Assoc. Prof. Dr. Jessica Fleming | Molecular Biomarkers | Best Researcher Award

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Assoc. Prof. Dr. Jessica Fleming | Molecular Biomarkers | Best Researcher Award

The Ohio State University, United States.

Dr. Jessica L. Fleming, PhD, is an accomplished radiobiologist at the James Comprehensive Cancer Center, The Ohio State University. With over a decade of experience in translational oncology research, she specializes in molecular biomarkers and radiation therapy innovations. Dr. Fleming plays a key role in collaborative clinical and research initiatives, especially in glioma and FLASH radiotherapy. She is also a co-founder and former CEO of the Cap City Biohackers, demonstrating her entrepreneurial edge in biomedical innovation.

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🎓 Education

Dr. Fleming earned her PhD in Molecular, Cellular, and Developmental Biology from The Ohio State University in 2012, following a BS in Biology, Cum Laude, from Ashland University in 2006. Her strong academic foundation was supported by multiple fellowships and research opportunities during her undergraduate and graduate studies.

🧪 Experience

Dr. Fleming currently serves as an Associate Radiobiologist at OSU, working with Dr. Arnab Chakravarti. Her journey at OSU began as a graduate student, advancing through postdoctoral research and senior research associate roles. She has led cutting-edge radiobiological studies and was integral to several major clinical protocols. Beyond academia, she was the CEO and Co-Founder of Cap City Biohackers, reflecting her commitment to science outreach and innovation.

🔬 Research Interests

Radiation oncology and molecular oncology, particularly adult gliomas and biomarkers

FLASH radiotherapy, clinical translation, and toxicity modeling

Tumor heterogeneity and resistance mechanisms

Translational research bridging lab discoveries and patient care

🏆 Awards & Honors

🥇 2024 ASTRO Annual Meeting Abstract Award

🏅 Columbus CEO Future 50 Award (2020)

🎖 Best of ASTRO & Basic/Translational Science Abstract Award (2018)

🎓 Alumni Grants for Graduate Research (2012)

🧬 NSF REU Fellow (2005)

🌟 Track & Field Athletic Scholar and Presidential Scholar (2002–2006)

📚 Selected Publications

Here are some of Dr. Fleming’s key publications, with citation and access details:

Fleming JL et al. (2025) – Comprehensive Molecular Analysis in NRG Oncology/RTOG 9813 – Int J Radiat Oncol Biol Phys (Accepted)

Manring HR, Fleming JL et al. (2025) – FLASH Radiotherapy: From In Vivo Data to Clinical Translation – Hematol Oncol Clin N Am (PMID: 39828472)

Fleming JL, Chakravarti A. (2025) – Molecular Biomarkers in Adult Lower-Grade Gliomas – Cancer J, 31(1): e0758. (PMID: 39841423)
➤ Cited by: 2 articles

Kotecha R, Schiff D, Chakravarti A, Fleming JL et al. (2024) – Management of IDH-Mutated Gliomas – J Clin Oncol, 42(21): 2588-2598. (PMID: 38833641)
➤ Cited by: 15 articles

Becker AP, Becker V, McElroy J, Fleming J et al. (2024) – HMGB2 as Biomarker in Astrocytomas – Cancers (Basel), 16(8): 1516. (PMID: 38672598)
➤ Cited by: 7 articles

Dr. David Hua | Artificial Intelligence | Best Researcher Award

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Dr. David Hua | Artificial Intelligence | Best Researcher Award

Ball State University, United States.

Dr. David M. Hua is an Associate Professor at the Center for Information and Communication Sciences, Ball State University. With a rich academic background and over two decades of teaching, Dr. Hua has become a pivotal figure in the intersection of technology education, cybersecurity, and higher education. He is recognized for mentoring student-led innovation and his contribution to emerging tech curricula including offensive security, private cloud infrastructure, and sustainability in IT.

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🎓 Education

Dr. Hua earned his Ed.D. in Higher Education in 2010 from Ball State University, where he also completed an MBA in Information Systems (2000) and a B.S. in Psychological Science (1991). This diverse academic foundation reflects his commitment to both technical expertise and educational leadership.

💼 Experience

Since July 20, 1998, Dr. Hua has served at Ball State University, advancing to the role of Associate Professor. He began as an Assistant Professor in 2000. His teaching spans undergraduate and graduate levels with courses ranging from cybersecurity and network configuration to cloud technologies. Beyond Ball State, his engagements with other institutions and organizations have broadened his interdisciplinary impact on both students and faculty.

