Khalifa Aliyu Ibrahim | Engineering and Technology | Best Researcher Award

Khalifa Aliyu Ibrahim | Engineering and Technology | Best Researcher Award

Mr Khalifa Aliyu Ibrahim, Cranfield University, United Kingdom

Mr. Kamilu A. Ibrahim is a dedicated researcher and academic with expertise in AI-driven high-frequency power electronics. Currently pursuing a PhD at Cranfield University, he has a strong background in physics, energy, and power systems. His research focuses on sustainable energy solutions, incorporating artificial intelligence and machine learning. With numerous publications in reputable journals and conferences, Mr. Ibrahim has made significant contributions to renewable energy, hydrogen systems, and power electronics. His academic career includes roles as a lecturer and research assistant, demonstrating his passion for knowledge dissemination. Recognized for his excellence, he has received prestigious scholarships and awards.

Publication Profile

Google Scholar

Education

Mr. Kamilu A. Ibrahim is currently pursuing a PhD in AI-driven design of high-frequency power electronics at Cranfield University, where he explores innovative approaches to sustainable energy and power systems. He previously earned a Master of Science in Energy Systems and Thermal Processes from Cranfield University (2020-2021), gaining expertise in energy efficiency, renewable energy, and thermal management. Further advancing his research skills, he completed a Master’s by Research (M.Res.) in Energy and Power (2022-2023), focusing on advanced power systems and their optimization. His academic journey began with a Bachelor of Science in Physics from Kaduna State University (2013-2016), where he built a strong foundation in physical sciences and energy applications. Throughout his education, Mr. Ibrahim has demonstrated a commitment to innovation in power electronics, artificial intelligence, and sustainable energy solutions. His multidisciplinary background equips him with the technical and analytical skills essential for driving advancements in renewable energy and intelligent power systems. πŸŽ“βš‘πŸ”‹

Experience

Mr. Kamilu A. Ibrahim has a strong background in research, teaching, and project management, with a focus on power systems, renewable energy, and AI applications. Since 2022, he has been working as a Research Assistant at Cranfield University, contributing to cutting-edge studies in AI-driven high-frequency power electronics. Prior to this, he served as a Lecturer at Kaduna State University from 2021 to 2022, where he taught physics and energy-related courses while mentoring students in research projects. From 2020 to 2021, he was a Lecturer at Nuhu Bamalli Polytechnic, Zaria, where he played a key role in curriculum development and academic instruction in energy systems. Throughout his career, Mr. Ibrahim has combined his expertise in energy and artificial intelligence to drive innovation in sustainable energy solutions. His experience spans teaching, publishing research in top-tier journals, and collaborating on interdisciplinary projects, making significant contributions to the advancement of renewable energy technologies.

Awards and Honors

Mr. Kamilu A. Ibrahim has been recognized for his academic excellence and research contributions through several prestigious awards and honors. He received the Petroleum Technology Development Fund Scholarship (2021), a highly competitive award supporting outstanding researchers in energy and power systems. In 2020, he was also honored with the Merit-based Foreign Scholarship, which enabled him to pursue advanced studies in energy systems and AI-driven power electronics. In addition to these distinguished scholarships, Mr. Ibrahim has earned multiple certificates of completion from various specialized training programs, focusing on sustainable energy, artificial intelligence applications in power systems, and cutting-edge advancements in high-frequency electronics. His commitment to continuous learning and innovation has positioned him as a leader in his field, contributing significantly to research in renewable energy, hydrogen storage, and machine learning applications. These achievements underscore his dedication to academic excellence and groundbreaking contributions to the future of energy technologies.

