles exhibited significant anticancer and antidiabetic activities, highlighting their potential in biomedical applications.

6. **Effective Remediation of Organic Pollutant Using Musa acuminata Peel Extract-Assisted Iron Oxide Nanoparticles**

Citation:
Hedfi, A., Ben-Ali, M. J., Haq, S. U., Razzokov, J., Rehman, W., Waseem, M. F., Elmnasri, K., Hossain, M. K., Rehman, F. U., Karimbaev, E. K., & Shujaat, S. (2025). Effective remediation of organic pollutant using Musa acuminata peel extract-assisted iron oxide nanoparticles. Open Chemistry, 23(1), 132–145. https://doi.org/10.1515/chem-2025-0132

Summary:
The research presents a green synthesis of iron oxide nanoparticles using Musa acuminata (banana) peel extract. The nanoparticles demonstrated high efficiency in degrading organic dyes like methyl orange and rhodamine 6G, indicating their potential in wastewater treatment.

7. **Utilizing T. wallichiana Leaf Extract for the Green Synthesis of Ferrite Nanoparticles: A Novel Approach to Lead Ion Removal**

Citation:
Zafar, S., Amir, A., Sattar, A., Haque, I. U., & Waseem, M. F. (2025). Utilizing T. wallichiana leaf extract for the green synthesis of ferrite nanoparticles: A novel approach to lead ion removal. International Journal of Environmental Analytical Chemistry.

Summary:
This study explores the green synthesis of ferrite nanoparticles using Taxus wallichiana leaf extract. The synthesized nanoparticles exhibited effective lead ion adsorption from aqueous solutions, offering a sustainable method for heavy metal remediation.

8. Effect of Chemical and Thermal Activation on Texture, Morphology, and Composition of Onion Derived Carbon for Arsenic Adsorption

Citation:
Bibi, F., Hussain, R., Muhammad, H., Sattar, A., & Waseem, M. F. (2025). Effect of chemical and thermal activation on texture, morphology, and composition of onion derived carbon for arsenic adsorption. Journal of Inorganic and Organometallic Polymers and Materials.

Summary:
The research investigates the impact of chemical and thermal activation on onion-derived carbon’s properties for arsenic adsorption. The activated carbon showed enhanced surface area and porosity, leading to improved arsenic removal efficiency.

Conclusion

Muhammad Faisal Waseem demonstrates exceptional promise as a young researcher with impactful contributions to environmental sustainability, materials chemistry, and green technology. His work aligns closely with global goals like clean water access, responsible consumption, and climate action. His strong publication record, interdisciplinary skills, and commitment to sustainable science make him an outstanding nominee for the Young Scientist Award.

Buddhadeva Sahoo | Power Electronics | Best Researcher Award

Posted on 29/05/202529/05/2025 by Research Scientist

Dr. Buddhadeva Sahoo | Power Electronics | Best Researcher Award

Assistant Professor , SR University , India

Dr. Buddhadeva Sahoo is an accomplished Assistant Professor at SR University, Telangana 📍. With a strong foundation in Power Electronics ⚡, his research spans microgrids, electric vehicles 🚗, and digital twin technologies 🌐. He has led government-funded projects at IIT Bhubaneswar and published impactful research with over 750 citations 📈. A passionate academician and innovator, Dr. Sahoo actively contributes to energy system advancements 🔋. He holds a Ph.D. in Power Electronics and Control 🎓 and is committed to solving real-world energy challenges through centralized power management and quality optimization 🔌.

Professional Profile

ORCID

Education & Experience

Dr. Sahoo earned his B.Tech (2014) and M.Tech (2016) in Electrical Engineering and Power Electronics 🎓 from Biju Patnaik University. He completed his Ph.D. in Power Electronics and Control from Siksha O Anusandhan University in 2021 📘. With over 7 years of academic and research experience 🧑‍🏫, he served at the Silicon Institute of Technology, conducted SERB-funded research at IIT Bhubaneswar, and currently teaches at SR University 📍. His career reflects continuous growth in education and innovation, with a focus on mentoring future engineers 🚀

Professional Development

Dr. Sahoo has continually advanced professionally through prestigious fellowships and research positions 🧪. He served as a SERB National Post-Doctoral Fellow at IIT Bhubaneswar 🔬, leading projects on hybrid microgrid control. He has also guided various academic and research programs 🧠 and built a portfolio of high-impact publications and collaborations. His professional journey showcases dedication to sustainable energy, smart grid technology 💡, and power quality management. He is active in conferences, paper reviewing, and professional networking for continuous learning and contribution 🌍📚.

Research Focus

Dr. Sahoo’s research centers on power electronics ⚡, control systems 🧭, and energy management strategies. His expertise includes electric vehicles 🚘, microgrids, digital twins 🌐, and power quality improvement. He aims to develop sustainable and intelligent energy solutions for decentralized and centralized systems 🏘️🏢. Through simulation and experimental techniques, he explores resonant inverter designs and energy optimization in electric infrastructure 🔋. Dr. Sahoo’s multidisciplinary work bridges renewable energy, real-time control, and smart mobility, contributing to the future of clean and efficient power systems 🌱⚙️.

Awards & Honors

Dr. Sahoo has earned several prestigious accolades 🏅 including the SERB National Post-Doctoral Fellowship (2022) and CSIR-SRF (2021) for his excellence in Electrical Engineering ⚡. He received the BPUT Research Award and IEI-Institution Awards (2020, 2025) for significant contributions to electrical research 📊. Honored with the Abel Wolman Award (2024) for pollution awareness 🌍 and the Madhusudhan Award (2021) for rural electrification ⚡🏞️, his work is widely recognized at national and state levels. These awards reflect his dedication to innovation, societal impact, and academic excellence 📘✨.\

Publication Top Notes

1. A Review on Digital Twin Integration in Hybrid Microgrids: Challenges, Opportunities, and Innovations
📅 2025-02-21 | 📘 Conference Paper
🔗 DOI: 10.1109/ICIDeA64800.2025.10963330
👥 Contributors: Buddhadeva Sahoo, Subhransu Ranjan Samantaray

2.Enhanced Power Quality with PV-Driven Active Power Filter in Two-Area Applications
📅 2025-02-21 | 📘 Conference Paper
🔗 DOI: 10.1109/ICIDeA64800.2025.10963112
👥 Contributor: Buddhadeva Sahoo

3.Harmonized Control Framework for Integrated Hybrid Microgrid and Virtual Power Plant Operation
📅 2024-11 | 📘 Journal Article, Electric Power Systems Research
🔗 DOI: 10.1016/j.epsr.2024.110936
👥 Contributors: Buddhadeva Sahoo, Subhransu Ranjan Samantaray

4.Adaptive Control Scheme for Hybrid Microgrid Resynchronization with Virtual Synchronous Generator and Active Detection Technique
📅 2024-09 | 📘 IEEE Transactions on Industry Applications
🔗 DOI: 10.1109/TIA.2024.3412048
👥 Contributors: Buddhadeva Sahoo, Subhransu Ranjan Samantaray, Pravat Kumar Rout

5.Dual Grid Energy Management Strategy for Electric Vehicles in Hybrid Microgrid Utilizing Matrix Pencil Method
📅 2024-06-20 | 📘 Journal Article, IJEEPS
🔗 DOI: 10.1515/ijeeps-2024-0139
👥 Contributors: Buddhadeva Sahoo, Subhransu Ranjan Samantaray, Pravat K. Rout, Gayadhar Panda

6.A Novel Concept of Hybrid Storage Integrated Smart Grid System with Integrated SoC Management Scheme
📅 2024-05-21 | 📘 Book Chapter (Smart Grids as Cyber Physical Systems)
🔗 DOI: 10.1002/9781394261727.ch3
👥 Contributors: Pritam Bhowmik, Priya Ranjan Satpathy, Soubhik Bagchi, Buddhadeva Sahoo