🔬 Research Interests

Dr. Hua’s research interests lie at the crossroads of cybersecurity, AI in mental health surveillance, sustainable IT practices, and technology integration in higher education. He is especially passionate about leveraging machine learning to support mental health outcomes and empower student innovation through data-driven methodologies.

🏆 Awards & Mentorship

Dr. Hua has been an active mentor in various student projects, honors theses, and national competitions like the National Cyber League. He’s also served on several doctoral committees, contributing to dissertations in educational leadership and adult learning. His efforts have earned him recognition as a dedicated mentor, innovator, and academic leader.

📚 Publication

AI-Driven Mental Health Surveillance: Identifying Suicidal Ideation Through Machine Learning Techniques
📅 2025 | Big Data and Cognitive Computing
🧾 Cited by: 3 articles (as of early 2025)
👉 DOI: 10.3390/bdcc9010016

Dr. Hengyu Zhang | Materials Science | Best Researcher Award

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Dr. Hengyu Zhang | Materials Science | Best Researcher Award

Soochow University, China.

Dr. Hengyu Zhang (张恒宇), is a passionate Chinese researcher specializing in thermal management and electromagnetic functional textile materials. With a strong academic foundation in textile engineering and chemistry, he is currently serving as a postdoctoral fellow at Soochow University. Dr. Zhang's research bridges innovation and application, particularly in the development of advanced textiles using supercritical processes and electromagnetic functionalities. His work has been widely recognized through awards, publications, and patents.

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🎓 Education

Dr. Hengyu Zhang holds a solid academic background in textile science and engineering. He is currently serving as a Postdoctoral Fellow in Textile Chemistry and Dyeing & Finishing at Soochow University, Suzhou, China (April 2024–Present). Prior to this, he earned his Ph.D. in Textile Materials and Textile Design from Donghua University, Shanghai, China (September 2018–March 2024). His academic journey began with a B.Sc. in Textile Engineering from Qingdao University, Qingdao, China (September 2014–June 2018). This progression reflects his deepening expertise in textile research and innovation, with a strong foundation in both theoretical and applied aspects of textile science.

💼 Experience

Currently a Postdoctoral Fellow at Soochow University, Dr. Zhang previously completed his Ph.D. at Donghua University, one of China's leading textile research institutions. Throughout his academic career, he actively participated in multiple research projects, including those funded by the National Natural Science Foundation of China and Donghua University's Graduate Innovation Fund. His practical experience also includes work on advanced instruments such as SEM, FTIR, and XRD, alongside simulation tools like CST.

🔬 Research Interests

Dr. Zhang’s primary research interests include:

👕 Thermal management textile materials developed using supercritical processes

📡 Electromagnetic functional textiles for wave absorption, shielding, and stealth applications

🧪 Composite materials and nanoarchitectures for multifunctional smart fabrics

📐 Frequency-selective surfaces and gradient impedance structures

🏅 Awards & Honors

🥇 National Scholarship – Sep 2023

🧵 First Prize, China Textile Industry Federation Science & Tech Award – Aug 2023

🎤 Outstanding Reporter, Shanghai Intl. Textile Graduate Summer School – Jul 2023

🥈 Silver Award, 9th China Intl. "Internet +" Innovation Competition

🗣️ Outstanding Oral Report, 2nd Textile Graduate Forum – Apr 2023

📝 Finalist, 23rd Chen Weiji Outstanding Paper Award – Mar 2023

💰 Comprehensive Scholarship, Donghua University – Sep 2022

🏆 22nd Chen Weiji Excellent Paper Award – Oct 2021

📚 Selected Publications

Here’s a selection of Dr. Hengyu Zhang’s representative research works:

Zhang, H.Y. et al. (2024). MXene/PPy electromagnetic wave absorbing felt with impedance continuous gradient structure prepared by freezing interface polymerization. ACS Applied Nano Materials, 7(1), 1289–1399.

Zhang, H.Y. et al. (2023). Frequency-selective/impedance gradient MXene/PPy nanocomposite polyester felt. Composites Part A, 175, 107776.

Zhang, H.Y. et al. (2022). Nanoarchitectonics of MXene/PPy/polyester composite fabric. Composites Part A, 163, 107163.

Zhang, H.Y. et al. (2022). Washable conductive cotton yarn using MXene coating. Industrial Crops and Products, 188, 115653.

Zhang, H.Y. et al. (2022). Multilayer flexible EMI shielding fabric. Textile Research Journal, 92(5-6), 851–859.

Mr. Hussm Rostum | Computer Science | Best Researcher Award

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Mr. Hussm Rostum | Computer Science | Best Researcher Award

Miskolc University, Institute of Automation and Info-communication, Hungary.