Publication Top Notes

  • πŸ“Š Revolutionizing Power Electronics Design Through Large Language Models: Applications and Future Directions (2024)
  • 🌊 Floating Solar Wireless Power Transfer System for Electric Ships: Design and Laboratory Tests (2025)
  • πŸ”‹ Harnessing Energy for Wearables: A Review of Radio Frequency Energy Harvesting Technologies (2023)
  • β˜€οΈ The Effect of Solar Irradiation on Solar Cells (2019)
  • 🌑️ Cooling of Concentrated Photovoltaic Cellsβ€”A Review and the Perspective of Pulsating Flow Cooling (2023)
  • 🌱 High-Performance Green Hydrogen Generation System (2021)
  • βš—οΈ Advancing Hydrogen: A Closer Look at Implementation Factors, Current Status, and Future Potential (2023)
  • πŸ“‘ Survey and Assessment of Radiation Levels Associated with Mobile and Wireless Telecommunication Mast in Residential and Office Areas within Kaduna Metropolis (2019)
  • πŸš€ Decision Support System for Sustainable Hydrogen Production: Case Study of Saudi Arabia (2025)
  • πŸ›’οΈ Measurements of Pour Points, Flash Points, Water Contents, and Viscosity of Some Selected Automobile Oils Used as Lubricants in Nigeria (2022)

Ebrahim Farrokh | Engineering and Technology | Best Researcher Award

Ebrahim Farrokh | Engineering and Technology | Best Researcher Award

Assoc. Prof. Dr Ebrahim Farrokh, Amirkabir University of Technology, Iran

Assoc. Prof. Dr. Ebrahim Farrokh is a distinguished expert in rock mechanics and mining engineering, serving as the Head of Rock Mechanics and Mining Engineering at Amirkabir University of Technology. With a career spanning academia and industry, he specializes in tunnel boring machines (TBMs), underground excavation, and rock stability analysis. He has played a key role in major tunneling projects, providing expertise on TBM operations, rock fragmentation, and ground control. His research has led to numerous influential publications, advancing TBM performance prediction and tunnel design methodologies. Alongside his academic role, he consults for Tunnel Saz Machin Co. and has held managerial positions at Hyundai Engineering and Construction. Recognized with prestigious awards, including the Hardy Memorial Award and SME’s NAT Conference Scholarship, his contributions continue to shape the field of mining engineering. His work combines theoretical advancements with practical applications, ensuring safer and more efficient underground construction projects. πŸš†πŸ’‘

Publication Profile

Google Scholoar

Education

  • Ph.D. in Mining Engineering, Penn State University (2009-2012) πŸ—οΈ
    Dr. Farrokh earned his Ph.D. at Penn State University, focusing on TBM performance evaluation, advance rate prediction, and rock behavior analysis. His research contributed to innovative methodologies for assessing TBM cutter wear and ground stability.

  • M.Sc. in Mining Engineering, Tehran University (2001-2004) ⛏️
    During his master’s studies, he specialized in underground excavation, tunnel stability, and mine planning. His thesis examined rock fragmentation techniques and their applications in mechanized tunneling.

  • B.Sc. in Mining Engineering, Yazd University (1997-2001) 🌍
    He completed his undergraduate degree at Yazd University, gaining foundational knowledge in rock mechanics, mineral extraction, and geotechnical engineering. His early research explored TBM operational parameters and ground convergence in tunneling projects.

Experience

  • Associate Professor & Head, Rock Mechanics & Mining Engineering, Amirkabir University of Technology (2018-present) πŸŽ“
    Leads research and academic initiatives in TBMs, tunnel stability, and underground mining.

  • Consultant, Tunnel Saz Machin Co. (2018-present) πŸ—οΈ
    Provides technical expertise in TBM operations, ground support, and excavation efficiency.

  • TBM Specialist & Manager, Hyundai Engineering & Construction (2013-2017) 🚜
    Managed TBM operations in major tunneling projects, optimizing performance and reducing downtime.

  • Research Assistant, Penn State University (2009-2012) πŸ“Š
    Conducted cutting-edge research on TBM cutter wear, penetration rate estimation, and tunnel convergence.

Awards and Honors πŸ†

  • Outstanding Business Performance Award, Hyundai Engineering & Construction (2015) 🌟
    Recognized for leadership in TBM project execution and efficiency improvements.

  • Outstanding Research Award, Hyundai Engineering & Construction (2014, 2015) πŸ…
    Awarded for contributions to TBM performance evaluation and geotechnical risk mitigation.