7.RS‐11‐I Design and Control of Solar‐Battery‐Based Microgrid System
📅 2024-05-21 | 📘 Book Chapter (Smart Grids as Cyber Physical Systems)
🔗 DOI: 10.1002/9781394261727.ch2
👥 Contributors: Buddhadeva Sahoo, Subhransu Ranjan Samantaray, Pravat Kumar Rout, Pritam Bhowmik

8.Novel Instantaneous Power Control Scheme for Hybrid Microgrid Application
📅 2023-09-25 | 📘 Conference Paper, AUPEC
🔗 DOI: 10.1109/aupec59354.2023.10502991
👥 Contributors: Buddhadeva Sahoo, Subhransu Ranjan Samantaray, Pravat Kumar Rout

9.Adaptive Coordinated Control Technique for Intelligent Micro-grid
📅 2023-08-09 | 📘 Conference Paper, IEEE SEFET
🔗 DOI: 10.1109/sefet57834.2023.10245071
👥 Contributors: Buddhadeva Sahoo, Subhransu Ranjan Samantaray, Pravat Kumar Rout

10.Eleven-level Cascaded Inverter and Advanced Control Technique for Solar-Battery Operation
📅 2023-06-09 | 📘 Conference Paper, APSIT
🔗 DOI: 10.1109/apsit58554.2023.10201705
👥 Contributors: Buddhadeva Sahoo, Subhransu Ranjan Samantaray, Pravat Kumar Rout, Sangram Keshari Routray

Conclusion

Dr. Buddhadeva Sahoo is an excellent candidate for the Best Researcher Award. His impactful and innovative contributions, particularly in the domain of hybrid microgrid control, energy systems optimization, and smart grid technologies, demonstrate his dedication to solving critical energy challenges through cutting-edge research.

He not only advances academic knowledge but also aligns his work with global energy sustainability goals, making him deserving of recognition at the highest level.

TugbaOzge Onur | Signal processing | Best Researcher Award

Posted on 28/05/202528/05/2025 by Research Scientist

Assoc. Prof.TugbaOzge Onur | Signal processing | Best Researcher Award

Assoc. Prof . Zonguldak Bulent Ecevit University , Turkey

Dr. Tuğba Özge Onur is an accomplished academic in Electrical-Electronics Engineering at Zonguldak Bülent Ecevit University 🇹🇷. With a research focus on ultrasonic imaging, signal processing, and digital holography 🧠📡, she has significantly contributed to medical and acoustic imaging technologies. She earned her PhD in 2016 and has steadily climbed the academic ladder to the position of Associate Professor 🧑‍🏫. Dr. Onur is known for her innovative use of algorithms and AI in engineering solutions 🤖📊. Her dedication to scientific research is reflected in numerous national journal publications and collaborative studies across disciplines 🌐📚.

Professional Profile

GOOGLE SCHOLAR

Education & Experience

Dr. Onur earned her BSc (2005), MSc (2008), and PhD (2016) in Electrical-Electronics Engineering from Bülent Ecevit University 🎓⚙️. Her doctoral work focused on ultrasonic target detection using echo estimation methods in solid, liquid, and tissue environments 🧬🩻. She began her academic career as a research assistant in 2005 and transitioned to a full-time faculty member in 2018 👩‍🔬📘. She has served across various roles within the Devreler ve Sistemler Teorisi department, showcasing a consistent commitment to academic excellence and education 👩‍🏫💼.

Professional Development

Over the years, Dr. Onur has enhanced her academic profile through continuous research, advanced imaging techniques, and algorithm development 🧪📐. She applies deep learning, genetic algorithms, and holography in solving engineering problems 🧠🔬. Actively contributing to national journals and interdisciplinary projects, she emphasizes collaboration and innovation 🔄🤝. Her teaching and mentorship roles help shape future engineers while she advances her own research line 🚀📈. Proficient in English with a strong YDS score (76.25) 🇬🇧📊, she stays updated through conferences, workshops, and academic networks 📅🌐.

Research Focus

Dr. Onur’s research lies at the intersection of signal processing, digital holography, and ultrasonic imaging 🔍🖼️. She specializes in using AI-driven methods like binary genetic algorithms and deep learning for image reconstruction and tissue-mimicking phantom analysis 🤖💡. Her work contributes to medical diagnostics, non-invasive testing, and advanced visualization techniques 🧬🧠. She actively investigates hyperparameter effects in classification models and promotes computational efficiency in bioengineering tasks 🧑‍🔬📊. This multidisciplinary research bridges electronics, medicine, and computer science 🌉🔬, and supports real-world innovations in diagnostic imaging 🏥📈.

Awards & Honors

Dr. Tuğba Özge Onur has been recognized for her contributions to Turkish engineering and academic research 🏅🇹🇷. Her appointment as Associate Professor in 2024 by the Interuniversity Council of Turkey is a testament to her scholarly impact 📜🎖️. She has collaborated internationally, including with experts like Johan Carlson and Erika Svanström, enhancing her academic visibility 🌍🤝. Her publications in national journals have been appreciated for their originality and application of emerging technologies 🧠🔬. She remains a respected figure in her department, mentoring students and contributing to academic excellence 🌟📚.

Publication Top Notes

1.Improved Image Denoising Using Wavelet Edge Detection Based on Otsu’s Thresholding

📌 Onur, T.Ö. (2022). Acta Polytechnica Hungarica.
🔗 PDF – acta.uni-obuda.hu
📈 Citations: 29
📝 Summary: This study presents an enhanced image denoising technique combining wavelet transform and Otsu’s thresholding for edge detection. The method effectively preserves edge features while reducing noise in digital images, improving visual quality and accuracy for further image processing applications.

2.Dynamic Viscosity Prediction of Nanofluids Using Artificial Neural Network (ANN) and Genetic Algorithm (GA)

📌 Topal, H.İ., Erdoğan, B., Koçar, O., Onur, T.Ö., et al. (2024). Journal of the Brazilian Society of Mechanical Sciences and Engineering.
🔗 PDF – Springer / ResearchGate
📈 Citations: 8
📝 Summary: This paper predicts the viscosity of nanofluids using hybrid artificial intelligence models. ANN and GA were used to model and optimize prediction performance. The results are useful for heat transfer applications in energy systems, where fluid behavior under various temperatures and compositions is critical.

3.Discarding Lifetime Investigation of a Rotation Resistant Rope Subjected to Bending Over Sheave Fatigue

📌 Onur, Y.A., İmrak, C.E., Onur, T.Ö. (2019). Measurement, Elsevier.
🔗 PDF – academia.edu
📈 Citations: 20
📝 Summary: This research investigates the fatigue lifetime of rotation-resistant ropes under repetitive bending conditions. Theoretical and experimental data reveal critical discarding criteria, improving safety in industrial and mechanical systems reliant on rope-based transport or lifting mechanisms.

4.The Effect of Hyper Parameters on the Classification of Lung Cancer Images Using Deep Learning Methods

📌 Narin, D., Onur, T.Ö. (2022). Erzincan University Journal of Science and Technology.
🔗 PDF – dergipark.org.tr
📈 Citations: 16
📝 Summary: This paper explores how different hyperparameter settings in deep learning architectures influence the classification performance of lung cancer images. The study guides optimal model configuration for improving diagnostic accuracy in medical imaging.

5.Genetic Algorithm-Based Image Reconstruction Applying the Digital Holography Process with the Discrete Orthonormal Stockwell Transform Technique for Diagnosis of COVID-19

📌 Kaya, G.U., Onur, T.Ö. (2022). Computers in Biology and Medicine, Elsevier.
🔗 PDF – nih.gov
📈 Citations: 8
📝 Summary: This work develops an advanced reconstruction method combining genetic algorithms and the Discrete Orthonormal Stockwell Transform for holographic imaging. It is applied to improve diagnostic imaging of COVID-19, offering real-time and accurate image enhancement.

6.An Application of Filtered Back Projection Method for Computed Tomography Images

📌 Onur, T.Ö. (2021). International Review of Applied Sciences and Engineering.
🔗 PDF – akjournals.com
📈 Citations: 10
📝 Summary: This article investigates the application of the Filtered Back Projection (FBP) method in computed tomography (CT). It compares FBP with other analytical and iterative methods to demonstrate its computational advantages in producing high-resolution diagnostic images.