Hussam Rostum is a PhD candidate and researcher at the University of Miskolc in Hungary, specializing in computer vision for autonomous drone navigation. With a strong background in telecommunications and electronics, he blends academic excellence with hands-on experience as a part-time software engineer at FIEK. Hussam is known for developing cutting-edge solutions in industrial automation, biomedical imaging, and human–machine interfaces. Fluent in Arabic and English, he brings international insight into interdisciplinary research projects, merging software innovation with engineering systems.

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🎓 Education

Hussam holds a BSc and MSc in Telecommunication and Electronic Engineering, equipping him with deep theoretical and practical knowledge in signal processing, system design, and electronics. Currently, he is pursuing a PhD in Information Science at the University of Miskolc, focusing on AI-based vision systems for autonomous drone operations.

💼 Experience

Hussam serves as an Assistant Researcher and Part-time Software Engineer at FIEK, where he builds C# monitoring software, implements PLC-to-PC communications, and automates data workflows using Linux, Docker, and Excel. His professional journey includes work as a Full Stack Developer and Telecom Engineer, with experience in GUI development, DevOps collaboration, and .NET technologies.

🔬 Research Interests

📸 Computer Vision & Image Processing

🤖 Autonomous Systems & Drone Navigation

🩺 Biomedical Imaging & Oxygen Saturation Estimation

🔬 Optical System Design (Zemax)

⚙️ Industrial Automation & Data Visualization

🧠 Human–Machine Interfaces & Sensor Integration

📚 Selected Publications

Enhancing Machine Learning Techniques in VSLAM for Robust Autonomous Unmanned Aerial Vehicle Navigation
📅 2025-04-02 | 📰 Electronics
📌 Focus: Improving Visual SLAM with machine learning for UAVs in complex environments.
🔗 DOI: 10.3390/electronics14071440
👥 Co-author: József Vásárhelyi

Comparing the Effectiveness and Performance of Image Processing Algorithms in Face Recognition
📅 2024-05-22 | 📚 Conference Paper
📌 Focus: Evaluation of various image processing techniques for face recognition applications.
🔗 DOI: 10.1109/ICCC62069.2024.10569864
👥 Co-author: József Vásárhelyi

FPGA Implementation in Mobile Robot Applications: State of the Art Review
📅 2023-12-20 | 📰 Multidiszciplináris Tudományok
📌 Focus: Overview of FPGA-based systems in robotics.
🔗 DOI: 10.35925/j.multi.2023.2.21
👥 Co-authors: Omar M. Salih, Noha Hammami

An Overview of Energies Problems in Robotic Systems
📅 2023-12-14 | 📰 Energies
📌 Focus: Challenges in energy management for robotic systems.
🔗 DOI: 10.3390/en16248060
👥 Co-authors: József Vásárhelyi, Omar M. Salih, Rabab Benotsname

A Review of Using Visual Odometry Methods in Autonomous UAV Navigation in GPS-Denied Environments
📅 2023-12-01 | 📰 Acta Universitatis Sapientiae, Electrical and Mechanical Engineering
📌 Focus: Use of visual odometry for UAVs in GPS-denied settings.
🔗 DOI: 10.2478/auseme-2023-0002
👥 Co-author: József Vásárhelyi

 

 

 

 

Dr. Mazen Azhry Mohammed Musa | Dentistry | Best Researcher Award

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Dr. Mazen Azhry Mohammed Musa | Dentistry | Best Researcher Award

Xi'an Jiaotong University, China.

Dr. Mazen Azhry Mohammed Musa is a dedicated orthodontist and clinical researcher, currently affiliated with Xi’an Jiaotong University, China, and University of Science and Technology Omdurman, Sudan. His work bridges clinical excellence and scholarly innovation, with a particular passion for temporomandibular joint disorders (TMD), smile aesthetics, and orthodontic therapies. Through his contributions to several high-impact journals and peer-reviewed collaborations, he strives to advance dental medicine and improve patient care globally.

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🎓 Education

Dr. Mazen Azhry Mohammed Musa 🦷 is a dedicated orthodontist currently pursuing his MD in Orthodontics at Xi’an Jiaotong University, China (2020–2025), where his research focuses on quantitative and qualitative condylar changes following stabilization splint therapy in TMD patients. He also holds an MSc in Orthodontics from the same university (2017–2020), with his thesis published in BMC Oral Health. 📚 In addition, Dr. Musa earned a Postgraduate Diploma in Research Methodology & Biostatistics from UMST, Sudan (2015–2016) 📊, complementing his clinical expertise with solid research skills. His journey in dentistry began with a Bachelor of Dental Surgery (BDS) from the University of Science & Technology, Sudan (2008–2013), where he completed a thesis on the prevalence of caries in special needs children in Khartoum State 🪥. Dr. Musa’s clinical acumen, academic rigor, and commitment to improving oral health outcomes make him a rising figure in the field of orthodontics.

