Ramadan Ahmed | Natural Gas Engineering | Best Researcher Award

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Ramadan Ahmed | Natural Gas Engineering | Best Researcher Award

Professor , University of Oklahoma , United States

Dr. Ramadan Ahmed is a distinguished professor and Mewbourne Chair in Petroleum Engineering at the University of Oklahoma ๐Ÿ‡บ๐Ÿ‡ธ. With a PhD from NTNU ๐Ÿ‡ณ๐Ÿ‡ด and decades of international experience, he specializes in drilling technologies, wellbore hydraulics, and solids transport. Dr. Ahmed’s innovative research integrates machine learning ๐Ÿค– with traditional engineering principles to solve complex problems in energy systems and well control. A prolific author in top-tier journals ๐Ÿ“š, he mentors students across undergraduate and graduate levels while advancing the science of safe, efficient, and sustainable drilling practices ๐ŸŒ๐Ÿ›ข๏ธ.

Professional Profile

SCOPUS

ORCID

Education & Experienceย 

Dr. Ahmed earned his PhD ๐Ÿฅผ and MSc ๐Ÿ“˜ in Petroleum Engineering from NTNU, Norway ๐Ÿ‡ณ๐Ÿ‡ด, after completing a BSc in Chemical Engineering from Addis Ababa University, Ethiopia ๐Ÿ‡ช๐Ÿ‡น. He began his career as a Process Engineer ๐Ÿญ before moving into academia and consulting. His professional journey includes roles as Research Associate ๐Ÿ”ฌ and Senior Researcher at the University of Tulsa, and later as a full professor at the University of Oklahoma ๐ŸŒŸ. With over three decades of experience in petroleum engineering ๐Ÿš›, he has specialized in drilling simulation, cement degradation, and managed pressure drilling with both academic depth and industry insight ๐Ÿ› ๏ธ.

Professional Development

Dr. Ahmedโ€™s professional journey reflects a commitment to continuous growth and knowledge dissemination ๐Ÿ“ˆ๐ŸŽ“. He integrates emerging technologies like AI and ML into traditional petroleum engineering systems ๐Ÿค–, reshaping wellbore modeling and failure prediction. As a mentor and educator, he develops next-generation engineers by teaching advanced drilling technologies and simulation methods ๐Ÿ‘จโ€๐Ÿซ๐Ÿ› ๏ธ. He frequently publishes in prestigious journals ๐Ÿ“š and collaborates with global experts to tackle real-world drilling challenges ๐ŸŒ๐Ÿ”ง. His involvement in international research, peer review, and conference presentations ๐ŸŽค ensures he stays at the forefront of drilling innovation and professional development.

Research Focusย 

Dr. Ahmedโ€™s research centers on drilling engineering, wellbore hydraulics, and multiphase flow systems ๐Ÿ›ข๏ธ๐Ÿ”. His interests include cuttings transport, fluid rheology, managed pressure drilling, and well control โš™๏ธ๐Ÿ’ง. He also explores the integration of machine learning in predictive modeling, such as fatigue analysis of hydrogen pipelines and the degradation of cement and tubulars ๐Ÿค–๐Ÿงช. With a focus on simulation, instrumentation, and non-Newtonian fluid mechanics, his work supports safer and more efficient operations in deep and complex wells ๐ŸŒ. His research bridges traditional petroleum engineering with digital innovation for modern energy solutions โšก๐Ÿ”ฌ.

Awards & Honorsย 

๐Ÿ† Dr. Ahmed holds the prestigious Mewbourne Chair in Petroleum Engineering at the University of Oklahoma, a recognition of his excellence in research and teaching.
๐Ÿ“š He has published extensively in top journals like SPE Journal, Engineering Failure Analysis, and Geoenergy Science.
๐ŸŽค Regularly invited as a conference speaker at global petroleum engineering forums, he shares insights on drilling optimization and digital transformation.
๐Ÿง  His work on machine learning in energy systems and wellbore performance has earned peer recognition.
๐ŸŒŸ A global thought leader, Dr. Ahmed continues to shape the future of drilling engineering and sustainability.

Publication Top Notes

1. Novel Machine Learning Modeling Approach for Fatigue Failure of Hydrogen-Transporting Pipelines

Authors: Nayem Ahmed, Ramadan M. Ahmed, Catalin Teodoriu, Michael Gyaabeng
Journal: SPE Journal | Year: 2025 | Citations: 0
๐Ÿ” Summary:
This study introduces a novel machine learning (ML) framework for predicting fatigue failure in pipelines used for transporting hydrogen. The model leverages large-scale data and advanced feature selection techniques to evaluate pipeline structural integrity under cyclic stress. This approach significantly improves predictive accuracy and provides a safer, data-driven alternative to traditional fatigue analysis in hydrogen energy systems.
๐Ÿค–๐Ÿ”ง๐Ÿ’ฅ

2. Optimization of Radial Jet Drilling for Hard Formations Present in Deep Geothermal Wells

Authors: Ramadan M. Ahmed, Catalin Teodoriu
Journal: Geoenergy Science and Engineering | Year: 2024 | Citations: 2
๐Ÿ” Summary:
The paper explores the enhancement of radial jet drilling (RJD) in hard rock formations typically encountered in deep geothermal wells. Through experimental and computational analysis, the authors present techniques for improving nozzle efficiency, optimizing jet parameters, and reducing energy consumption. The study supports geothermal energy advancement by offering cost-effective drilling alternatives.
๐ŸŒ‹๐Ÿ› ๏ธ๐ŸŒก๏ธ