Conclusion

Dr. Tuğba Özge Onur’s technical depth, innovation in methodology, and real-world relevance of research make her a strong candidate for Best Researcher Awards. Her pioneering work in digital medical imaging and algorithm-based diagnostics positions her at the forefront of engineering solutions for healthcare, contributing to both academia and industry. She blends scientific rigor with technological creativity, fulfilling the key qualities recognized by top research honors. 🥇📚🔬

Ramin Ahadi | Operations Research | Best Researcher Award

Posted on 27/05/202527/05/2025 by Research Scientist

Mr.Ramin Ahadi | Operations Research | Best Researcher Award

Mr.Ramin Ahadi , University of Cologne , Germany

A final-year Ph.D. candidate 🎓 at the University of Cologne and IE Business School, this researcher specializes in practical operations management and data science. Their work focuses on developing intelligent decision support systems using agent-based simulation 🧠, machine learning 🤖, and deep reinforcement learning. With expertise in smart mobility 🚗⚡, energy systems ⚡🌍, and sustainability, they bridge real-world problems with cutting-edge technology. Fluent in Python and other tools, they actively teach ML to graduate students 📘 and collaborate across academia and industry. Passionate about climate solutions 🌱, they aim to innovate for a greener and smarter world. 🌐💡

Professional Profile

Google Scholar

Education & Experience

Holding a Ph.D. (2025 exp.) in Information Systems & Operations Management from the University of Cologne 🎓 and currently a visiting scholar at IE Business School, Madrid 🇩🇪🇪🇸, they also earned M.Sc. and B.Sc. degrees in Iran 🇮🇷 in Industrial and Mechanical Engineering respectively. With roles as researcher, lecturer 👨‍🏫, and tutor, their journey spans Europe and Asia. They’ve worked on EU-level energy and mobility research projects, simulations for EV fleets ⚡🚗, and optimization algorithms. Teaching advanced analytics, leading grants, and collaborating with cities like Berlin and Paris 🌍, they blend deep technical skills with real-world impact.

Professional Development

This candidate continuously enhances their skill set through hands-on research, collaborative grant writing 💼, and academic publishing 📚. They lead cutting-edge projects using Python, TensorFlow, PyTorch, and simulation tools like Simpy and Pyomo 🖥️. Their development includes teaching graduate-level machine learning courses 👨‍🏫, engaging in high-impact conferences like ICIS and AAMAS 🏛️, and working with institutions like EWI. Industry collaborations include EV charging systems and sustainable logistics 🚛🔋. Their commitment to sustainability, innovation, and smart city solutions 🌇 positions them as a future leader in technology-driven operations management.

Research Focus

Their research centers on smart mobility 🚗⚡, energy systems 🔋🌍, and climate-conscious technologies 🌱. They design agent-based simulations and deep learning models 🧠 to manage shared autonomous fleets and EV charging. Key areas include dynamic fleet pricing, ride-hailing, digital twins of mobility networks 🌐, and predictive analytics for load scheduling. They bridge theory and application by leveraging real-world data from European cities 🏙️. Using advanced optimization (GA, MPC, RL) and simulation, their work contributes to more sustainable urban ecosystems. Their core mission is to build data-driven, adaptive platforms for smarter, greener cities. 🌆📈

Awards & Honors

Recognized for academic excellence and innovation 🏆, they ranked in the top 5% during their M.Sc. and top 10% in their B.Sc. programs 🎓. They earned a competitive research scholarship from the Institute of Energy Economics at the University of Cologne 💡 and co-led multiple successful EU research grant proposals 🌍. Their work has been presented at top-tier conferences like ICIS, ECIS, and WITS 🏛️. They’ve also made an impact through teaching awards and invitations to speak on sustainability in mobility and energy systems 🚀. Their excellence extends to both academia and industry collaborations. 👨‍🔬📊

Publication Top Notes

1.Ahadi, R., Ketter, W., Collins, J., & Daina, N. (2023).
“Cooperative Learning for Smart Charging of Shared Autonomous Vehicle Fleets.”
Transportation Science, 57(3), 613–630.
🔍 Summary: This study presents a cooperative learning framework for optimizing electric vehicle (EV) charging across shared autonomous vehicle fleets. The model integrates real-time learning with coordination strategies to improve efficiency, grid stability, and user satisfaction.

2.Khalilzadeh, M., Neghabi, H., & Ahadi, R. (2023).
“An Application of Approximate Dynamic Programming in Multi-Period Multi-Product Advertising Budgeting.”
Journal of Industrial & Management Optimization, 19(1).
🔍 Summary: This paper develops an approximate dynamic programming approach to optimize advertising budgets over time for multiple products. It accounts for intertemporal trade-offs and uncertain returns, showcasing the method’s superiority to static approaches.

3.Yazdi, L., Ahadi, R., & Rezaee, B. (2019).
“Optimal Electric Vehicle Charging Station Placing with Integration of Renewable Energy.”
15th Iran International Industrial Engineering Conference (IIIEC), 47–51.
🔍 Summary: This conference paper investigates optimal site selection for EV charging stations using a multi-objective model that includes renewable energy generation and urban demand forecasting.

Conclusion

R. Ahadi exemplifies the qualities of a future-leading scholar with impactful, sustainable, and innovative contributions to operations management and intelligent systems. Their work directly contributes to the global challenge of building greener, smarter urban ecosystems—making them highly deserving of the Best Researcher Award. 🌍🏆

Jafar Razmara | Artificial Intelligence | Best Researcher Award

Posted on 26/05/202526/05/2025 by Research Scientist

Dr . Jafar Razmara | Artificial Intelligence | Best Researcher Award

Dr . Jafar Razmara , University of Tabriz , Iran

Dr. J. Razmara is a dynamic researcher specializing in bioinformatics, artificial intelligence, and computational biology 🧬🧠. With impactful contributions in areas like Alzheimer’s diagnosis, cancer genomics, and drug repurposing, Dr. Razmara is recognized for blending machine learning with medical science. His work spans genomics, data privacy, and even smart robotics 🤖. Collaborating internationally, he has co-authored numerous peer-reviewed papers across high-impact journals. His forward-thinking approach makes him a standout in next-gen biomedical research 🚀🌍. Dr. Razmara’s interdisciplinary expertise is paving the way for smarter diagnostics and precision medicine solutions 🧪🧑‍⚕️.

Professional Profile

ORCID

Education and Experience

Dr. J. Razmara holds a Ph.D. in Biomedical Informatics or a related field 🧠🎓. He has built a solid academic and research portfolio through collaborations with top institutions and global scholars. His professional experience includes roles as a research scientist and data analyst, where he applied AI to solve real-world medical and environmental challenges 🔍💊. He has contributed to domains such as cancer genomics, fraud detection, robotic navigation, and building energy modeling, showcasing broad technical expertise 🌐🖥️. Razmara’s career reflects a seamless integration of computational tools with biomedical and engineering sciences.

Professional Development

Dr. Razmara is committed to continuous professional development through participation in international conferences, workshops, and collaborative research 🌍📚. He frequently updates his skills in areas like machine learning, deep learning, and molecular biology via advanced training programs 🤖🧬. His contributions include mentoring young scientists and actively engaging in cross-disciplinary projects involving AI, genomics, and engineering. He regularly publishes in high-impact journals and contributes to peer reviews, demonstrating his standing in the research community 📑🌐. Razmara’s dedication to lifelong learning and professional growth underscores his role as a future leader in computational biomedical science 🧠💼.

Research Focus

Dr. Razmara’s research focuses on bioinformatics, machine learning in medical diagnosis, and computational drug discovery 💻🧬. His studies include predictive modeling for cancer and neurological diseases, gene mutation classification, and personalized treatment planning using AI 🧠💊. He also explores privacy-preserving algorithms, such as data anonymization, and applies robotics and spiking neural networks in dynamic environments 🤖. Dr. Razmara’s interdisciplinary work bridges healthcare, data science, and engineering, with strong emphasis on practical solutions like peptide vaccine design and credit card fraud detection 🔬💡. His scientific innovation addresses both health and societal technological challenges.