  • NAT Student Conference Scholarship Award, SME (2012) πŸŽ“
    Acknowledged for excellence in mining engineering research and academic achievements.

  • Hardy Memorial Award, Penn State University (2010) πŸ†
    Prestigious recognition for outstanding research contributions in mining and rock mechanics.

Research Focus

Dr. Farrokh’s research focuses on Tunnel Boring Machines (TBMs) 🚜, specializing in performance evaluation, advance rate prediction, and cutterhead design optimization. In Rock Mechanics πŸ—οΈ, he investigates rock properties, ground convergence, and stability assessment for underground projects. His work in Mining Engineering ⛏️ explores underground mining methods, rock fragmentation, and geotechnical risk analysis. By integrating theoretical advancements with real-world applications, Dr. Farrokh enhances the efficiency and safety of tunneling and mining operations. His research contributes to optimizing excavation processes, reducing operational risks, and advancing sustainable underground construction. πŸ“ŠπŸ”¬

Publications Top Notes

  1. Tunnel Face Pressure Design and Control πŸ“Š (2020)
  2. Concrete Segmental Lining: Procedure of Design, Production, and Erection of Segmental Lining in Mechanized Tunneling πŸ“š (2006)
  3. Study of Various Models for Estimation of Penetration Rate of Hard Rock TBMs πŸ“Š (2012)
  4. Effect of Adverse Geological Conditions on TBM Operation in Ghomroud Tunnel Conveyance Project 🌎 (2009)
  5. Correlation of Tunnel Convergence with TBM Operational Parameters and Chip Size in the Ghomroud Tunnel, Iran πŸ“Š (2008)
  6. A Discussion on Hard Rock TBM Cutter Wear and Cutterhead Intervention Interval Length Evaluation πŸ’‘ (2018)
  7. Evaluation of Ground Convergence and Squeezing Potential in the TBM-Driven Ghomroud Tunnel Project 🌎 (2006)
  8. Study of Utilization Factor and Advance Rate of Hard Rock TBMs πŸ“Š (2013)
  9. A Study of Various Models Used in the Estimation of Advance Rates for Hard Rock TBMs πŸ“Š (2020)
  10. Analysis of Unit Supporting Time and Support Installation Time for Open TBMs πŸ•’ (2020)

Marc Muselli | Engineering and Technology | Best Researcher Award

Marc Muselli | Engineering and Technology | Best Researcher Award

Prof Marc Muselli, University of Corsica, France

Prof. Marc Muselli stands out as a strong candidate for the Best Researcher Award. His significant contributions to renewable energy and alternative water production through dew utilization are notable.

Publication profile

google scholar

Introduction

Prof. Marc Muselli is a full professor at the University of Corsica, France, recognized globally for his expertise in renewable energy and water production systems. His research addresses critical environmental challenges, focusing on hydrogen-based energy storage, solar energy electrolysis, and alternative water sources like dew collection under varying climate conditions.

Education

With a rich academic journey at the University of Corsica, Corte, France, this individual earned their Habilitation in September 2007 πŸŽ“, demonstrating a high level of expertise in their field. Their doctorate, completed between September 1994 and October 1997 πŸ“š, further solidified their research capabilities. Prior to that, they undertook intensive studies from September 1993 to June 1994 πŸ“–, laying the groundwork for their distinguished academic career. Their educational path showcases a dedication to scholarly excellence and continuous learning 🌟.

Expertise and Research Impact

Prof. Marc Muselli, a full professor at the University of Corsica, has made substantial contributions to renewable energy systems and alternative water production. His work focuses on solar energy-based electrolysis, hydrogen storage, and dew collection for potable water under diverse climate conditions. His pioneering research in these areas has been globally recognized, reflected in his extensive publication record.

Scientific Leadership

From 2012 to 2020, Muselli served as President of the Scientific Council at the University of Corsica, demonstrating his leadership in driving scientific advancements. He is also an active member of the OPUR International Organization for Dew Utilization.

Awards and Honors

Muselli’s reputation in environmental sciences is reinforced by his ranking among the world’s top 2% of scientists by Stanford University (2021-2023) and his recognition as one of the Best Environmental Scientists by Research.com in 2023.