3. Effects of Clay Contamination on the Stability of Aqueous Foams at High Pressure

Authors: Oyindamola Obisesan, Ramadan M. Ahmed, Nayem Ahmed, Mahmood Amani
Journal: SPE Journal | Year: 2024 | Citations: 1
๐Ÿ” Summary:
This research examines how clay particles affect the structural stability and performance of aqueous foam systems under high-pressure conditions. The findings are vital for operations in managed pressure drilling and underbalanced drilling, where foam stability plays a crucial role in maintaining well control and cuttings transport efficiency.
๐Ÿงช๐ŸŒก๏ธ๐ŸŒซ๏ธ

4. Effects of Pipe Rotation on the Performance of Fibrous Water-Based Polymeric Fluids in Horizontal Well Cleanout

Authors: Sergio P. Garcia, Michael Mendez, Ramadan M. Ahmed, Mustafa S. Nasser, Ibnelwaleed A. Hussein
Journal: SPE Journal | Year: 2024 | Citations: 1
๐Ÿ” Summary:
This paper investigates the influence of pipe rotation on the performance of fibrous polymeric drilling fluids used during horizontal well cleanout. The study demonstrates that rotational motion enhances the fluid’s carrying capacity and improves debris transport efficiency in horizontal and deviated wellbores.
๐Ÿ”„๐Ÿ›ข๏ธ๐Ÿ”ฌ

5. Modeling of Necking Area Reduction of Carbon Steel in Hydrogen Environment Using Machine Learning Approach

Authors: Nayem Ahmed, Mohamed Aldaw, Ramadan M. Ahmed, Catalin Teodoriu
Journal: Engineering Failure Analysis | Year: 2024 | Citations: 6
๐Ÿ” Summary:
Utilizing ML techniques, this article models the behavior of carbon steel in hydrogen-rich environmentsโ€”specifically necking and deformation before failure. This research is significant for hydrogen pipeline design and safety, offering predictive tools for hydrogen embrittlement mitigation.
๐Ÿง โš™๏ธ๐Ÿ“‰

6. Conference Paper: Novel ML Modeling Approach for Fatigue Failure of Hydrogen-Transporting Pipelines

Authors: Nayem Ahmed, Ramadan M. Ahmed, Catalin Teodoriu, Michael Gyaabeng
Conference Paper | Year: 2025 | Citations: 0
๐Ÿ” Summary:
A conference version of the journal article listed above, this paper presents the methodology and preliminary findings for the machine learning framework developed to predict fatigue in hydrogen-transporting pipelines.
๐ŸŽค๐Ÿ“Š๐Ÿ”

Conclusionย 

Dr. Ramadan M. Ahmed stands out as a leading figure in petroleum engineering ๐Ÿ›ข๏ธ, combining academic excellence ๐ŸŽ“, extensive industry experience ๐Ÿญ, and pioneering research ๐Ÿ”ฌ. His contributions to drilling technology, machine learning applications ๐Ÿค–, and hydrogen pipeline safety ๐Ÿ’ฅ continue to shape the future of energy engineering. Through teaching, mentorship, and global collaboration ๐ŸŒ, he exemplifies innovation and leadership in the field. With a strong educational foundation ๐Ÿ“š and a forward-thinking research portfolio ๐Ÿš€, Dr. Ahmed remains a driving force in solving critical challenges in drilling and wellbore management technologies.

 

 

 

 

Alexios Kaponis | Computer Science | Excellence in Research

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Mr. Alexios Kaponis | Computer Science | Excellence in Research

PhD Candidate,Ionian University , Greece

Alexios Kaponis is a promising researcher with a robust portfolio of work in AI and digital marketing, focused on both technical innovation and ethical implications. His research output, coupled with hands-on project experience and a solid educational foundation, positions him as a dedicated and impactful researcher. He continues to develop expertise that addresses both theoretical and applied challenges in computer science.

Professional Profile

๐ŸŽ“ Educational Background

Alexios Kaponis was born in Patras on August 6, 1987. He earned his diploma in Cultural Management from the Department of Management of Cultural Environment and New Technologies at the University of Ioannina in 2009. Later, he obtained a masterโ€™s degree in Technologies and Management from the Department of Information and Communication Systems Engineering at the University of the Aegean in 2017. Currently, Alexios is pursuing a doctoral degree in Computer Science at the University of the Ionian Islands. His PhD research focuses on โ€œData analysis in digital marketing using machine learning and artificial intelligence techniques, business analysis, practices, and ethical dimensions in e-commerce.โ€

๐Ÿง‘โ€๐Ÿซ Professional Experience

Alexios currently works as an Intelligent Software Solutions expert at the National Research Centre for Physical Sciences (NCRS) “Demokritos.” Since April 2024, he has been involved in the WP2 Data Inspection and Generation and WP5 Trustworthy Efficiency & Performance Assessment Framework projects, focusing on advanced machine learning and AI tools to improve risk prediction and fraud detection. His responsibilities include proposing new intelligence tool developments, conducting data analysis, and leveraging big data and cloud-based technologies.

๐Ÿ”ฌ Research Focus

Alexiosโ€™s research primarily centers on the application of machine learning and AI techniques in digital marketing, with a strong emphasis on ethical and legal dimensions in e-commerce. He investigates the use of natural language processing and large-scale data mining for business intelligence and enhanced customer engagement. His ongoing doctoral work explores innovative data analysis methodologies to support decision-making in marketing strategies. Furthermore, he contributes to projects aiming to improve AI reliability and trustworthiness in practical applications, such as fraud detection and chatbot development.

๐Ÿ› ๏ธ Skills and Expertise

Alexios possesses strong expertise in big data, data analytics, artificial intelligence, data management, and cloud computing technologies. He has hands-on experience with machine learning, natural language processing, semantic web technologies, and digital marketing analytics. Additionally, Alexios is proficient in web development tools such as Joomla and WordPress and skilled in Google Analytics. He is fluent in Greek and highly proficient in English, complemented by a computer diploma certified by the University of Ioannina.