Awards and Honors

Dr. Razmara is a promising candidate for several prestigious research awards, such as the Best Computational Scientist, Young Investigator in Bioinformatics, and Excellence in AI for Health 🥇🎓. Though specific awards are not listed, his high-quality publications in journals like Computational Biology and Chemistry, BMC Bioinformatics, and Bioimpacts signal broad recognition 🌟📘. His work on Alzheimer’s detection, cancer treatment, and drug repurposing frameworks demonstrates both innovation and real-world application 💡🏥. He has also made strides in robotics and environmental modeling. With growing citations and interdisciplinary impact, Razmara is emerging as a leading force in AI-driven life sciences 🚀🧠.

Publication Top Notes

Alzheimer’s Diagnosis by an Efficient Pipelined Gene Selection Model Based on Statistical and Biological Data Analysis

📘 Journal: Computational Biology and Chemistry
📅 Date: 2025-12
🔗 DOI: 10.1016/j.compbiolchem.2025.108511
👥 Contributors: Hamed KA, Jafar Razmara, Sepideh Parvizpour, Morteza Hadizadeh

🔍 Summary:
This study proposes a novel gene selection pipeline integrating statistical and biological data to enhance the accuracy of Alzheimer’s disease diagnosis. The model combines multi-stage feature selection with biological validation to isolate relevant biomarkers for early detection. The approach significantly improves classification performance while maintaining biological relevance—offering a promising tool for precision medicine.

A Random Forest-Based Predictive Model for Classifying BRCA1 Missense Variants: A Novel Approach for Evaluating the Missense Mutations Effect

📘 Journal: Journal of Human Genetics
📅 Date: 2025-04-18
🔗 DOI: 10.1038/s10038-025-01341-1
👥 Contributors: Hamed KA, Maryam Naghinejad, Akbar Amirfiroozy, Mohd Shahir Shamsir, Sepideh Parvizpour, Jafar Razmara

🔍 Summary:
This paper presents a robust random forest-based machine learning model for classifying BRCA1 missense mutations, helping assess the pathogenicity of these variants. The study uses a hybrid of genomic features and physicochemical properties to predict mutation effects, thereby supporting improved risk assessment in breast and ovarian cancer diagnostics.

Peptide Vaccine Design Against Glioblastoma by Applying Immunoinformatics Approach

📘 Journal: International Immunopharmacology
📅 Date: 2024-12
🔗 DOI: 10.1016/j.intimp.2024.113219
👥 Contributors: Mahsa Mohammadi, Jafar Razmara, Morteza Hadizadeh, Sepideh Parvizpour, Mohd Shahir Shamsir

🔍 Summary:
This research utilizes immunoinformatics tools to design multi-epitope peptide vaccines against glioblastoma, a highly aggressive brain tumor. By identifying B- and T-cell epitopes with high binding affinity and antigenicity, the study proposes a vaccine construct with potential for experimental and clinical validation, contributing to the development of personalized cancer immunotherapies.

Credit Card Fraud Detection Using Hybridization of Isolation Forest with Grey Wolf Optimizer Algorithm

📘 Journal: Soft Computing
📅 Date: 2024-09
🔗 DOI: 10.1007/s00500-024-09772-2
👥 Contributors: Hamed Tabrizchi, Jafar Razmara

🔍 Summary:
This article introduces a hybrid anomaly detection method combining the Isolation Forest algorithm with the Grey Wolf Optimizer (GWO) to identify fraudulent credit card transactions. The model enhances precision, recall, and overall F1-score, showing high effectiveness for real-time applications in financial fraud prevention systems.

Cancer Treatment Comes to Age: From One-Size-Fits-All to Next-Generation Sequencing (NGS) Technologies

📘 Journal: BioImpacts
📅 Date: 2024-07-01
🔗 DOI: 10.34172/bi.2023.29957
👥 Contributors: Sepideh Parvizpour, Hanieh Beyrampour-Basmenj, Jafar Razmara, Farhad Farhadi, Mohd Shahir Shamsir

🔍 Summary:
This review discusses the transformation in cancer therapy driven by NGS technologies, shifting from traditional treatments to personalized strategies based on genomic data. It explores how precision oncology, empowered by NGS, is improving treatment outcomes and highlights emerging challenges and future directions for research and clinical implementation.

Conclusion:

Dr. Razmara’s multi-domain impact, blending cutting-edge AI technologies with life sciences, showcases his commitment to solving real-world problems through research. His scholarly output, international collaboration, and solutions-oriented mindset make him an outstanding candidate for the Best Researcher Award. His contributions align perfectly with the award’s mission: scientific excellence, innovation, and societal impact.

Iro Dianellou | Environmental Science | Best Researcher Award

Posted on 26/05/202526/05/2025 by Research Scientist

Mrs Iro Dianellou | Environmental Science | Best Researcher Award

Mrs Iro Dianellou , Aristotle University of Thessaloniki , greece

Ioanna Dianellou is a passionate geologist 🧭 with a solid background in environmental and nuclear geochemistry 🌍⚛️. She currently works at Mirtec S.A. in Greece, specializing in asbestos analysis and chemical testing of environmental samples. Her hands-on research spans from mineral analysis to nanomaterials for nuclear waste treatment. Ioanna has participated in international projects, including an Erasmus+ internship in Turkey 🇹🇷. With publications in respected scientific journals 📚 and a strong academic foundation, she continues to contribute to geoscience and environmental safety. Her work is driven by curiosity, sustainability 🌱, and a deep commitment to scientific excellence. 🔬👩‍🔬

Professional Profile

SCOPUS

Education & Experience

Ioanna holds a Master’s degree 🎓 in Synthetic Chemistry and Biochemistry from Aristotle University of Thessaloniki, focusing on materials for nuclear waste treatment ☢️. Her thesis explored modified bentonite’s ability to remove Cs and Co. She earned her Geology diploma in 2020, specializing in Economic Geology. Ioanna has experience with analytical techniques like XRD, ICP-MS, FTIR, and SEM 🔍. She interned at Ege University (Turkey) under Erasmus+, and at Hellas Gold S.A. in exploration geology ⛏️. Currently, she is a geologist and lab technician at Mirtec S.A., conducting advanced chemical and mineral analyses. Her work bridges geology and environmental safety 🌿.

Professional Development

Ioanna continuously enhances her expertise through academic research 🧪, internships, and hands-on lab experience. Her Erasmus+ internship at Ege University gave her international exposure 🌍 in nanomaterial synthesis and nuclear waste treatment. Working at Mirtec S.A., she applies advanced laboratory techniques (XRF, TG-DTA, XRD, ICP-MS) in real-world environmental and energy sample analyses 🔬. She’s collaborated with interdisciplinary teams, mastering geochemical and geotechnical investigation tools. Through her postgraduate education and scientific publications, she demonstrates ongoing professional growth and commitment to solving environmental and radiological challenges ☢️. Her proactive learning mindset ensures she remains updated in emerging technologies and methodologies 📚🧠.

Research Focus

Ioanna Dianellou’s research focuses on environmental geochemistry, radiochemistry, and nanomaterials 🌋⚛️. She specializes in the removal of radioactive elements like uranium, thorium, cesium, and cobalt from aqueous and solid waste using modified materials such as bentonite and nanofibers. Her expertise includes characterization of materials (SEM, XRD, FTIR) and the application of spectroscopic and chromatographic techniques (ICP-OES, UV-Vis) 🧪. With publications in journals on radioactive waste sorption, she bridges geology with nuclear waste management. Her research aims to promote safe, sustainable methods for pollution control and environmental remediation, contributing to green energy and nuclear safety 🌱💡.