💼 Experience

🦷 Orthodontist, Xi’an Jiaotong University, China (Sep 2020 – Present)
Dr. Musa has been actively engaged in clinical orthodontic practice, delivering comprehensive treatment plans while integrating advanced diagnostic tools and therapeutic strategies. His work focuses on orthodontics and temporomandibular disorders (TMD), and he contributes to research supervision and academic development within the department.

🔬 Research Interests

🦷 Dentistry & Oral Health

🧬 Orthodontics & Dentofacial Orthopaedics

😁 Smile Aesthetics

💢 Temporomandibular Joint Disorders (TMD)
His research integrates cone beam CT, 3D analysis, and esthetic evaluation to inform personalized treatment.

📚 Selected Publications

😬 Temporomandibular Joint (TMJ) & Stabilization Splint Therapy

Title: Three dimensional evaluation of the skeletal and temporomandibular joint changes following stabilization splint therapy...

Authors: MMS Ahmed, D Shi, MAA Al-Somairi, M Musa, et al.

Journal: BMC Oral Health, 23(1), 18

Citations: 17

Year: 2023

Title: Quantitative and qualitative condylar changes following stabilization splint therapy...

Authors: M Musa, Q Zhang, R Awad, et al.

Journal: Clinical Oral Investigations, 27(5), 2399–2310

Citations: 12

Year: 2023

😁 Smile Aesthetics & Sociocultural Factors

Title: Effect of the ethnic, profession, gender, and social background on the perception of upper dental midline deviations...

Authors: M Musa, R Awad, A Mohammed, et al.

Journal: BMC Oral Health, 23(1), 214

Citations: 8

Year: 2023

🧬 Stem Cells & ceRNA Networks

Title: Analysis of ceRNA networks during mechanical tension‐induced osteogenic differentiation of periodontal ligament stem cells

Authors: W Wang, N Li, M Musa, et al.

Journal: European Journal of Oral Sciences, 130(5), e12891

Citations: 8

Year: 2022

Dr. Ali Saleh | Transportation | Best Researcher Award

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Dr. Ali Saleh | Transportation | Best Researcher Award

Széchenyi István University, Germany.

Ali Saleh is a dedicated Syrian 🇸🇾 Civil Engineer and Ph.D. researcher specializing in road engineering and sustainable asphalt technology. With years of hands-on experience in both academia and infrastructure development, Ali blends practical engineering skills with cutting-edge research. He is particularly focused on asphalt mixture optimization using AI and neural networks. Currently based in Germany 🇩🇪, Ali seeks to contribute to advanced civil engineering innovations worldwide.

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🎓 Education

Dr. Ali Saleh holds a Ph.D. in Engineering Sciences from Széchenyi István University, Hungary (2020–2024), where he engaged in cutting-edge research within the field of civil engineering. Prior to his doctoral studies, he completed both a Master of Science in Civil Engineering (2015–2019) and a Bachelor of Science in Civil Engineering (2007–2013) at Tishreen University, Syria. Dr. Saleh’s academic background showcases a strong foundation in structural analysis, a deep commitment to infrastructure development, and a progressive trajectory in engineering sciences.

💼 Experience

In addition to his academic achievements, Dr. Ali Saleh brings valuable professional and teaching experience in the field of civil engineering. He worked as a Civil Engineer at Latakia Port, Syria (2014–2020), where he managed and supervised major infrastructure projects from design through execution, ensuring strict adherence to deadlines and quality standards. Alongside his engineering role, he served as a Lecturer at Tishreen University (2016–2019), where he delivered core civil engineering lectures and guided students academically. He also contributed to technical education as an Instructor at Omega Institute (2018–2019), teaching AutoCAD and Civil 3D to aspiring engineers, bridging theoretical knowledge with practical application.

🔬 Research Interests

♻️ Reclaimed Asphalt Pavement (RAP)

🧠 Machine Learning & Neural Networks in Civil Engineering

🌱 Sustainable Road Construction

🛣️ Bitumen Foaming and Asphalt Performance

📊 Pavement Testing and ITS/HWTT Data Modeling

🏆 Awards & Innovations

🛠️ Invention: Designed a bitumen foaming machine

🏅 Recognized for contributions in road project sustainability and environmental research at various international conferences.