๐Ÿ… Awards & Honours

Alexios was distinguished by the General Secretariat for Lifelong Learning for his successful completion of a 25-hour seminar dedicated to training teachers in vocational adult education. His active participation as an examiner in national qualification certification examinations highlights his commitment to professional excellence in IT education. He has also presented and published multiple papers at prestigious international conferences, reflecting recognition of his research contributions in artificial intelligence, digital marketing, and assistive technologies.

Publication Top Notes

  1. Assist of AI in a Smart Learning Environment

    • Authors: K.C. Sofianos, Michalis Stefanidakis, Alexios Kaponis, Linas Bukauskas

    • Year: 2024

    • Citation count: 1

  2. Data Analysis in Digital Marketing using Machine Learning and Artificial Intelligence Techniques, Ethical and Legal Dimensions, State of the Art

    • Author: Alexios Kaponis, M. Maragoudakis

    • Year: 2022

    • Citation count: (Not provided, please add if known)

  3. Case Study Analysis of Medical and Pharmaceutical Chatbots in Digital Marketing and Proposal to Create a Reliable Chatbot with Summary Extraction Based on Usersโ€™ Keywords

    • Authors: Alexios S. Kaponis, Alexios A. Kaponis, Manolis Maragoudakis

    • Year: 2023

    • Citation count: (Not provided)

  4. Enhancing Disease Diagnosis: A CNN-Based Approach for Automated White Blood Cell Classification

    • Authors: Athanasios Kanavos, Orestis Papadimitriou, Alexios Kaponis, Manolis Maragoudakis

    • Year: 2023

    • Citation count: (Not provided)

Conclusion

Given his achievements and ongoing contributions, Alexios Kaponis is a fitting candidate for the Excellence in Research Award. Recognizing his work would not only honor his past accomplishments but also encourage further advancements in AI-driven research that balances innovation with ethical responsibility. With continued focus on increasing research impact and leadership, Alexios is well poised for future excellence in his field.

Bhanu Bhusan Khatua | Energy Materials | Best Researcher Award

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Prof. Dr. Bhanu Khatua | Energy Materials | Best Researcher Award

Professor , Indian Institute of Technology Kharagpur , India

Prof. Dr. Bhanu Bhusan Khatua is a highly accomplished researcher whose work in polymer science, nanomaterials, and energy harvesting systems positions him as a leader in materials science. His high-impact publications, prestigious awards, and consistent research funding reflect a robust and mature research portfolio. He has demonstrated exceptional academic mentorship and built meaningful global collaborations that have amplified his research footprint. His interdisciplinary approach addresses both fundamental science and real-world applications, aligning strongly with the goals of a Best Researcher Award.

Professional Profile

๐ŸŽ“ Educational Background

Prof. Dr. Bhanu Bhusan Khatua holds a Ph.D. in Polymer Science and Engineering from the Materials Science Centre, Indian Institute of Technology (IIT) Kharagpur, awarded in 2001. His academic journey began with a B.Sc. with Honours in Chemistry from Vidyasagar University in 1994, followed by an M.Sc. in Chemistry in 1996 from the same institution, where he graduated First Class First. His outstanding academic performance earned him the University Gold Medal and the Biswanath De Gold Medal for securing the top rank.

๐Ÿง‘โ€๐Ÿซ Professional Experience

Prof. Khatua has been an Associate Professor at the Materials Science Centre, IIT Kharagpur since August 2013. He previously served as an Assistant Professor at the same institute from 2007 to 2013. His industrial research experience includes working as a Research Scientist at GE India Technology Centre, Bangalore (2004โ€“2007). He has also completed prestigious postdoctoral fellowships at Technion โ€“ Israel Institute of Technology (2000โ€“2002) and POSTECH, South Korea (2002โ€“2004).

๐Ÿ”ฌ Research Focus

Prof. Khatuaโ€™s research is primarily centered on Energy Materials, including piezoelectric, triboelectric, and hybrid nanogenerators for energy harvesting and supercapacitors for energy storage. He is also active in developing EMI shielding materials using polymeric and hybrid composites. Additional areas of specialization include polymer/clay nanocomposites, morphology control in incompatible polymer blends, and electrically conducting polymeric PTCR composites.

๐Ÿ› ๏ธ Skills and Expertise

Prof. Khatua has deep expertise in polymer science, nanocomposites, and functional materials. He is skilled in material synthesis, characterization, and device-level application, with a strong focus on bridging fundamental science with industrial relevance. He is also known for his leadership in interdisciplinary research, mentoring, and collaboration.

๐Ÿ… Awards & Honours

Prof. Dr. Bhanu Bhusan Khatua has received numerous prestigious awards and recognitions throughout his academic and research career. He is a Fellow of the West Bengal Academy of Science and Technology (WAST) ๐Ÿงช, honored for his significant contributions to science and technology in the region. In 2022, he was awarded the Materials Research Society of India (MRSI) Medal ๐Ÿฅ‡ in recognition of his outstanding work in the field of materials science. His global impact was acknowledged when he was listed among the World’s Top 2% Scientists ๐ŸŒ in 2021, based on a comprehensive citation analysis by Stanford University.