Additional Contributions

Muselli has contributed significantly to understanding atmospheric phenomena like dew, fog, and rain as water sources, especially in coastal and island regions. His research on radiative cooling and dew yield optimization has advanced alternative water production methods, particularly in arid and semi-arid regions.

Publication top notes

Calculation of the polycrystalline PV module temperature using a simple method of energy balance

Forecasting of preprocessed daily solar radiation time series using neural networks

Numerical weather prediction (NWP) and hybrid ARMA/ANN model to predict global radiation

Dew water collector for potable water in Ajaccio (Corsica Island, France)

Optimization of an artificial neural network dedicated to the multivariate forecasting of daily global radiation

Forecasting and simulating wind speed in Corsica by using an autoregressive model

Using radiative cooling to condense atmospheric vapor: a study to improve water yield

Measurement and modelling of dew in island, coastal and alpine areas

Dew, fog, and rain as supplementary sources of water in south-western Morocco

Chemical and biological characteristics of dew and rain water in an urban coastal area (Bordeaux, France)

Conclusion

His extensive contributions to environmental science, renewable energy, and alternative water production, along with his global recognition and leadership in research, Prof. Marc Muselli is an exceptional candidate for the Best Researcher Award. His influential research publications, international collaborations, and honors strongly align with the award criteria.

 

Theoklitos Karakatsanis | Engineering and Technology | Best Researcher Award

Theoklitos Karakatsanis | Engineering and Technology | Best Researcher Award

Assist Prof Dr Theoklitos Karakatsanis, Democritus University of Thrace, Greece

Based on the information provided, Assist. Prof. Dr. Theoklitos Karakatsanis appears to be a strong candidate for the Best Researcher Award for several reasons:

Publication profile

google scholar

Academic Position

Currently, he serves as an Assistant Professor at the School of Engineering, Democritus University of Thrace (DUTH), focusing on Production Engineering and Management.

Professional Experience

Currently, he serves as an Assistant Professor at the School of Engineering, Democritus University of Thrace (DUTH), in the Department of Production Engineering and Management. His extensive experience includes years as a private consultant engineer and work as an Elevator Engineer since 1989.

Research Contributions

Focus Areas: His research interests in modeling and control of electric machines, energy production, and saving are highly relevant in today’s energy landscape, especially with the growing importance of renewable energy sources.

Publications: Dr. Karakatsanis has co-authored numerous publications in respected journals, with a focus on probabilistic load flow analysis and its applications in power systems. His work on integrating wind power into distribution systems is particularly noteworthy, as it addresses critical challenges in renewable energy management.

Research Interests

His research interests are centered around modeling and control of electric machines, production energy, and energy saving.

Impact and Collaborations

Collaborative Work: He has collaborated with recognized researchers, which strengthens the credibility and reach of his work. His participation in various conferences and publications demonstrates an active engagement in his field.

Practical Application: His extensive experience as a consultant engineer enhances the practical applicability of his research, bridging the gap between theory and real-world implementation.

Professional Affiliations

Membership: Being a member of IEEE and the Technical Chamber of Greece highlights his professional standing and commitment to ongoing professional development.

Conclusion

Given his strong academic credentials, impactful research contributions, and active involvement in the engineering community, Assist. Prof. Dr. Theoklitos Karakatsanis is a suitable candidate for the Best Researcher Award. His work not only contributes to academic knowledge but also offers practical solutions in energy management and sustainability.

Publication top notes

Probabilistic load flow in distribution systems containing dispersed wind power generation

Probabilistic constrained load flow based on sensitivity analysis

Voltage control settings to increase wind power based on probabilistic load flow

Probabilistic load flow for assessment of voltage instability

Distribution system voltage and reactive power control based on probabilistic load flow analysis

The effect of wind parks on the operation of voltage control devices

Probabilistic calculations of aggregate storage heating loads

Probabilistic constrained load flow for optimizing generator reactive power resources

A probabilistic approach to control variable adjustment for power system planning applications

Probabilistic cost allocation of losses in networks with dispersed renewable generation