📚 Selected Publications

🛣️ Warm Mix Asphalt (WMA) & Reclaimed Asphalt Pavement (RAP) Research

1. Machine Learning Modelling the Rut Depth of WMA Mixtures with Variable RAP and Foamed Bitumen Content

Journal: Dorogi i mosti (October 9, 2024)
DOI: 10.36100/dorogimosti2024.30.138
Highlights:

Utilizes machine learning models to predict rutting behavior in WMA.

Investigates performance effects of variable RAP and foamed bitumen levels.

Promotes data-driven pavement design and performance prediction.

2. Modelling Indirect Tensile Strength of Warm Mix Asphalt with Variable RAP Content

Journal: Dorogi i mosti (October 9, 2024)
DOI: 10.36100/dorogimosti2024.30.157
Highlights:

Focuses on indirect tensile strength (ITS) behavior of WMA mixtures.

Models mechanical performance under different RAP inclusion rates.

Supports RAP optimization for maintaining structural integrity.

3. Environmental Impacts of Using Foamed Asphalt

Journal: Dorogi i mosti (April 25, 2023)
DOI: 10.36100/dorogimosti2023.27.296
Highlights:

Evaluates environmental implications of foamed asphalt in road construction.

Considers emissions, energy savings, and recyclability.

Lays groundwork for greener road-building practices.

Prof. Dr. Javier Ruiz-del-Solar | Robotics | Best Researcher Award

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Prof. Dr. Javier Ruiz-del-Solar | Robotics | Best Researcher Award

Universidad de Chile, Chile.

Javier Ruiz-del-Solar S. is a Chilean Full Professor at the Department of Electrical Engineering, Universidad de Chile, and Director of the Advanced Mining Technology Center. With a deep passion for robotics, AI, and mining tech, he has made remarkable contributions to academia and industry, mentoring the next generation of engineers and researchers.

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🎓 Education

Prof. Dr. Javier Ruiz-del-Solar is a distinguished academic with a strong foundation in electrical and electronic engineering. He earned his Doctor-Engineer degree from the Technical University of Berlin, Germany in 1997. Prior to that, he obtained his M.Sc. in Electrical Engineering in 1992 and his undergraduate degree in Electrical Engineering in 1991 from the Universidad Técnica Federico Santa María, Chile. His academic trajectory reflects a solid commitment to excellence in engineering and research.

🧑‍🔬 Experience

Prof. Dr. Javier Ruiz-del-Solar has held numerous prominent academic and editorial positions throughout his career. He serves as a Full Professor at the Universidad de Chile, where he also directs the Advanced Mining Technology Center. His editorial contributions include being an Associate Editor for the IEEE Transactions on Cognitive and Developmental Systems (2017–2023) and a current Advisory Board Member of the Journal of Field Robotics (2022–2024). He also served as an Associate Editor for the Journal of Intelligent and Robotic Systems (2008–2017). In addition, Prof. Ruiz-del-Solar has been the Chairman of the IEEE Latin American Robotics Council since 2003, contributing significantly to the development of robotics research and collaboration across the region.

🔍 Research Interests

His work lies at the intersection of:

🤖 Robotics & Autonomous Systems

🧠 Artificial Intelligence & Deep Learning

⛏️ Mining Technology and Automation

🏆 Awards & Honors

🏅 Member, Chilean Academy of Engineering (since 2009)

🥇 Best Paper Award, RoboCup Symposium (2004, 2015, 2017)

🚀 RoboCup @Home Innovation Award (2007, 2008)

🎤 IEEE Distinguished Lecturer (2008–2009)

👨‍🏫 Best Teacher Award, Universidad de Chile (2007)

📚 Selected Publications

🛠️ Autonomous & Collaborative Mining Systems

1. The Road to the Mine of the Future: Autonomous Collaborative Mining

Journal: Mining (April 2025)
DOI: 10.3390/mining5020025
Key Themes:

Vision of fully autonomous, cooperative mining systems.

Integrates robotic systems, multi-agent collaboration, and intelligent decision-making.

Emphasis on safety, productivity, and sustainability in future mining operations..

🤖 Reinforcement Learning in Mining

2. Autonomous Loading of Ore Piles with Load-Haul-Dump Machines Using DRL

Journal: Expert Systems with Applications (March 2025)
DOI: 10.1016/j.eswa.2024.125770
Highlights:

Application of deep reinforcement learning to optimize ore loading in underground mining.

Demonstrates efficiency gains and reduced human intervention.

3. Control of Heap Leach Piles Using Deep Reinforcement Learning

Journal: Minerals Engineering (July 2024)
DOI: 10.1016/j.mineng.2024.108707
Highlights:

Uses DRL to optimize irrigation and aeration in heap leaching.