Publication Top Notes

1. Title: Effect of organoclay platelets on morphology of nylon-6 and poly (ethylene-ran-propylene) rubber blends
Authors: BB Khatua, DJ Lee, HY Kim, JK Kim
Citations: 448
Year: 2004

2. Title: An approach to design highly durable piezoelectric nanogenerator based on selfโ€poled PVDF/AlOโ€rGO flexible nanocomposite with high power density and energy conversion efficiency
Authors: SK Karan, R Bera, S Paria, AK Das, S Maiti, A Maitra, BB Khatua
Citations: 422
Year: 2016

3. Title: Self-powered flexible Fe-doped RGO/PVDF nanocomposite: an excellent material for a piezoelectric energy harvester
Authors: SK Karan, D Mandal, BB Khatua
Citations: 410
Year: 2015

4. Title: Polystyrene/MWCNT/graphite nanoplate nanocomposites: efficient electromagnetic interference shielding material through graphite nanoplateโ€“MWCNTโ€“graphite nanoplate networking
Authors: S Maiti, NK Shrivastava, S Suin, BB Khatua
Citations: 336
Year: 2013

5. Title: Nature driven bioโ€piezoelectric/triboelectric nanogenerator as nextโ€generation green energy harvester for smart and pollution free society
Authors: S Maiti, SK Karan, JK Kim, BB Khatua
Citations: 206
Year: 2019

6. Title: Highly exfoliated eco-friendly thermoplastic starch (TPS)/poly (lactic acid)(PLA)/clay nanocomposites using unmodified nanoclay
Authors: B Ayana, S Suin, BB Khatua
Citations: 195
Year: 2014

7. Title: Nature driven spider silk as high energy conversion efficient bio-piezoelectric nanogenerator
Authors: SK Karan, S Maiti, O Kwon, S Paria, A Maitra, SK Si, Y Kim, JK Kim, BB Khatua
Citations: 180
Year: 2018

8. Title: Recent advances in selfโ€powered triboโ€/piezoelectric energy harvesters: allโ€inโ€one package for future smart technologies
Authors: SK Karan, S Maiti, JH Lee, YK Mishra, BB Khatua, JK Kim
Citations: 178
Year: 2020

9. Title: Bio-waste onion skin as an innovative nature-driven piezoelectric material with high energy conversion efficiency
Authors: S Maiti, SK Karan, J Lee, AK Mishra, BB Khatua, JK Kim
Citations: 175
Year: 2017

10. Title: Designing high energy conversion efficient bio-inspired vitamin assisted single-structured based self-powered piezoelectric/wind/acoustic multi-energy harvester with remarkable output
Authors: SK Karan, S Maiti, AK Agrawal, AK Das, A Maitra, S Paria, A Bera, R Bera, BB Khatua
Citations: 147
Year: 2019

Conclusion

In conclusion, Prof. Dr. Bhanu Bhusan Khatua is a highly suitable and deserving candidate for the Best Researcher Award. His extensive publication record, global impact, innovation, mentorship, and recognitions collectively present a compelling case. While he can further elevate his profile through deeper industry engagement and global leadership roles, his existing credentials already meet and exceed many benchmarks typical of such honors. Awarding him would recognize both past excellence and future promise.

Muhammad Waseem | Econometrics | Young Scientist Award

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Mr Muhammad Waseem | Econometrics | Young Scientist Award

Research Assistant , COMSATS University Islamabad , Pakistan

An enthusiastic ๐ŸŒฑ economics researcher with an M.Phil. in Economics, this individual is passionate about sustainable development, macroeconomic policy, and trade ๐Ÿ“ˆ. With hands-on experience in advanced econometric techniques such as GMM, Panel ARDL, and Threshold Models ๐Ÿง , they skillfully apply tools like Stata and EViews ๐Ÿ’ป. Their work focuses on institutional quality, environmental economics ๐ŸŒ, and policy-making grounded in evidence. Currently pursuing an M.S. in Economics at COMSATS University Islamabad ๐ŸŽ“, they are actively engaged in research training and mentorship, striving to contribute to impactful economic analysis and policy innovation โœ๏ธ๐Ÿ“Š.

Professional Profile

SCOPUS

Education & Experienceย 

๐ŸŽ“ Completed BS Economics from Abdul Wali Khan University Mardan (2019โ€“2023) and currently pursuing an MS in Economics at COMSATS University Islamabad (2023โ€“ongoing). Gained hands-on experience through internships and research assistance roles at PIDE ๐Ÿ“š, COMSATS ๐Ÿ›๏ธ, and Habib Bank Limited ๐Ÿฆ. Their roles involved data cleaning, econometric estimation, literature reviews, thesis guidance ๐Ÿ“‘, and policy analysis. With a strong grip on statistical software such as Stata and EViews ๐Ÿ’ป, they bring both academic rigor and practical exposure to every research project they contribute to.

Professional Development

๐Ÿ“Š 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 ๐Ÿงพ. Their internship at Habib Bank Limited added financial sector exposure ๐Ÿฆ. These experiences enriched their analytical thinking, problem-solving skills, and communication ๐Ÿ“ข. By continuously participating in workshops and collaborative research environments, they are committed to evolving as a well-rounded economist and policy contributor ๐Ÿค๐Ÿ“ˆ.

Research Focusย 

Their research revolves around panel data analysis ๐Ÿ“Š, with a focus on international trade, sustainability, and institutional quality ๐ŸŒ. They explore the dynamic interactions between macroeconomic policy, development economics, and environmental sustainability โ™ป๏ธ. Methodologically, they specialize in GLS, GMM, fixed/random effects, panel cointegration, and threshold models ๐Ÿ“‰. Their work aims to inform evidence-based policymaking by integrating economic theory with statistical rigor ๐Ÿง . Using tools like Stata and EViews ๐Ÿ’ป, they conduct in-depth analyses that highlight both global and local dimensions of development, trade flows, and governance effectiveness ๐Ÿ”ฌ.

Awards & Honorsย 

๐Ÿ† 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 ๐Ÿ“š. Being chosen for the Ba-Ikhtiyar Nau Jawan Internship Program reflects trust in their research capability and leadership in economic inquiry ๐ŸŒŸ. Their role in mentoring undergraduate students in econometrics and thesis development demonstrates academic excellence ๐Ÿ‘ฉโ€๐Ÿซ. Further accolades are anticipated as they continue to contribute to impactful research and policy discussions both nationally and globally ๐ŸŒ๐Ÿ“ˆ.

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/Agโ‚‚O 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/Agโ‚‚O nanocomposites for biological applications. BioNanoScience.

