Belén Requena | Biotechnology | Research Excellence Award

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Dr. Belén Requena | Biotechnology | Research Excellence Award

San Pablo CEU University | Spain

Belén Paula Fernández Requena is a biotechnologist and academic researcher specializing in metabolomics, bioanalysis, lipid metabolism, and advanced imaging technologies. She holds a Bachelor’s degree in Biotechnology, a Master’s degree in Genetics and Cellular Biology, and a PhD in Health Sciences and Technology from CEU San Pablo University, where she is currently a full-time Profesor Contratado. Her doctoral work was conducted within the Excellence Research Group in Metabolomics and Bioanalysis (CEMBIO), focusing on molecular and metabolic mechanisms relevant to human health. Her international research experience spans leading European institutions, including Julius-Maximilians Universität Würzburg, IMDEA Food Institute, and Maastricht University, where she trained in single-cell imaging under the supervision of Prof. Ron Heeren. Her research interests include lipidomics, epigenetic regulation of metabolism, extracellular vesicles, plant and insect signaling mechanisms, and host–pathogen interactions, particularly lipid alterations associated with Leishmania infection and therapeutic response. Her work has contributed to interdisciplinary advances across biotechnology, molecular biology, and translational health research. Through sustained international collaboration and methodological innovation, she continues to advance metabolomics-driven approaches with long-term impact in biomedical and biotechnological sciences.


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Featured Publications


Plasma miRNA–Metabolite Dysregulation in People with HIV with Cirrhosis Despite Successful HCV Cure
Ana Virseda-Berdices, Raquel Behar-Lagares, Juan Berenguer, Juan González-García, Belén Fernández Requena et al.,
Pharmaceuticals, 2026. (Journal Article)

Addressing the Untargeted Lipidomics Challenge in Urine Samples: Comparative Study of Extraction Methods by UHPLC-ESI-QTOF-MS
Belén Fernández Requena, Carolina González-Riaño, Coral Barbas,
Analytica Chimica Acta, 2024. (WOS)

Comprehensive Lipidomic Analysis Reveals Further Insights into the Molecular Mechanism of Podocyte Lipotoxicity in Alport Syndrome
Amir Shabaka, Belén Fernández Requena, Carolina González-Riaño et al.,
Nephrology Dialysis Transplantation, 2024. (WOS)

LiLA: Lipid Lung-Based ATLAS Built Through a Comprehensive Workflow Designed for Accurate Lipid Annotation
Belén Fernández Requena, Sajid Nadeem, Vineel P. Reddy et al.,
Communications Biology, 2024. (Nature Portfolio)

Norhazwani Md Yunos | Data Science and Analytics | Research Excellence Award

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Dr. Norhazwani Md Yunos | Data Science and Analytics | Research Excellence Award

Universiti Teknikal Malaysia Melaka | Malaysia

Dr. Norhazwani Md Yunos is an accomplished computer scientist and academic whose work bridges theoretical algorithms and applied data analytics. She has authored 11 Scopus-indexed documents, receiving 68 citations with an h-index of 4, reflecting steady scholarly impact across multiple domains. Her educational background is grounded in computer science and algorithmic research, with strong foundations in graph theory, optimization, and computational complexity. Over her academic career, she has gained extensive experience as a lecturer and researcher, contributing to both fundamental theory and real-world applications. Her research interests span machine learning, sentiment analysis, network and community detection, optimization algorithms, big data analytics, and combinatorial optimization, including notable contributions to polynomial-space exact algorithms for the Traveling Salesman Problem (TSP) and modern studies on dynamic community detection and data-driven classification models. Dr. Md Yunos has published in reputable journals such as Alexandria Engineering Journal, Pertanika Journal of Science and Technology, and Journal of Electronic Materials, demonstrating interdisciplinary reach from algorithm design to intelligent systems. Her scholarly record includes peer-reviewed journal articles, conference papers, and book chapters, alongside recognition through high citation performance in selected works. Overall, her research portfolio highlights a sustained commitment to advancing computational methods, intelligent data analysis, and algorithmic efficiency for contemporary scientific and industrial challenges.

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Featured Publications

Dongju Yang | Computer Science and Artificial Intelligence | Research Excellence Award

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Dr. Dongju Yang | Computer Science and Artificial Intelligence | Research Excellence Award

North China University of Technology | China

Dr. Dongju Yang is an Associate Researcher and Assistant Lead Professor for Artificial Intelligence at North China University of Technology, with over a decade of academic and research experience in intelligent computing systems. She earned her Ph.D. in Computer Software and Theory from Northwestern Polytechnical University and previously conducted advanced research at the Institute of Computing Technology, Chinese Academy of Sciences. Her research focuses on Large Language Models, Retrieval-Augmented Generation (RAG), AI Agents, Knowledge Graphs, Natural Language Processing, Service Computing, and Data Intelligence, with strong application impact in smart elderly care and intelligent education. Dr. Yang has led more than ten competitive research projects as principal investigator, including a sub-project of China’s National Key R&D Program and an NSFC General Program, while contributing to multiple major national initiatives. She has contributed to one national standard and three group standards and received the Beijing Science and Technology Progress Award. Overall, her work bridges fundamental AI research with scalable, real-world technological impact and talent cultivation.