 

Yiming Xu | Tech Innovations | Best Researcher Award

Yiming Xu | Tech Innovations | Best Researcher Award

Mr Yiming Xu, Cranfield University, United Kingdom

Yiming Xu is a Ph.D. candidate in Energy at Cranfield University (2020-2024) with a focus on AI for energy flexibility and decarbonisation. He holds an MSc in Advanced Mechanical Engineering from Cranfield University and a BEng in Mechanical Engineering from Nanjing University of Aeronautics and Astronautics. Yiming has contributed to Innovate UK projects, presented at conferences such as ICAE and ISGT, and published papers on energy trading. He has interned at DJI Technology Co., Ltd, and holds patents in finger flexibility devices and mountain-climbing aids. Proficient in Python, C++, and data visualization, he is also an amateur Muay Thai fighter. πŸ§ πŸ”‹πŸ€–πŸ“šπŸ₯Š

Publication profile

Orcid

Education

With a PhD in Energy from Cranfield University (2020-2024) πŸŽ“, He focused on AI for energy flexibility modelling and decarbonisation 🌱, vehicle-to-vehicle energy trading, and EV owner behaviour analysis πŸš—. He presented at ICAE, ISGT, ICPADS, and other seminars 🎀. My MSc in Advanced Mechanical Engineering (2019-2020) included a thesis on peer-to-peer energy trading for EVs ⚑ and courses like CFD and risk engineering πŸ“š. During an AI exchange at Imperial College London (2018), I designed computer vision algorithms for a robotic arm πŸ€–. My BEng from Nanjing University (2015-2019) involved a thesis on 3D printing and courses in mechanics and materials πŸ› οΈ.

Experience

During my internship at DJI Technology Co., Ltd in Shenzhen, China, from June to August 2018, I participated in the global young engineer competition ROBOMASTER, working with a team that included top universities from China and overseas. I served as venue maintenance personnel in the ROBOMASTER machinery group, responsible for debugging mechanical organs and sensors, and maintaining the visual recognition module of the referee system. I inspected and maintained over 50 units of equipment, resolving issues more than 10 times, ensuring the smooth operation of the event. πŸŒπŸ€–πŸ”§πŸ‘¨β€πŸ”§πŸ“·βœ…

Research Projects

As a Research Assistant on three Innovate UK projects, I optimized energy flow management in urban EV charging with Lesla Ltd (Aug 2023 – Jan 2024), designing AI models to schedule charging behavior and forecast energy demand πŸ“ˆπŸ”‹. I established a smart home EV charger system for Entrust Smart Home Ltd (Jan 2021 – Mar 2021), focusing on app design and peer-to-peer energy trading πŸ“±πŸ . Additionally, I worked with SNRG Ltd and Electric Corby CIC (Oct 2020 – Mar 2021) on advanced grid services, analyzing driving behavior data and designing trading algorithms πŸš—πŸ’‘. All projects met quality standards and were successfully delivered βœ….

Research focus

Yiming Xu’s research primarily focuses on vehicle-to-vehicle (V2V) energy trading, particularly through innovative auction models and flexible trading platforms. His work explores sustainable energy solutions, fraud prevention, and efficient market mechanisms in V2V energy exchanges. Xu’s studies integrate advanced technologies like the K-factor approach and double auction systems to enhance energy trading efficiency and security. His research contributions are significant in the fields of smart grids, green computing, and sustainable energy, aiming to develop robust frameworks for future energy systems. πŸŒπŸ”‹πŸš—πŸ’‘πŸ“‰πŸ”’

Publication top notes

Vehicle-to-Vehicle Energy Trading Framework: A Systematic Literature Review

An Anti-fraud Double Auction Model in Vehicle-to-Vehicle Energy Trading with the K-factor Approach

A Vehicle-to-vehicle Energy Trading Platform Using Double Auction With High Flexibility

 

Ioannis Chatzilygeroudis | Computer Science and Artificial Intelligence | Best Researcher Award

Ioannis Chatzilygeroudis | Computer Science and Artificial Intelligence | Best Researcher Award