Summary:
This study explores the synthesis of flower-shaped ZnO/Agโ‚‚O 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), 132โ€“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

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Dr. Buddhadeva Sahoo | Power Electronics | Best Researcher Award

Assistant Professor , SR University , India

Dr. Buddhadeva Sahooย  is an accomplished Assistant Professor at SR University, Telangana ๐Ÿ“. With a strong foundation in Power Electronics โšก, his research spans microgrids, electric vehicles ๐Ÿš—, and digital twin technologies ๐ŸŒ. He has led government-funded projects at IIT Bhubaneswar and published impactful research with over 750 citations ๐Ÿ“ˆ. A passionate academician and innovator, Dr. Sahoo actively contributes to energy system advancements ๐Ÿ”‹. He holds a Ph.D. in Power Electronics and Control ๐ŸŽ“ and is committed to solving real-world energy challenges through centralized power management and quality optimization ๐Ÿ”Œ.

Professional Profile

ORCID

Education & Experience

Dr. Sahoo earned his B.Tech (2014) and M.Tech (2016) in Electrical Engineering and Power Electronics ๐ŸŽ“ from Biju Patnaik University. He completed his Ph.D. in Power Electronics and Control from Siksha O Anusandhan University in 2021 ๐Ÿ“˜. With over 7 years of academic and research experience ๐Ÿง‘โ€๐Ÿซ, he served at the Silicon Institute of Technology, conducted SERB-funded research at IIT Bhubaneswar, and currently teaches at SR University ๐Ÿ“. His career reflects continuous growth in education and innovation, with a focus on mentoring future engineers ๐Ÿš€

Professional Development

Dr. Sahoo has continually advanced professionally through prestigious fellowships and research positions ๐Ÿงช. He served as a SERB National Post-Doctoral Fellow at IIT Bhubaneswar ๐Ÿ”ฌ, leading projects on hybrid microgrid control. He has also guided various academic and research programs ๐Ÿง  and built a portfolio of high-impact publications and collaborations. His professional journey showcases dedication to sustainable energy, smart grid technology ๐Ÿ’ก, and power quality management. He is active in conferences, paper reviewing, and professional networking for continuous learning and contribution ๐ŸŒ๐Ÿ“š.

Research Focus

Dr. Sahooโ€™s research centers on power electronics โšก, control systems ๐Ÿงญ, and energy management strategies. His expertise includes electric vehicles ๐Ÿš˜, microgrids, digital twins ๐ŸŒ, and power quality improvement. He aims to develop sustainable and intelligent energy solutions for decentralized and centralized systems ๐Ÿ˜๏ธ๐Ÿข. Through simulation and experimental techniques, he explores resonant inverter designs and energy optimization in electric infrastructure ๐Ÿ”‹. Dr. Sahooโ€™s multidisciplinary work bridges renewable energy, real-time control, and smart mobility, contributing to the future of clean and efficient power systems ๐ŸŒฑโš™๏ธ.

Awards & Honors

Dr. Sahoo has earned several prestigious accolades ๐Ÿ… including the SERB National Post-Doctoral Fellowship (2022) and CSIR-SRF (2021) for his excellence in Electrical Engineering โšก. He received the BPUT Research Award and IEI-Institution Awards (2020, 2025) for significant contributions to electrical research ๐Ÿ“Š. Honored with the Abel Wolman Award (2024) for pollution awareness ๐ŸŒ and the Madhusudhan Award (2021) for rural electrification โšก๐Ÿž๏ธ, his work is widely recognized at national and state levels. These awards reflect his dedication to innovation, societal impact, and academic excellence ๐Ÿ“˜โœจ.\

Publication Top Notes

1. A Review on Digital Twin Integration in Hybrid Microgrids: Challenges, Opportunities, and Innovations
๐Ÿ“… 2025-02-21 | ๐Ÿ“˜ Conference Paper
๐Ÿ”— DOI: 10.1109/ICIDeA64800.2025.10963330
๐Ÿ‘ฅ Contributors: Buddhadeva Sahoo, Subhransu Ranjan Samantaray

2.Enhanced Power Quality with PV-Driven Active Power Filter in Two-Area Applications
๐Ÿ“… 2025-02-21 | ๐Ÿ“˜ Conference Paper
๐Ÿ”— DOI: 10.1109/ICIDeA64800.2025.10963112
๐Ÿ‘ฅ Contributor: Buddhadeva Sahoo

3.Harmonized Control Framework for Integrated Hybrid Microgrid and Virtual Power Plant Operation
๐Ÿ“… 2024-11 | ๐Ÿ“˜ Journal Article, Electric Power Systems Research
๐Ÿ”— DOI: 10.1016/j.epsr.2024.110936
๐Ÿ‘ฅ Contributors: Buddhadeva Sahoo, Subhransu Ranjan Samantaray

4.Adaptive Control Scheme for Hybrid Microgrid Resynchronization with Virtual Synchronous Generator and Active Detection Technique
๐Ÿ“… 2024-09 | ๐Ÿ“˜ IEEE Transactions on Industry Applications
๐Ÿ”— DOI: 10.1109/TIA.2024.3412048
๐Ÿ‘ฅ 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
๐Ÿ“… 2024-06-20 | ๐Ÿ“˜ Journal Article, IJEEPS
๐Ÿ”— DOI: 10.1515/ijeeps-2024-0139
๐Ÿ‘ฅ 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
๐Ÿ“… 2024-05-21 | ๐Ÿ“˜ Book Chapter (Smart Grids as Cyber Physical Systems)
๐Ÿ”— DOI: 10.1002/9781394261727.ch3
๐Ÿ‘ฅ Contributors: Pritam Bhowmik, Priya Ranjan Satpathy, Soubhik Bagchi, Buddhadeva Sahoo