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Featured Publications

Intelligent Orientation Robot Based on Large Language Models and Retrieval-Augmented Generation
Dongju Yang, 5th International Conference on Artificial Intelligence and Computer Engineering (ICAICE), 2024. (WOS)

Multi-source Autoregressive Entity Linking Based on Generative Method
Dongju Yang, Weishui Lan, Communications in Computer and Information Science, 2024. (Book Chapter)

IoT Service Distributed Management Architecture and Service Discovery Method for Edge-Cloud Federation
Dongju Yang, International Journal of Grid and Utility Computing, 2022. (WOS)

Construction and Analysis of Scientific and Technological Personnel Relational Graph for Group Recognition
Dongju Yang, International Journal of Software Engineering and Knowledge Engineering, 2021. (WOS)

Research on User Demand-Driven Service Matching Methodology
Huiying Zhang, Dongju Yang, IEEE 6th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA), 2021.

Mayank Choubey | Mechanical Engineering | Research Excellence Award

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Dr. Mayank Choubey | Mechanical Engineering | Research Excellence Award

SGT University Gurugram Haryana | India

Dr. Mayank Choubey is an accomplished academic and researcher in the field of manufacturing engineering, currently serving as an Assistant Professor with strong expertise in advanced and digital manufacturing technologies. He holds a solid educational background in mechanical and manufacturing engineering and has gained substantial teaching and research experience at the undergraduate and postgraduate levels. His research interests span hybrid machining, additive and digital manufacturing, micro-machining, simulation-driven process optimization, and finite element analysis, with a focus on improving manufacturing efficiency and precision. He is the author of three ISBN-registered books and has five patents published or under process, demonstrating a strong orientation toward innovation and applied research. In addition, he serves on the editorial board of an academic journal and actively contributes as a peer reviewer. His academic contributions are supported by verified research documents and citation records available through recognized scholarly platforms. Overall, Dr. Choubey’s consistent research output, academic service, and innovation-driven mindset make him a deserving candidate for research excellence recognition.

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Featured Publications

A Review on Vibration-Assisted EDM, Micro-EDM and WEDM
K.P. Maity, M. Choubey, Surface Review and Letters, 26(05), 1830008, 2019. (Citations: 81)

Algae: A Potential Feedstock for Third Generation Biofuel
R.S. Powar, A.S. Yadav, C.S. Ramakrishna, S. Patel, M. Mohan, et al., Materials Today: Proceedings, 63, A27–A33, 2022. (Citations: 60)

Finite Element Modeling of Material Removal Rate in Micro-EDM Process with and without Ultrasonic Vibration
M. Choubey, K.P. Maity, A. Sharma, Grey Systems: Theory and Application, 10(3), 311–319, 2020. (Citations: 33)

Modeling and Process Simulation of Vibration Assisted Workpiece in Micro-EDM Using FEM
K.P. Maity, M. Choubey, World Journal of Engineering, 13(3), 242–250, 2016. (Citations: 16)

A Review on Various Methods to Improve Process Capabilities of Electrical Discharge Machining Process
M. Choubey, M. Rawat, Materials Today: Proceedings, 47, 2756–2764, 2021. (Citations: 10)

Valentin Ivanov | Electrical Engineering | Research Excellence Award

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Dr. Valentin Ivanov | Electrical Engineering | Research Excellence Award

University of Dschang | Cameroon

Valentin Y. Ivanov is a distinguished physicist and mathematician with dual Ph.D. degrees in Physics (Emission Electronics) and Mathematics (Integral Equations in Electron Optics), along with an M.D. in Physics focused on numerical design of high-power RF generators. With extensive experience in computational physics, electromagnetism, electron optics, and nonlinear beam dynamics, he has authored six monographs and over 300 peer-reviewed articles. His research encompasses high-current electron guns, accelerator structure simulations, microchannel plate amplifiers, and advanced numerical methods for 2D and 3D electrodynamics, electromechanics, and beam optics. Dr. Ivanov has successfully developed more than 20 computational codes for diverse applications, including crystal growth, hydrodynamics, gun design, ground motion analysis, and feedback control in accelerators. He has contributed to numerous international collaborations and publications, including SLAC and IEEE journals. His work has significantly influenced high-power RF sources and accelerator design, earning him recognition in computational and applied physics communities. Dr. Ivanov’s contributions are reflected in his h-index of 2, with over 12 citations and 7 publications. He continues to advance research in electron optics, computational methods, and high-performance simulations, combining theoretical insights with practical applications in accelerator physics and physical electronic instrumentation.

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Featured Publications


3-D Method for the Design of Multi or Sheet Beam RF Sources
V. Ivanov, K. Ko, A. Krasnykh, L. Ives, G. Miram, SLAC-PUB-9366, 2002.

An Electron Gun for a Sheet Beam Klystron
M.E. Read, G. Miram, R.L. Ives, A. Krasnykh, V. Ivanov, IEEE Plasma Phys., 2002, pp. 190–194.

Simulating Accelerator Structure Operation at High Power
V. Ivanov et al., SLAC-PUB-10731, 2003.

An Improved Version of TOPAZ 3D
V. Ivanov, A. Krasnykh, G. Scheitrum, A. Jensen, SLAC-PUB-10081, 2003.

Development of Multiple Beam Guns for High Power RF Sources for Accelerators and Colliders
R.L. Ives, G. Miram, A. Krasnykh, V. Ivanov et al., SLAC-PUB-10704, 2004.

X-Band Linear Collider R&D in Accelerating Structures Through Advanced Computing
Z. Li, N. Folwell, L. Ge, A. Guetz, V. Ivanov et al., EPAC-2004-MOPLT134, SLAC-PUB-10563, 2004.