Potential for smarter, real-time process control in hydrometallurgy.

🍒 AI and Robotics Beyond Mining

4. Cherry CO Dataset: Detection, Segmentation, and Maturity Recognition

Journal: IEEE Robotics and Automation Letters (June 2024)
DOI: 10.1109/LRA.2024.3393214
Focus:

High-quality dataset for precision agriculture using computer vision.

Supports cherry detection and ripeness classification.

 

 

 

Dr. Ali Altuntepe | Hydrogen Energy | Best Researcher Award

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Dr. Ali Altuntepe | Hydrogen Energy | Best Researcher Award

Sivas of Science and Technology university, Turkey.

Dr. Ali Altuntepe is a Turkish researcher and materials scientist specializing in experimental condensed matter physics, thin film technology, and two-dimensional materials. With a Ph.D. in Mechanical Engineering, his work focuses on hydrogen storage, graphene synthesis, and solar cell enhancement. He is passionate about integrating nanomaterials in renewable energy applications and continues to contribute significantly to the scientific community through numerous high-impact publications and collaborative projects.

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🎓 Education

Dr. Ali Altuntepe has pursued his entire academic journey in Mechanical Engineering at Niğde Ömer Halisdemir University, where he demonstrated a consistent dedication to advanced research in materials science and energy systems. He recently completed his Ph.D. in Mechanical Engineering (2019–2024) with an outstanding GPA of 9.74/10.00. His doctoral thesis focused on the "Investigation of Hydrogen Storage Potential of Two-Dimensional Materials, Metal Hydrides, and Their Compositions," reflecting his deep engagement with sustainable and cutting-edge energy technologies. Prior to this, he earned his Master’s degree in Mechanical Engineering (2017–2019), achieving a GPA of 90.09/100, with a thesis centered on the "Synthesis of Doped and Pristine Graphene." His academic foundation was laid with a Bachelor's degree in the same field (2012–2017), where he graduated with a GPA of 3.35/4.00. Throughout his academic career, Dr. Altuntepe has cultivated expertise in nanomaterials, hydrogen storage systems, and graphene synthesis, positioning him as a strong contributor to both academic and applied research in clean energy and material innovation.

🧑‍🏫 Experience

Dr. Altuntepe has extensive experience in thin film synthesis and characterization. His work includes growing doped and pristine graphene, investigating 2D materials like MoS₂, WS₂, LiH, and NaH, and applying these materials in PEM fuel cells and solar cells. He has presented at international conferences and co-authored a book chapter on sustainable materials in solar technology.

🔬 Research Interests

Graphene and TMDs (MoS₂, WS₂) synthesis

Hydrogen storage materials

Solar cell enhancement using 2D materials

Thin film deposition techniques (CVD, PVD, E-beam)

Materials characterization (XRD, SEM, Raman, XPS, etc.)

Transparent conductive oxides (TCOs)

Integration of nanomaterials into composite and optoelectronic systems

🏆 Awards & Achievements

Co-authorship in a prestigious Elsevier publication:
Sustainable Materials Solutions for Solar Energy Technologies (2021)

Oral presentations at international conferences including ICSM and MSNG

High citation record with over 20 peer-reviewed journal articles

📚 Selected Publications

☀️ Advanced Solar Cell Materials

1. Boron Doped Graphene and MoS₂-Based Ultra-Thin Schottky Junction Solar Cell

Journal: Optical Materials (May 2025)
DOI: 10.1016/j.optmat.2025.116828
Highlights:

Integrates boron-doped graphene with MoS₂ to form an ultra-thin Schottky junction.

Aims to enhance charge transport and light absorption.

Promising for lightweight and high-efficiency PV applications.

2. Nitrogen Doped Single Layer Graphene for CZTS-Based Thin Film Solar Cells

Journal: Optical Materials (2024)
DOI: 10.1016/j.optmat.2024.115167
Highlights:

Uses nitrogen doping to tune electronic properties of graphene.

Applied in CZTS (Copper Zinc Tin Sulfide) solar cells — known for being earth-abundant and non-toxic.

💨 Hydrogen Storage and Fuel Cells

3. Optimizing Hydrogen Storage and Fuel Cell Performance Using Carbon-Based Materials

Journal: Hydrogen (March 2025)
DOI: 10.3390/hydrogen6020022
Highlights:

Studies effects of surface area and pressure on carbon-based hydrogen storage.

Bridges material design with real-world performance in fuel cells.