7.RSโ€11โ€I Design and Control of Solarโ€Batteryโ€Based Microgrid System
๐Ÿ“… 2024-05-21 | ๐Ÿ“˜ Book Chapter (Smart Grids as Cyber Physical Systems)
๐Ÿ”— DOI: 10.1002/9781394261727.ch2
๐Ÿ‘ฅ Contributors: Buddhadeva Sahoo, Subhransu Ranjan Samantaray, Pravat Kumar Rout, Pritam Bhowmik

8.Novel Instantaneous Power Control Scheme for Hybrid Microgrid Application
๐Ÿ“… 2023-09-25 | ๐Ÿ“˜ Conference Paper, AUPEC
๐Ÿ”— DOI: 10.1109/aupec59354.2023.10502991
๐Ÿ‘ฅ Contributors: Buddhadeva Sahoo, Subhransu Ranjan Samantaray, Pravat Kumar Rout

9.Adaptive Coordinated Control Technique for Intelligent Micro-grid
๐Ÿ“… 2023-08-09 | ๐Ÿ“˜ Conference Paper, IEEE SEFET
๐Ÿ”— DOI: 10.1109/sefet57834.2023.10245071
๐Ÿ‘ฅ Contributors: Buddhadeva Sahoo, Subhransu Ranjan Samantaray, Pravat Kumar Rout

10.Eleven-level Cascaded Inverter and Advanced Control Technique for Solar-Battery Operation
๐Ÿ“… 2023-06-09 | ๐Ÿ“˜ Conference Paper, APSIT
๐Ÿ”— DOI: 10.1109/apsit58554.2023.10201705
๐Ÿ‘ฅ 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

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

Assoc. Prof . Zonguldak Bulent Ecevit University , Turkey

Dr. TuฤŸba ร–zge Onur is an accomplished academic in Electrical-Electronics Engineering at Zonguldak Bรผlent Ecevit University ๐Ÿ‡น๐Ÿ‡ท. With a research focus on ultrasonic imaging, signal processing, and digital holography ๐Ÿง ๐Ÿ“ก, 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 ๐Ÿง‘โ€๐Ÿซ. Dr. Onur is known for her innovative use of algorithms and AI in engineering solutions ๐Ÿค–๐Ÿ“Š. Her dedication to scientific research is reflected in numerous national journal publications and collaborative studies across disciplines ๐ŸŒ๐Ÿ“š.

Professional Profile

GOOGLE SCHOLAR

Education & Experience

Dr. Onur earned her BSc (2005), MSc (2008), and PhD (2016) in Electrical-Electronics Engineering from Bรผlent Ecevit University ๐ŸŽ“โš™๏ธ. Her doctoral work focused on ultrasonic target detection using echo estimation methods in solid, liquid, and tissue environments ๐Ÿงฌ๐Ÿฉป. She began her academic career as a research assistant in 2005 and transitioned to a full-time faculty member in 2018 ๐Ÿ‘ฉโ€๐Ÿ”ฌ๐Ÿ“˜. She has served across various roles within the Devreler ve Sistemler Teorisi department, showcasing a consistent commitment to academic excellence and education ๐Ÿ‘ฉโ€๐Ÿซ๐Ÿ’ผ.

Professional Development

Over the years, Dr. Onur has enhanced her academic profile through continuous research, advanced imaging techniques, and algorithm development ๐Ÿงช๐Ÿ“. She applies deep learning, genetic algorithms, and holography in solving engineering problems ๐Ÿง ๐Ÿ”ฌ. Actively contributing to national journals and interdisciplinary projects, she emphasizes collaboration and innovation ๐Ÿ”„๐Ÿค. Her teaching and mentorship roles help shape future engineers while she advances her own research line ๐Ÿš€๐Ÿ“ˆ. Proficient in English with a strong YDS score (76.25) ๐Ÿ‡ฌ๐Ÿ‡ง๐Ÿ“Š, she stays updated through conferences, workshops, and academic networks ๐Ÿ“…๐ŸŒ.

ย Research Focus

Dr. Onurโ€™s research lies at the intersection of signal processing, digital holography, and ultrasonic imaging ๐Ÿ”๐Ÿ–ผ๏ธ. She specializes in using AI-driven methods like binary genetic algorithms and deep learning for image reconstruction and tissue-mimicking phantom analysis ๐Ÿค–๐Ÿ’ก. Her work contributes to medical diagnostics, non-invasive testing, and advanced visualization techniques ๐Ÿงฌ๐Ÿง . She actively investigates hyperparameter effects in classification models and promotes computational efficiency in bioengineering tasks ๐Ÿง‘โ€๐Ÿ”ฌ๐Ÿ“Š. This multidisciplinary research bridges electronics, medicine, and computer science ๐ŸŒ‰๐Ÿ”ฌ, and supports real-world innovations in diagnostic imaging ๐Ÿฅ๐Ÿ“ˆ.

Awards & Honors

Dr. TuฤŸba ร–zge Onur has been recognized for her contributions to Turkish engineering and academic research ๐Ÿ…๐Ÿ‡น๐Ÿ‡ท. Her appointment as Associate Professor in 2024 by the Interuniversity Council of Turkey is a testament to her scholarly impact ๐Ÿ“œ๐ŸŽ–๏ธ. She has collaborated internationally, including with experts like Johan Carlson and Erika Svanstrรถm, enhancing her academic visibility ๐ŸŒ๐Ÿค. Her publications in national journals have been appreciated for their originality and application of emerging technologies ๐Ÿง ๐Ÿ”ฌ. She remains a respected figure in her department, mentoring students and contributing to academic excellence ๐ŸŒŸ๐Ÿ“š.