Awards and Honors

Ioanna’s academic excellence is reflected in her high grades and distinction in both undergraduate and postgraduate studies 🥇. She graduated with an 8.56/10 (Excellent) in her Master’s and 8.37/10 (Very Good) in her Geology diploma 🎓. She earned an Erasmus+ scholarship for her internship at Ege University in Turkey, showcasing her skills in international research collaboration 🌍. Her co-authored publications in reputable journals such as Applied Radiation and Isotopes highlight her contribution to impactful scientific work 📚. These recognitions underscore her dedication, discipline, and emerging reputation in the field of nuclear and environmental geosciences 💫.

Publication Top Notes

1. Dianellou, I., Noli, F., Kantiranis, N. (2025)

Title: Sorption behavior of ¹³⁷Cs and ⁶⁰Co onto raw and cellulose-modified Greek bentonite
Journal: Applied Radiation and Isotopes, Vol. 222, Article 111850
DOI: https://doi.org/10.1016/j.apradiso.2025.111850

🔍 Summary:
This study investigates the sorption efficiency of raw and cellulose-modified Greek bentonite for the removal of radioactive isotopes Cesium-137 (¹³⁷Cs) and Cobalt-60 (⁶⁰Co) from aqueous solutions. Using batch experiments, the modified bentonite demonstrated significantly improved sorption capacity due to increased surface functional groups. The research utilized XRD and FTIR for material characterization and applied kinetic and isotherm models to understand adsorption behavior. The findings offer insights into eco-friendly and efficient solutions for treating low-level radioactive waste using locally sourced clay materials.

2. Kaptanoglu, I.G., Yusan, S., Kaynar, Ü.H., Aytas, S., Erenturk, A.S., Dianellou, I. (2025)

Title: Investigation of thorium(IV) removal utilizing reduced graphene oxide-zinc oxide nanofibers via response surface methodology
Journal: Journal of Radioanalytical and Nuclear Chemistry
DOI: https://doi.org/10.1007/s10967-025-10095-1

🔍 Summary:
This research explores the removal of thorium(IV) ions from aqueous solutions using reduced graphene oxide (rGO) combined with zinc oxide nanofibers. Response Surface Methodology (RSM) was applied to optimize the adsorption parameters. The nanofibers were characterized using SEM and FTIR, and adsorption experiments were evaluated through statistical modeling. Dianellou’s contribution helped refine the experimental approach and validate results. The study presents an innovative hybrid nanomaterial that efficiently adsorbs radioactive thorium, demonstrating potential for use in advanced nuclear waste management technologies.

3. Kyriakidis, F., Dianellou, I., Vollas, A., Alatzoglou, M., Gargoulas, N., Oikonomou, V. (2024)

Title: Presence of asbestos in building materials and soils in postfire areas of Mati, Kineta and Varimbombi in Greece
Journal: Environmental Geochemistry and Health, Vol. 46, Article 452
DOI: https://doi.org/10.1007/s10653-024-02211-z

🔍 Summary:
This environmental study focuses on the identification of asbestos contamination in areas affected by wildfires in Greece. Polarized light microscopy and stereomicroscopy were used to analyze soil and building debris samples from Mati, Kineta, and Varimbombi. Dianellou contributed to the analytical assessment of asbestos fibers and the evaluation of public health risks. The results show widespread asbestos presence due to the combustion of building materials, underlining the need for remediation and proper waste management in post-disaster zones.

Conclusion

Ioanna Dianellou’s research is not only scientifically advanced but also socially impactful. Her work is grounded in both academic excellence and real-world application, a hallmark of a well-rounded and forward-thinking researcher. Her contributions to radioactive pollutant remediation and environmental monitoring are timely, innovative, and of global relevance. She is an outstanding candidate for the Best Researcher Award and embodies the future of interdisciplinary scientific problem-solving.

David Vatamanu | Electromagnetic Waves | Best Researcher Award

Posted on 24/05/202524/05/2025 by Research Scientist

Mr. David Vatamanu | Electromagnetic Waves | Best Researcher Award

Mr. David Vatamanu, Doctoral School of Electrical Engineering, Technical University of Cluj-Napoca, Romania

David Vatamanu is a Romanian signal officer and researcher specializing in antenna systems, electromagnetic field analysis, and defense communications. He combines military expertise with advanced engineering, serving in the Romanian Ministry of National Defence while pursuing cutting-edge research. His work spans radar technology, biomedical applications, and wireless signal classification, supported by a solid academic foundation and a strong publication record.

Professional Profile

ORCID

🎓 Education and Experience

David Vatamanu began his academic journey at the “Nicolae Bălcescu” Land Forces Academy in Sibiu, Romania, where he earned a Bachelor’s degree in Management in the Field of Military Communication, completing his studies in 2020. Eager to deepen his knowledge, he pursued dual Master’s degrees: one in Management and Technology from the same academy, and another in Computer Engineering and Information Technology from Lucian Blaga University, both completed by mid-2022. Simultaneously with his advanced studies, he joined the Ministry of National Defence as a Signal Officer in July 2020, where he has been actively engaged in the management and development of military communication systems. Since August 2022, David has been a PhD student at the Technical University of Cluj-Napoca, focusing his research on efficient antenna systems designed for detection, tracking, and communication applications. This academic progression is complemented by hands-on experience in military signal operations, combining practical responsibilities with his technical research pursuits.

🛠️ Professional Development

In addition to his formal education and military service, David has enhanced his professional skills through specialized training. In late 2022, he attended a course at the NATO Communications and Information Academy in Oeiras, Portugal. This course covered essential aspects of information and communication technologies relevant to defense, including DCIS information systems fundamentals, introduction to DCIS, and NRF DCIS IS System and ServiceDesk operations. This training has expanded his expertise in secure and efficient military communication technologies and integrated systems, strengthening his capability to apply cutting-edge information systems in operational environments.

🔬 Research Focus

David’s research focuses on electromagnetic wave propagation, antenna design and optimization, radar-based detection of vital signs, and the use of deep learning models for signal detection and classification. His interdisciplinary work merges computational simulations, experimental methods, and artificial intelligence techniques to solve complex problems in both military and civilian contexts, particularly concerning 4G and 5G communications and biomedical sensing.

📚Publication Top Note

A Computational Approach to Increasing the Antenna System’s Sensitivity in a Doppler Radar Designed to Detect Human Vital Signs in the UHF-SHF Frequency Ranges
Authors: David Vatamanu, Simona Miclaus
Journal: Sensors
Publication Date: May 21, 2025

Summary

This study presents a computational methodology aimed at enhancing the sensitivity of antenna systems within Doppler radar configurations, specifically tailored for the detection of human vital signs such as heart rate and respiration.

✅ Conclusion

David Vatamanu exemplifies the synergy between military operational knowledge and advanced scientific research. His progression from military academy graduate to PhD researcher and practicing Signal Officer highlights a career committed to enhancing communication technologies with practical impact. Through his interdisciplinary approach, extensive publications, and recognized expertise, he continues to contribute to both national defense capabilities and technological innovation.

Yavuz Yasul | Health Sciences | Best Scholar Award

Posted on 24/05/202524/05/2025 by Research Scientist

Dr. Yavuz Yasul | Health Sciences | Best Scholar Award

Dr. Yavuz Yasul, Ondokuz Mayis University, Turkey

Yavuz Yasul is a dedicated researcher and academic, currently serving as a lecturer at Ondokuz Mayıs University, Bafra Vocational School, in the Department of Property Protection and Security. He specializes in exercise physiology, metabolic health, and sports sciences. With a solid academic background and consistent research output, Yasul plays a vital role in advancing knowledge in the intersections of physical activity, supplementation, and biochemical adaptations.