4. Hydrogen Storage Capacity of Two-Dimensional MoS₂

Journal: International Journal of Hydrogen Energy (2024)
DOI: 10.1016/j.ijhydene.2023.12.120
Highlights:

Focus on MoS₂ for reversible hydrogen storage.

Explores adsorption behavior on 2D surfaces.

5. Investigating Surface Area and Hydrogen Pressure Effects on LiH and NaH

Journal: Journal of Solid State Chemistry (2024)
DOI: 10.1016/j.jssc.2023.124483
Highlights:

Dives into metal hydrides (LiH and NaH).

Correlates structural properties with storage performance under different pressures.

 

 

Assist. Prof. Dr. Guillermo Escrivá-Escrivá | Energy | Academic and Industrial Synergy Award

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Assist. Prof. Dr. Guillermo Escrivá-Escrivá | Energy | Academic and Industrial Synergy Award

Universitat Politècnica de València, Spain.

Guillermo Escrivá-Escrivá is a distinguished professor in the Electrical Engineering Department at the Universitat Politècnica de València (UPV), Spain. He earned his Ph.D. in Industrial Engineering from UPV in 2009 and has been a faculty member since 2005. His research focuses on energy efficiency, renewable energies, and power system quality. Prior to his academic career, he worked as a facilities engineer in a major construction company from 2000 to 2005. Throughout his tenure at UPV, Professor Escrivá-Escrivá has collaborated on numerous national and European projects, contributing significantly to advancements in electrical engineering.

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Education 🎓

Guillermo Escrivá-Escrivá earned his Ph.D. in Industrial Engineering from the Universitat Politècnica de València (UPV) in 2009, where he also completed his undergraduate degree as an Ingeniero Industrial in 1999. His doctoral work laid the foundation for his long-term research into energy efficiency and power system quality, areas in which he has since become a recognized expert.​

Experience 🏫

Professor Escrivá-Escrivá has been a faculty member at the Universitat Politècnica de València (UPV) since 2005, rising through the academic ranks to his current position as Profesor Titular de Universidad (Associate Professor) in 2016. Prior to that, he served as Profesor Contratado Doctor (2011–2016), Profesor Ayudante Doctor (2010–2011), and Ayudante (2007–2010). He began his academic career as a Profesor Asociado in 2005. Before transitioning into academia, he gained industrial experience as a Facilities Engineer in a major construction company from 2000 to 2005, where he was involved in large-scale engineering projects. This combination of practical field experience and academic depth has significantly shaped his approach to research and teaching.

Research Interests 🔬

Energy Efficiency: Developing strategies to optimize energy consumption in various sectors.​

Renewable Energies: Integrating sustainable energy sources into existing power systems.​

Power System Quality: Enhancing the reliability and performance of electrical power systems.

Achievements & Contributions 🌟

Organized and delivered the technical workshop “Diseño de sistemas de climatización con aplicación de geotermia y carga virtual para la reducción de emisiones de CO₂” at the Colegio Aparejadores de Murcia.

Authored a technical article on sympathetic tripping in differential protections in industrial and commercial electrical systems.

Serves as an Advisory Board Member for Cambridge Scholars Publishing since 2018, contributing to editorial oversight and scientific quality.

Participated in the DERD Project, focused on the creation of an R&D laboratory for the optimized management of demand and distributed energy resources.

Selected ​​Publications 📚

🔋 Hybrid Energy Solutions for Rural Areas

Title: Hybrid Energy Solutions for Enhancing Rural Power Reliability in the Spanish Municipality of Aras de los Olmos
Journal: Applied Sciences (2025-03-30)
DOI: 10.3390/app15073790
Highlights:

Focuses on rural electrification and improving reliability using hybrid renewable systems.

Real-world case study in Aras de los Olmos, Spain.

Likely involves solar, wind, and storage integration.

🛠️ Fault Diagnosis in Electrical Machines

Title: Optimizing Bearing Fault Diagnosis in Rotating Electrical Machines Using Deep Learning and Frequency Domain Features
Journal: Applied Sciences (2025-03-13)
DOI: 10.3390/app15063132
Highlights:

Uses deep learning models and spectral analysis for predictive maintenance.

Enhances diagnostics accuracy for rotating electrical equipment.

♻️ Sustainable Biogas Integration

Title: Strategic Resource Planning for Sustainable Biogas Integration in Hybrid Renewable Energy Systems
Journal: Applied Sciences (2025-01-10)
DOI: 10.3390/app15020642
Highlights:

Addresses planning and modeling for incorporating biogas in hybrid systems.

Focuses on sustainability and energy resource optimization.