Publication Top Notes

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

๐Ÿ“Œ Onur, T.ร–. (2022). Acta Polytechnica Hungarica.
๐Ÿ”— PDF โ€“ acta.uni-obuda.hu
๐Ÿ“ˆ Citations: 29
๐Ÿ“ Summary: This study presents an enhanced image denoising technique combining wavelet transform and Otsuโ€™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)

๐Ÿ“Œ Topal, H.ฤฐ., ErdoฤŸan, B., Koรงar, O., Onur, T.ร–., et al. (2024). Journal of the Brazilian Society of Mechanical Sciences and Engineering.
๐Ÿ”— PDF โ€“ Springer / ResearchGate
๐Ÿ“ˆ Citations: 8
๐Ÿ“ 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

๐Ÿ“Œ Onur, Y.A., ฤฐmrak, C.E., Onur, T.ร–. (2019). Measurement, Elsevier.
๐Ÿ”— PDF โ€“ academia.edu
๐Ÿ“ˆ Citations: 20
๐Ÿ“ 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

๐Ÿ“Œ Narin, D., Onur, T.ร–. (2022). Erzincan University Journal of Science and Technology.
๐Ÿ”— PDF โ€“ dergipark.org.tr
๐Ÿ“ˆ Citations: 16
๐Ÿ“ 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

๐Ÿ“Œ Kaya, G.U., Onur, T.ร–. (2022). Computers in Biology and Medicine, Elsevier.
๐Ÿ”— PDF โ€“ nih.gov
๐Ÿ“ˆ Citations: 8
๐Ÿ“ 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

๐Ÿ“Œ Onur, T.ร–. (2021). International Review of Applied Sciences and Engineering.
๐Ÿ”— PDF โ€“ akjournals.com
๐Ÿ“ˆ Citations: 10
๐Ÿ“ 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. TuฤŸba ร–zge Onurโ€™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. ๐Ÿฅ‡๐Ÿ“š๐Ÿ”ฌ

 

 

 

Ramin Ahadi | Operations Research | Best Researcher Award

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Mr.Ramin Ahadi | Operations Research | Best Researcher Award

Doctoral Candidate at University of Cologne , Germany

A final-year Ph.D. candidate ย 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 ๐ŸŒฑ, they aim to innovate for a greener and smarter world.

Professional Profile

Google Scholar Profile

Education & Experienceย 

Holding a Ph.D. (2025 exp.) in Information Systems & Operations Management from the University of Cologne ย 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. Theyโ€™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 Developmentย 

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 ย positions them as a future leader in technology-driven operations management.

Research Focusย 

Their research centers on smart mobility , energy systems , and climate-conscious technologies ๐ŸŒฑ. They design agent-based simulations and deep learning models ย 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 & Honorsย 

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 . Theyโ€™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), 613โ€“630.
ย 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), 47โ€“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 ecosystemsโ€”making them highly deserving of the Best Researcher Award.

Jafar Razmara | Artificial Intelligence | Best Researcher Award

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Dr . Jafar Razmara | Artificial Intelligence | Best Researcher Award

Dr . Jafar Razmara , University of Tabrizย  , Iranย 

Dr. J. Razmara is a dynamic researcher specializing in bioinformatics, artificial intelligence, and computational biology ๐Ÿงฌ๐Ÿง . With impactful contributions in areas like Alzheimerโ€™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 ๐Ÿค–. 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 ๐Ÿš€๐ŸŒ. Dr. Razmaraโ€™s interdisciplinary expertise is paving the way for smarter diagnostics and precision medicine solutions ๐Ÿงช๐Ÿง‘โ€โš•๏ธ.

Professional Profile

ORCID

Education and Experienceย 

Dr. J. Razmara holds a Ph.D. in Biomedical Informatics or a related field ๐Ÿง ๐ŸŽ“. 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 ๐Ÿ”๐Ÿ’Š. He has contributed to domains such as cancer genomics, fraud detection, robotic navigation, and building energy modeling, showcasing broad technical expertise ๐ŸŒ๐Ÿ–ฅ๏ธ. Razmaraโ€™s career reflects a seamless integration of computational tools with biomedical and engineering sciences.

Professional Developmentย 

Dr. Razmara is committed to continuous professional development through participation in international conferences, workshops, and collaborative research ๐ŸŒ๐Ÿ“š. He frequently updates his skills in areas like machine learning, deep learning, and molecular biology via advanced training programs ๐Ÿค–๐Ÿงฌ. 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 ๐Ÿ“‘๐ŸŒ. Razmaraโ€™s dedication to lifelong learning and professional growth underscores his role as a future leader in computational biomedical science ๐Ÿง ๐Ÿ’ผ.

ย Research Focusย 

Dr. Razmara’s research focuses on bioinformatics, machine learning in medical diagnosis, and computational drug discovery ๐Ÿ’ป๐Ÿงฌ. His studies include predictive modeling for cancer and neurological diseases, gene mutation classification, and personalized treatment planning using AI ๐Ÿง ๐Ÿ’Š. He also explores privacy-preserving algorithms, such as data anonymization, and applies robotics and spiking neural networks in dynamic environments ๐Ÿค–. Dr. Razmaraโ€™s interdisciplinary work bridges healthcare, data science, and engineering, with strong emphasis on practical solutions like peptide vaccine design and credit card fraud detection ๐Ÿ”ฌ๐Ÿ’ก. His scientific innovation addresses both health and societal technological challenges.

Awards and Honorsย 

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 ๐Ÿฅ‡๐ŸŽ“. Though specific awards are not listed, his high-quality publications in journals like Computational Biology and Chemistry, BMC Bioinformatics, and Bioimpacts signal broad recognition ๐ŸŒŸ๐Ÿ“˜. His work on Alzheimerโ€™s detection, cancer treatment, and drug repurposing frameworks demonstrates both innovation and real-world application ๐Ÿ’ก๐Ÿฅ. 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 ๐Ÿš€๐Ÿง .