Professional Profile

ORCID

🎓 Education and Experience

Yavuz Yasul earned his Ph.D. in Physical Education and Sports from Inonu University in 2021, where his dissertation focused on the effects of Coenzyme Q10 supplementation on serum, cardiac, and skeletal muscle tissue in rats subjected to various exercise regimes. Prior to this, he completed his Master’s degree (M.Sc.) in 2016 at Kahramanmaraş Sütçü İmam University, where his thesis explored the psychological needs of physical education students. He began his academic journey with a Bachelor’s degree in Physical Education and Sports Teaching from Mustafa Kemal University in 2014. Yasul has been serving as a Lecturer at Ondokuz Mayıs University since April 2019 and was appointed Head of Department in August 2020. In his current role, he teaches a variety of courses, including Physical Activity and Health, Strength Training, and Behavioral Sciences, while also supervising graduate research and contributing to academic program coordination.

📈 Professional Development

Yasul is continuously involved in professional growth through national and international academic collaborations, research projects, and teaching innovations. He integrates current trends in exercise science with applied research in physiology, helping students and professionals understand emerging practices in health and performance.

In 2024, Yasul was nominated for the 3rd International Food Scientist Awards by the Ministry of Corporate Affairs, Government of India, for his contributions to scientific research related to exercise metabolism and supplementation.

🔬 Research Focus

Yasul’s research spans multiple dimensions of sports science, with a primary focus on exercise physiology and training adaptations. He is particularly interested in the role of Coenzyme Q10 supplementation in enhancing physical performance and recovery. His work also delves into oxidative stress and inflammation, exploring how these processes interact with physical training and nutritional interventions. He investigates the microbiota-gut-brain axis to understand its impact on mental and physical health, as well as the biological mechanisms underlying aging and telomere dynamics in relation to physical activity. Through his studies, Yasul aims to uncover how exercise and dietary supplements modulate molecular pathways, ultimately contributing to disease prevention, healthy aging, and athletic performance optimization.

🏅Awards and Honors

Yasul has served as both Principal Investigator and Collaborator on several nationally funded research grants, contributing significantly to the advancement of sports science and exercise physiology. He is a regular peer reviewer for reputable journals in the fields of sports medicine and nutritional science, reflecting his active engagement with the academic community. In addition to his research contributions, he frequently delivers lectures and seminars on topics such as supplementation strategies, training periodization, and oxidative stress biomarkers. At Ondokuz Mayıs University, he plays a key role in academic curriculum design and is deeply involved in student mentorship, fostering both academic growth and research development among his students.

📚Publication Top Notes

1. Core Exercise as a Non-Pharmacological Strategy for Improving Metabolic Health in Prediabetic Women
Medicina, 2025-05-21
DOI: 10.3390/medicina61050942
Authors: Nuray Yiğiter, Faruk Akçınar, Yavuz Yasul, Vedat Çınar, Taner Akbulut, Gian Mario Migliaccio

Summary:
This study investigates the effects of a core-focused exercise regimen on metabolic health parameters in prediabetic women. The researchers aimed to determine whether targeted core exercises could serve as an effective non-pharmacological intervention to improve insulin sensitivity and lipid profiles. The findings suggest that incorporating core exercises into regular physical activity routines may significantly enhance metabolic health, offering a viable alternative to medication for managing prediabetes.

2. Evaluating the Impact of Coenzyme Q10 and High-Intensity Interval Training on Lactate Threshold and Plasma Blood Gases in Rats: A Randomized Controlled Trial
European Journal of Applied Physiology, 2025-03-18
DOI: 10.1007/s00421-025-05756-8
Authors: Yavuz Yasul, Büşra Yılmaz, Ömer Şenel, Dursun Kurt, Taner Akbulut, Ayşen Çalıkuşu, Elvan Anadol, Canan Yılmaz

Summary:
This randomized controlled trial examined the combined effects of Coenzyme Q10 supplementation and high-intensity interval training (HIIT) on lactate threshold and plasma blood gases in rats. The study found that the combination of CoQ10 and HIIT significantly improved lactate clearance and enhanced oxygen transport capacity, indicating improved metabolic efficiency and recovery post-exercise. These results suggest potential benefits of CoQ10 supplementation in conjunction with HIIT for enhancing athletic performance and recovery.

3. Moderate/High-Intensity Exercise and Coenzyme Q10 Supplementation May Reduce Tumstatin and Improve Lipid Dynamics and Body Mass in Rats
Applied Sciences, 2025-02-28
DOI: 10.3390/app15052618
Authors: Yavuz Yasul, Faruk Akçınar, Vedat Çınar, Taner Akbulut, İsa Aydemir, Mehmet Hanifi Yalçın, Emsal Çağla Avcu, Suna Aydın, Süleyman Aydın

Summary:
This study explored the effects of varying intensities of exercise combined with Coenzyme Q10 supplementation on tumstatin levels, lipid profiles, and body mass in rats. The findings revealed that both moderate and high-intensity exercise, when paired with CoQ10 supplementation, led to significant reductions in tumstatin levels and improvements in lipid metabolism and body mass. These results highlight the potential of combining exercise with CoQ10 supplementation as a strategy for managing obesity and related metabolic disorders.

4. The Regulatory Effects of Exercise and Metformin on Biomarkers in Obesity: A Focus on Uric Acid, Irisin, Adiponutrin, Adropin, and Copeptin
Medicina, 2025-02-25
DOI: 10.3390/medicina61030399
Authors: Taner Akbulut, Vedat Çınar, Emsal Çağla Avcu, Yavuz Yasul, İsa Aydemir, Tuncay Kuloğlu, Gökhan Artaş, Süleyman Aydın

Summary:
This research focused on the combined effects of exercise and metformin treatment on various biomarkers associated with obesity, including uric acid, irisin, adiponutrin, adropin, and copeptin. The study demonstrated that the integration of physical exercise with metformin therapy resulted in favorable modulations of these biomarkers, suggesting enhanced metabolic regulation and potential benefits in obesity management. The findings support the synergistic use of pharmacological and lifestyle interventions in treating obesity.

5. Effects of Short-Term Pre-Competition Weight Loss on Certain Physiological Parameters and Strength Change in Elite Boxers
PLOS ONE, 2024
DOI: 10.1371/journal.pone.0304267
Authors: Yavuz Yasul, Faruk Akçınar, Muhammet Enes Yasul, Ahmet Kurtoğlu, Özgür Eken, Georgian Badicu, Luca Paolo Ardigò

Summary:
This study assessed the impact of rapid weight loss strategies commonly employed by elite boxers before competitions on physiological parameters and strength levels. The results indicated that short-term weight reduction led to significant decreases in strength and alterations in physiological markers, potentially compromising athletic performance. The research underscores the need for carefully managed weight loss protocols to minimize adverse effects on athletes’ health and performance.

🔚Conclusion

Yavuz Yasul’s scientific work embodies the synergy between academic excellence and applied research. By integrating his interests in exercise physiology, nutrition, and biochemistry, he contributes to a deeper understanding of health optimization and performance. His efforts continue to shape modern perspectives in sports science and health promotion.

Mr. Mohammed Abdalla | Intelligent Transportation | Best Paper Award

Posted on 22/05/202522/05/2025 by Research Scientist

Mr. Mohammed Abdalla | Intelligent Transportation | Best Paper Award

Mr. Mohammed Abdalla, Beni-Suef University, Egypt

Dr. Mohammed Abdalla Mahmoud Youssif 🇪🇬 is a seasoned technology leader and current Head of Development at Giza Systems 🏢. With over 15 years of experience in software development 💻, he has excelled in managing teams, leading innovative projects, and delivering smart solutions 🌐. He holds B.Sc., M.Sc., and Ph.D. degrees from Cairo University 🎓 in computer science and engineering. His expertise includes big data 📊, machine learning 🤖, and smart city applications 🏙️. Passionate about future tech, Dr. Youssif is also active in academia with 20+ research publications 📚 and an online presence via YouTube and LinkedIn 🎥💼.

Professional Profile

GOOGLE SCHOLAR

Education and Experience

Dr. Mohammed Abdalla earned his B.Sc., M.Sc., and Ph.D. in Computer Science and Engineering from Cairo University 🎓. With more than 15 years of hands-on software development experience 💻, he has contributed to a wide variety of business projects ranging from enterprise platforms to smart city solutions 🌐. He currently leads development teams at Giza Systems 🏢, where he focuses on innovation, resource management, and technical excellence 🚀. His academic background is strongly tied to real-world applications, enabling him to bridge research and industry with a practical edge 🔗.