🏥 Fiber Optics for Electrical Monitoring in Hospitals

Title: Intelligent Residual Current Monitor Application in Hospital With Fiber Optics Using Wavelength Division Multiplexing
Journal: IEEE Access (2024)
DOI: 10.1109/ACCESS.2024.3494055
Highlights:

Innovates electrical safety with intelligent monitoring via fiber optics.

Applicable in sensitive environments like hospitals.

Uses WDM technology to multiplex signals.

⚙️ Multi-objective Optimization of Rural Microgrids

Title: Optimal sizing and design of renewable power plants in rural microgrids using multi-objective particle swarm optimization and branch and bound methods
Journal: Energy (2023-12)
DOI: 10.1016/j.energy.2023.129318
Highlights:

Applies PSO and branch-and-bound algorithms for system design.

Supports decision-making for renewable microgrids in rural setups.

Balances cost, emissions, and energy reliability.

 

 

 

Prof. Dr. László Gáspár | Road Engineering | Best Researcher Award

Published on by Invention Awards

Prof. Dr. László Gáspár | Road Engineering | Best Researcher Award

KTI Non-profit Ltd, Hungary.

Dr. habil. László GÁSPÁR is a distinguished Hungarian civil engineer, researcher, and professor emeritus renowned for his expertise in road engineering, pavement and bridge management, and sustainability in infrastructure. He has made an exceptional impact in academia and research through decades of groundbreaking contributions to transport engineering and infrastructure sustainability. He currently serves as a research professor at the KTI Hungarian Institute for Transport Sciences and Logistics and an emeritus professor at Széchenyi István University. Fluent in five languages, Dr. Gáspár has dedicated his life to advancing civil engineering, mentoring PhD students, and contributing to international collaborations.

Profile

Orcid

🎓 Education

Dr. Gáspár earned dual Master of Science degrees from the Technical University of Budapest, first in Civil Engineering (1966) and then in Economic Engineering within the Transport Faculty (1970). His academic journey continued with a Technical University Doctorate (1972), followed by a PhD (Candidate of Technical Sciences, 1979) and a Doctor of Technical Sciences (DSc, 1991). He achieved his habilitation in 1997 and was promoted to full university professor in 2000. He also holds a Euro-engineer diploma (1992) and received an honorary doctorate from Széchenyi István University in 2019.

💼 Experience

With over five decades of professional engagement, Dr. Gáspár's roles span across academia, industry, and public policy. He led soil stabilization and asphalt groups in the 1960s and later directed road laboratories and conducted pioneering research in pavement condition evaluation. His international experience includes study tours in Germany and the USA (Darmstadt, Stuttgart, Berkeley, Ann Arbor). Since 1990, he has chaired or participated in numerous global conferences, led or reviewed 12+ EU-funded projects, and served on scientific committees and doctoral councils. His dedication to research mentoring is evidenced by supervising both Hungarian and international PhD candidates.

🔬 Research Interests

Dr. Gáspár’s research encompasses a wide range of civil engineering domains:
🛣️ Pavement and bridge management, 🧪 asphalt and cement concrete technology, 🧭 road maintenance, 🔬 quality control, 📊 road condition forecasting, and 🌍 climate change impacts on infrastructure. He is especially recognized as an early advocate for lifetime engineering in Hungary and for integrating BIM and sustainability assessment frameworks into road and bridge design.

🏆 Awards & Honors

His numerous accolades include being an official candidate for the Hungarian Academy of Sciences (2003, 2006, 2009) and receiving the Doctor honoris causa (Dr. h.c.) from Széchenyi István University in 2019. He has also held significant roles such as non-academic representative in the Technical Sciences Section of the Hungarian Academy and project leader of cutting-edge research on climate-resilient roads and innovative rubber-bitumen technology.

📚 Selected Publications 

“Optimizing Foamed Bitumen Mixtures: AI-Based Determination of Ideal RAP and FBC Percentages Using HWTT and ITS Data”, Applied Sciences, 2025 — 🔗 DOI:10.3390/app15073780
🧾 Cited by: forthcoming

“Optimizing Sustainability in Bridge Projects: A Framework Integrating Risk Analysis and BIM with LCSA According to ISO Standards”, Applied Sciences, 2025 — 🔗 DOI:10.3390/app15010383
🧾 Cited by: forthcoming

“The Role of BIM in Managing Risks in Sustainability of Bridge Projects: A Systematic Review with Meta-Analysis”, Sustainability, 2024 — 🔗 DOI:10.3390/su16031242
🧾 Cited by: 3+

“Optimizing Sustainability in Bridge Projects”, Preprint, 2024 — 🔗 DOI:10.20944/preprints202411.1625.v1
🧾 Cited by: pending review