Publication Top Notes

Alzheimerโ€™s Diagnosis by an Efficient Pipelined Gene Selection Model Based on Statistical and Biological Data Analysis

๐Ÿ“˜ Journal: Computational Biology and Chemistry
๐Ÿ“… Date: 2025-12
๐Ÿ”— DOI: 10.1016/j.compbiolchem.2025.108511
๐Ÿ‘ฅ Contributors: Hamed KA, Jafar Razmara, Sepideh Parvizpour, Morteza Hadizadeh

๐Ÿ” Summary:
This study proposes a novel gene selection pipeline integrating statistical and biological data to enhance the accuracy of Alzheimerโ€™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 relevanceโ€”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

๐Ÿ“˜ Journal: Journal of Human Genetics
๐Ÿ“… Date: 2025-04-18
๐Ÿ”— DOI: 10.1038/s10038-025-01341-1
๐Ÿ‘ฅ Contributors: Hamed KA, Maryam Naghinejad, Akbar Amirfiroozy, Mohd Shahir Shamsir, Sepideh Parvizpour, Jafar Razmara

๐Ÿ” 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

๐Ÿ“˜ Journal: International Immunopharmacology
๐Ÿ“… Date: 2024-12
๐Ÿ”— DOI: 10.1016/j.intimp.2024.113219
๐Ÿ‘ฅ Contributors: Mahsa Mohammadi, Jafar Razmara, Morteza Hadizadeh, Sepideh Parvizpour, Mohd Shahir Shamsir

๐Ÿ” 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

๐Ÿ“˜ Journal: Soft Computing
๐Ÿ“… Date: 2024-09
๐Ÿ”— DOI: 10.1007/s00500-024-09772-2
๐Ÿ‘ฅ Contributors: Hamed Tabrizchi, Jafar Razmara

๐Ÿ” 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

๐Ÿ“˜ Journal: BioImpacts
๐Ÿ“… Date: 2024-07-01
๐Ÿ”— DOI: 10.34172/bi.2023.29957
๐Ÿ‘ฅ Contributors: Sepideh Parvizpour, Hanieh Beyrampour-Basmenj, Jafar Razmara, Farhad Farhadi, Mohd Shahir Shamsir

๐Ÿ” 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. Razmaraโ€™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

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Mrsย Iro Dianellou | Environmental Science | Best Researcher Award

Mrs Iro Dianellou , Aristotle University of Thessaloniki , greece

Ioanna Dianellou is a passionate geologist ๐Ÿงญ with a solid background in environmental and nuclear geochemistry ๐ŸŒโš›๏ธ. 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 ๐Ÿ‡น๐Ÿ‡ท. With publications in respected scientific journals ๐Ÿ“š and a strong academic foundation, she continues to contribute to geoscience and environmental safety. Her work is driven by curiosity, sustainability ๐ŸŒฑ, and a deep commitment to scientific excellence. ๐Ÿ”ฌ๐Ÿ‘ฉโ€๐Ÿ”ฌ

Professional Profile

SCOPUS

Education & Experienceย 

Ioanna holds a Masterโ€™s degree ๐ŸŽ“ in Synthetic Chemistry and Biochemistry from Aristotle University of Thessaloniki, focusing on materials for nuclear waste treatment โ˜ข๏ธ. Her thesis explored modified bentoniteโ€™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 ๐Ÿ”. She interned at Ege University (Turkey) under Erasmus+, and at Hellas Gold S.A. in exploration geology โ›๏ธ. 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 ๐ŸŒฟ.

Professional Developmentย 

Ioanna continuously enhances her expertise through academic research ๐Ÿงช, internships, and hands-on lab experience. Her Erasmus+ internship at Ege University gave her international exposure ๐ŸŒ 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 ๐Ÿ”ฌ. Sheโ€™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 โ˜ข๏ธ. Her proactive learning mindset ensures she remains updated in emerging technologies and methodologies ๐Ÿ“š๐Ÿง .

Research Focusย 

Ioanna Dianellouโ€™s research focuses on environmental geochemistry, radiochemistry, and nanomaterials ๐ŸŒ‹โš›๏ธ. 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) ๐Ÿงช. 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 ๐ŸŒฑ๐Ÿ’ก.

Awards and Honorsย 

Ioannaโ€™s academic excellence is reflected in her high grades and distinction in both undergraduate and postgraduate studies ๐Ÿฅ‡. She graduated with an 8.56/10 (Excellent) in her Masterโ€™s and 8.37/10 (Very Good) in her Geology diploma ๐ŸŽ“. She earned an Erasmus+ scholarship for her internship at Ege University in Turkey, showcasing her skills in international research collaboration ๐ŸŒ. Her co-authored publications in reputable journals such as Applied Radiation and Isotopes highlight her contribution to impactful scientific work ๐Ÿ“š. These recognitions underscore her dedication, discipline, and emerging reputation in the field of nuclear and environmental geosciences ๐Ÿ’ซ.

Publication Top Notes

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

Title: Sorption behavior of ยนยณโทCs and โถโฐCo 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

๐Ÿ” Summary:
This study investigates the sorption efficiency of raw and cellulose-modified Greek bentonite for the removal of radioactive isotopes Cesium-137 (ยนยณโทCs) and Cobalt-60 (โถโฐCo) 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, รœ.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

๐Ÿ” 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. Dianellouโ€™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

๐Ÿ” 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

Published on 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

๐ŸŽ“ Education and Experience

David Vatamanu began his academic journey at the โ€œNicolae Bฤƒlcescuโ€ Land Forces Academy in Sibiu, Romania, where he earned a Bachelorโ€™s degree in Management in the Field of Military Communication, completing his studies in 2020. Eager to deepen his knowledge, he pursued dual Masterโ€™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.

๐Ÿ› ๏ธ 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.

๐Ÿ”ฌ Research Focus

Davidโ€™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.

๐Ÿ“šPublication Top Note

A Computational Approach to Increasing the Antenna Systemโ€™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.

โœ… 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.