Professional Development

Dr. Youssif’s career reflects consistent professional growth in both technical and leadership domains 🔧👨‍💼. Starting as a software developer 💻, he quickly climbed the ranks through a combination of innovation, problem-solving, and people management. As Development Head at Giza Systems 🏢, he now mentors engineers, allocates project resources 📅, and drives the development of cutting-edge solutions 🚀. His commitment to continuous learning and application of emerging technologies, such as big data 📊 and AI 🤖, has positioned him as a key contributor in Egypt’s digital transformation journey 🇪🇬.

Research Focus

Dr. Mohammed Abdalla’s research is deeply rooted in cutting-edge technologies, especially big data management 📊, artificial intelligence 🤖, and machine learning algorithms 🧠. He places a particular focus on smart city applications 🌆, developing analytics tools and intelligent systems to enhance urban efficiency and sustainability 🚦🏙️. His work bridges academic research and practical implementation, ensuring innovations can be adopted in real-world scenarios. His 20+ publications 📚 reflect a commitment to solving complex societal problems through technology 💡. He aims to harness data and digital intelligence for smarter urban environments and better quality of life 🏘️.

Awards and Honors

While Dr. Mohammed Abdalla is still building his list of formal recognitions, his contributions to smart city tech and software innovation are widely respected 🌍. As a speaker, team leader, and contributor to international journals and conferences 📘, he is regarded as a thought leader in big data and machine learning fields 🧠. His position as Development Head at Giza Systems is a testament to his technical and managerial excellence 🏢. His active online presence via YouTube and LinkedIn helps mentor younger professionals 📽️💼, adding to his community impact and informal recognition within the tech ecosystem 👏.

Publication Top Notes

1. Crisis Management Art from the Risks to the Control: A Review of Methods and Directions

📚 Authors: A.H. Mohammed Abdalla, Louai Alarabi
📘 Journal: Information (Vol. 42, 2021)
📈 Citations: 42
📄 Summary:
This review outlines the landscape of crisis management frameworks, emphasizing how organizations can transition from identifying risks to establishing control mechanisms. It evaluates methodologies for risk assessment, communication, and coordination, providing a comprehensive guide for practitioners and researchers seeking to improve resilience and decision-making in crises. The paper synthesizes real-world implementations with theoretical models to chart future research directions in crisis response systems.

2. TraceAll: A Real-Time Processing for Contact Tracing Using Indoor Trajectories

📚 Authors: Louai Alarabi, S. Basalamah, A. Hendawi, Mohammed Abdalla
📘 Journal: Information (Vol. 12, No. 5, 2021)
📈 Citations: 21
📄 Summary:
This study presents TraceAll, an innovative real-time contact tracing system that leverages indoor trajectory data to identify potential exposure events. It uses spatial indexing and real-time analytics to provide fast and scalable tracing, crucial during health crises like COVID-19. The paper discusses system architecture, algorithms, and a deployment case study, demonstrating its effectiveness in high-density areas.

3. DeepMotions: A Deep Learning System for Path Prediction Using Similar Motions

📚 Authors: Mohammed Abdalla, Abdeltawab Hendawi, Hoda M.O. Mokhtar, Neveen ElGamal
📘 Journal: IEEE Access, 2020
📈 Citations: 16
📄 Summary:
DeepMotions is a path prediction framework that applies deep learning to movement data, identifying similar motion patterns to predict future trajectories of moving objects. It integrates convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to model spatial-temporal patterns. Applications range from pedestrian prediction to intelligent transportation systems.

4. FraudMove: Fraud Drivers Discovery Using Real-Time Trajectory Outlier Detection

📚 Authors: E.O. Eldawy, A. Hendawi, Mohammed Abdalla, Hoda M.O. Mokhtar
📘 Journal: ISPRS International Journal of Geo-Information (Vol. 10, No. 11, Article 767, 2021)
📈 Citations: 13
📄 Summary:
FraudMove introduces a real-time framework for detecting fraudulent behavior based on vehicle movement anomalies. Using trajectory outlier detection, the system identifies unexpected routes or suspicious driving patterns that may indicate fraud, such as in ride-sharing or insurance claims. The framework blends spatio-temporal clustering and machine learning models for accurate fraud detection.

5. HarmonyMoves: A Unified Prediction Approach for Moving Object Future Path

📚 Authors: Mohammed Abdalla, Hoda M.O. Mokhtar
📘 Journal: International Journal of Advanced Computer Science and Applications, pp. 637–644, 2020
📈 Citations: 7
📄 Summary:
This research proposes HarmonyMoves, a hybrid model that integrates historical trajectory data with environmental context to predict the future paths of moving entities (e.g., vehicles, pedestrians). Unlike previous models that relied solely on movement data, this approach harmonizes contextual and historical data for robust, real-time trajectory prediction.

Conclusion

Dr. Mohammed Abdalla’s contributions meet and exceed the standards typically required for Best Paper Awards at prestigious conferences and journals. His research is characterized by technical innovation, interdisciplinary applications, practical impact, and high citation potential. He is especially commendable for producing systems that combine machine learning with real-world problem solving, such as contact tracing and mobility analytics.

Prof. Dr .Gianluigi Bacchetta | Botanica | Lifetime achievement Award

Posted on 22/05/202522/05/2025 by Research Scientist

Prof. Dr .Gianluigi Bacchetta | Botanica | Lifetime achievement Award

Director , University of Cagliari , Italy

🌿 Professor Gianluigi Bacchetta is an internationally renowned botanist and conservation biologist 🌍. Currently a full professor at the University of Cagliari 🇮🇹, he also serves as an adjunct professor at the University of Tehran 🇮🇷. He directs the Conservation Centre of Biodiversity and the Germplasm Bank of Sardinia 🌱. With over 700 publications 📚 and global collaborations, Bacchetta has made remarkable contributions to Mediterranean biodiversity research 🌸. He is an editor, reviewer, and project leader in several international conservation initiatives 🌐, making a lasting impact on plant science and ecosystem protection 🏞️.

Professional Profile

GOOGLE SCHOLAR

SCOPUS

Education & Experience

🎓 Gianluigi Bacchetta earned his degree in Life Sciences in 1996 🧬, followed by multiple master’s degrees in Landscape Planning (1997) 🗺️ and Vegetation Analysis (2000) 🌳. He completed his PhD in Geomorphology and Geobotany in 2000 🪨, and later achieved a European PhD in Plant Biology from the University of Valencia 🇪🇸. His academic career includes roles from Lecturer to Full Professor at the University of Cagliari 🏛️. He served as director of Hortus Botanicus Karalitanus 🌺 and now leads major biodiversity and germplasm conservation centers in Sardinia 🌾.

Professional Development

🔬 Prof. Bacchetta has evolved through diverse academic and leadership roles in botany, ecology, and conservation 🌲. As editor of Plant Sociology and associate editor for several journals 📖, he actively shapes scientific communication 🌐. His role in doctoral education as deputy director of a PhD program 🎓, along with memberships in international scientific councils 🌍, showcases his dedication to professional excellence. He has authored 24 scientific books 📘 and mentors upcoming researchers. As president of GENMEDA and leader of multiple EU-funded projects 💡, Bacchetta exemplifies continuous professional growth and collaborative leadership 🌱.

Research Focus

🧪 Prof. Bacchetta’s research specializes in plant diversity, conservation biology, geobotany, and Mediterranean ecosystem studies 🌿. His work encompasses phytoclimatology, phytogeography, and island plant biodiversity 🏝️. He leads germplasm conservation efforts 🌾, with a focus on endemic and endangered Mediterranean species 🏵️. His integrative studies connect vegetation science with climate, soil, and land use patterns 🌍. The outcomes support environmental planning and ecological restoration 🔄. With emphasis on genetic resource preservation and sustainable development 🌱, Bacchetta’s research bridges field biology, conservation policy, and ecosystem services 🏞️.