Prof Ioannis Chatzilygeroudis, University of Patras, Greece

Prof. Emeritus at the University of Patras, Greece, with a rich educational background in Mechanical and Electrical Engineering (NTUA), Theology (University of Athens), MSc in Information Technology, and a PhD in Artificial Intelligence (University of Nottingham). Fluent in Greek and English, he specializes in AI, KR&R, knowledge-based systems, theorem proving, intelligent tutoring, e-learning, machine learning, natural language generation, sentiment analysis, semantic web, and educational robotics. His prolific research includes a PhD thesis, 18 edited volumes, 21 book chapters, 46 journal papers, 115 conference papers, 8 national conference papers, and 14 workshop papers. πŸ“šπŸ€–πŸ’»πŸŒ

Publication profile

Orcid

Education

πŸ“š From September 1968 to June 1974, completed secondary education, earning a Certificate of High School Graduation in Science. πŸŽ“ Pursued a Diploma in Mechanical and Electrical Engineering with a specialization in Electronics at the National Technical University of Athens from October 1974 to July 1979. πŸ“œ From February to June 1983, obtained a Certificate of Educational Studies from PATES of SELETE, Greece. πŸ“– Achieved a Bachelor in Theology from the University of Athens, completed between October 1979 and December 1987. πŸŽ“ Earned an MSc in Information Technology from the University of Nottingham in 1989, followed by a PhD in Artificial Intelligence from the same university in 1992. 🧠 Thesis: “Integrating Logic and Objects for Knowledge Representation and Reasoning.”

Experience

πŸ“˜ From Feb. 1982 to June 1982, I served as a part-time lab professor at PALMER Higher School of Electronics in Greece, teaching Electronics Lab. My full-time teaching journey began at TEI of Athens (1982-84), where I covered courses like Electrotechnics and Circuit Theory. My secondary education tenure (1984-92) focused on electrical engineering subjects. I then transitioned to higher education, teaching at TEI of Kozani and Chalkida, and later at the University of Nottingham (1990-92). From 1995-2006, I was a senior researcher and lecturer at the University of Patras, ultimately becoming a professor (2009-2023). Now, I am a Professor Emeritus. πŸŽ“πŸ”¬

Projects

From June 1993 to November 1995, I managed the CTI team for the DELTA-CIME project, developing a knowledge-based production control system. I led several initiatives, including the MEDFORM project for multimedia education and the national project for educational software in chemistry. As a senior researcher, I contributed to intelligent systems for tele-education and hybrid knowledge representation. I led multiple European projects like MENUET, AVARES, and TESLA, focusing on innovative education through virtual reality. My work aims to enhance learning experiences across disciplines, involving collaboration with various international partners. πŸŒπŸ“šπŸ’»πŸŽ“

Research focus

Ioannis Hatzilygeroudis specializes in artificial intelligence and its applications in various domains, particularly in agriculture and healthcare. His research includes intelligent systems for diagnosing farmed fish diseases, employing deep learning techniques for image analysis, and exploring natural language processing methods. He has contributed significantly to the development of expert systems and reinforcement learning approaches to improve disease prediction in aquaculture. Additionally, his work in sentiment analysis and e-learning demonstrates a commitment to advancing educational technologies and user experience. Hatzilygeroudis’s interdisciplinary approach combines computer science with practical applications, making significant strides in health and environmental management. πŸŒ±πŸŸπŸ’»πŸ“Š

Publication focus

Using Level-Based Multiple Reasoning in a Web-Based Intelligent System for the Diagnosis of Farmed Fish Diseases

An Integrated GIS-Based Reinforcement Learning Approach for Efficient Prediction of Disease Transmission in Aquaculture

Speech Emotion Recognition Using Convolutional Neural Networks with Attention Mechanism

Expert Systems for Farmed Fish Disease Diagnosis: An Overview and a Proposal

Expert Systems for Farmed Fish Disease Diagnosis: An Overview and a Proposal

A Convolutional Autoencoder Approach for Boosting the Specificity of Retinal Blood Vessels Segmentation

Evaluating Deep Learning Techniques for Natural Language Inference