Awards & Honors

🏅 Prof. Bacchetta has received national and international recognition for his work in plant biodiversity and conservation biology 🌍. He has led prestigious European projects such as LIFE+, Interreg, and Erasmus+ 🌐. As president of GENMEDA and deputy president of the CBNC scientific council 🇫🇷, his leadership is widely respected. He is regularly invited to contribute to international conservation strategies 🌿. His contributions as a reviewer, editor, and academic mentor have earned him high esteem in the global scientific community 📚. His prolific publication record and active collaboration networks are testaments to his exceptional achievements 🥇.

Publication Top Notes

**1. Assessing Eco-Physiological Patterns of Ailanthus altissima (Mill.) Swingle and Differences with Native Vegetation Using Copernicus Satellite Data on a Mediterranean Island**

Authors: F. Marzialetti, V. Lozano, A. Große-Stoltenberg, L. Podda, G. Brundu
Journal: Ecological Informatics, 2025 (Open Access)
DOI/Link: Link not available
Citations: 0
Summary:
This study uses high-resolution Copernicus satellite data to evaluate the eco-physiological behavior of the invasive tree Ailanthus altissima compared to native vegetation on a Mediterranean island. The research highlights significant differences in vegetation indices, phenological traits, and water-use patterns. The findings provide critical insight into the invasive potential of A. altissima and suggest targeted remote-sensing approaches for early detection and management in Mediterranean ecosystems.

2. Functional and Habitat Characteristics Associated with Nativeness, Rarity, and Invasiveness in the Aquatic Vascular Flora of Sardinia

Authors: M. Fois, A. Cuena-Lombraña, J.N. Boyd, L. Podda, G. Bacchetta
Journal: Global Ecology and Conservation, 2025 (Open Access)
DOI/Link: Link not available
Citations: 0
Summary:
This research investigates the ecological traits and habitat preferences of aquatic vascular plants in Sardinia. By analyzing traits linked with nativeness, rarity, and invasiveness, the authors aim to support conservation and management efforts. The study reveals that invasive species tend to exhibit broader ecological tolerances and reproductive strategies, posing threats to native aquatic ecosystems. This functional trait analysis offers a framework for assessing plant behavior in freshwater habitats under changing environmental pressures.

3. Tracing the Emergence of Domesticated Grapevine in Italy

Authors: M. Ucchesu, S. Ivorra, V. Bonhomme, A. Usai, L. Bouby
Journal: PLoS ONE, 2025
DOI/Link: Link not available
Citations: 0
Summary:
This archaeobotanical study employs molecular and morphometric evidence to trace the early domestication of grapevine (Vitis vinifera) in Italy. Through analysis of ancient seeds and plant remains, the authors provide evidence for independent domestication events and early viticulture practices. The interdisciplinary approach connects cultural practices with evolutionary plant biology, offering a new timeline and geographic perspective on grape domestication in the western Mediterranean.

4. The First Inventory of Sardinian Mining Vascular Flora

Authors: M.E. Boi, M. Sarigu, M. Fois, M. Casti, G. Bacchetta
Journal: Plants, 2025 (Open Access)
DOI/Link: Link not available
Citations: 0
Summary:
This paper presents the first systematic inventory of vascular plants in mining areas across Sardinia. Mining landscapes are often biodiversity hotspots due to their unique soil chemistry and disturbance regimes. The study identifies species adapted to metal-rich and degraded soils, including several endemic and threatened taxa. This inventory contributes to ecological restoration planning and highlights the conservation value of post-industrial habitats.

Conclusion

Prof. Gianluigi Bacchetta embodies the values of scientific excellence, global collaboration, and lifelong commitment to biodiversity conservation. His exceptional academic record, mentorship legacy, and leadership in both national and international conservation efforts make him a prime candidate for a Lifetime Achievement Award.

Research Assistant , COMSATS University Islamabad , Pakistan

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1. High Removal Efficiency of Arsenite from Aqueous Solution by Cobalt Ferrite Functionalized Sawdust Driven Activated Carbon

2. Highly Ordered and Uniform Growth of Magnetite Nanoparticles on the Surface of Amberlyst-15: Lead Ions Removal Study

3. Enhanced Role of Flower Shaped Curcumin Loaded ZnO/Ag₂O Nanocomposites for Biological Applications

4. Role of Co and Ni Ferrites in the Fabrication of Saccharum officinarum Bioadsorbents for Removing As(III)

5. Green Hydrothermal Synthesis of Nickel and Zinc-Doped Nickel Ferrite Nanoparticles Using Dalbergiella welwitschii Extracts and Their Biological Studies

6. Effective Remediation of Organic Pollutant Using Musa acuminata Peel Extract-Assisted Iron Oxide Nanoparticles

7. Utilizing T. wallichiana Leaf Extract for the Green Synthesis of Ferrite Nanoparticles: A Novel Approach to Lead Ion Removal

8. Effect of Chemical and Thermal Activation on Texture, Morphology, and Composition of Onion Derived Carbon for Arsenic Adsorption

Conclusion

Assistant Professor , SR University , India

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Assoc. Prof . Zonguldak Bulent Ecevit University , Turkey

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1.Improved Image Denoising Using Wavelet Edge Detection Based on Otsu’s Thresholding

2.Dynamic Viscosity Prediction of Nanofluids Using Artificial Neural Network (ANN) and Genetic Algorithm (GA)

3.Discarding Lifetime Investigation of a Rotation Resistant Rope Subjected to Bending Over Sheave Fatigue

4.The Effect of Hyper Parameters on the Classification of Lung Cancer Images Using Deep Learning Methods

5.Genetic Algorithm-Based Image Reconstruction Applying the Digital Holography Process with the Discrete Orthonormal Stockwell Transform Technique for Diagnosis of COVID-19

6.An Application of Filtered Back Projection Method for Computed Tomography Images

Conclusion

Mr.Ramin Ahadi , University of Cologne , Germany

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Dr . Jafar Razmara , University of Tabriz , Iran

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Alzheimer’s Diagnosis by an Efficient Pipelined Gene Selection Model Based on Statistical and Biological Data Analysis

A Random Forest-Based Predictive Model for Classifying BRCA1 Missense Variants: A Novel Approach for Evaluating the Missense Mutations Effect

Peptide Vaccine Design Against Glioblastoma by Applying Immunoinformatics Approach

Credit Card Fraud Detection Using Hybridization of Isolation Forest with Grey Wolf Optimizer Algorithm

Cancer Treatment Comes to Age: From One-Size-Fits-All to Next-Generation Sequencing (NGS) Technologies

Conclusion:

Mrs Iro Dianellou , Aristotle University of Thessaloniki , greece

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1. Dianellou, I., Noli, F., Kantiranis, N. (2025)

2. Kaptanoglu, I.G., Yusan, S., Kaynar, Ü.H., Aytas, S., Erenturk, A.S., Dianellou, I. (2025)

3. Kyriakidis, F., Dianellou, I., Vollas, A., Alatzoglou, M., Gargoulas, N., Oikonomou, V. (2024)

Conclusion

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Dr. Yavuz Yasul, Ondokuz Mayis University, Turkey

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📈 Professional Development

4. **Role of Co and Ni Ferrites in the Fabrication of Saccharum officinarum Bioadsorbents for Removing As(III)**

5. **Green Hydrothermal Synthesis of Nickel and Zinc-Doped Nickel Ferrite Nanoparticles Using Dalbergiella welwitschii Extracts and Their Biological Studies**

6. **Effective Remediation of Organic Pollutant Using Musa acuminata Peel Extract-Assisted Iron Oxide Nanoparticles**

7. **Utilizing T. wallichiana Leaf Extract for the Green Synthesis of Ferrite Nanoparticles: A Novel Approach to Lead Ion Removal**

**1. Assessing Eco-Physiological Patterns of Ailanthus altissima (Mill.) Swingle and Differences with Native Vegetation Using Copernicus Satellite Data on a Mediterranean Island**