Zhi Guo | Medicine and Health Sciences | Editorial Board Member

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Prof. Dr. Zhi Guo | Medicine and Health Sciences | Editorial Board Member

Huazhong University of Science and Technology Union Shenzhen Hospital | China

Dr. Zhi Guo is a distinguished hematology researcher whose work focuses on hematological malignancies, hematopoietic stem cell transplantation, and tumor-related microecology. According to Scopus (Author ID: 24279665000), he has 77 indexed publications, 713 citations from 663 documents, and an h-index of 10, reflecting a solid and growing scholarly influence. His research has significantly advanced precision immunotherapy, particularly through clinical and translational innovations in CAR-T cell engineering, including anti-CD19, anti-CD7, and anti-BCMA CAR-T therapies, while contributing real-world evidence to lymphoma treatment and transplantation practices. He has also played a central role in developing expert consensus guidelines in tumor microecology, intestinal microbiota, and hematology-related infectious disease management. His research portfolio spans oral–intestinal microbiome interactions, graft-versus-host disease, microecological regulators, novel cryoprotectants, and stem-cell-based immunotherapies. With over ten completed or ongoing research projects, multiple consultancy-linked studies, and several books published with ISBN registration, he demonstrates strong multidisciplinary contributions to hematology and R&D innovation. His work in systematic reviews, meta-analyses, and multicenter clinical studies highlights his commitment to evidence-based medicine. Dr. Guo’s extensive experience in hematopoietic stem cell transplantation—supported by more than 1,300 clinical cases—continues to fuel impactful research outputs and leadership in national expert consensus development across oncology, immunology, and microecology research domains.

Profile: Scopus

Featured Publications

  • Guo, Z., et al. (2025). In vitro functional validation of anti-CD19 chimeric antigen receptor T cells expressing lysine-specific demethylase 1 short hairpin RNA for the treatment of diffuse large B cell lymphoma. Frontiers in Immunology, 15, 1521778. https://doi.org/10.3389/fimmu.2025.1521778

  • Guo, Z., et al. (2025). The case of T-cell acute lymphoblastic leukemia treated with chemotherapy followed by anti-CD7 CAR-T cells using retroviral vector. Frontiers in Immunology, 15, 1519055. https://doi.org/10.3389/fimmu.2025.1519055

  • Guo, Z., et al. (2025). Shaping oral and intestinal microbiota and the immune system during the first 1,000 days of life. Frontiers in Pediatrics, 13, 1471743. https://doi.org/10.3389/fped.2025.1471743

  • Guo, Z., et al. (2024). The role of fecal microbiota transplantation in the treatment of acute graft-versus-host disease. Journal of Cancer Research and Therapeutics, 20(7), 1964–1973. https://doi.org/10.4103/jcrt.jcrt_1372_22

  • Guo, Z., et al. (2024). Rapid response in relapsed follicular lymphoma to novel anti-CD19 CAR-T therapy with pseudo-progression and cytomegalovirus infection: A case report. International Immunopharmacology, 134, 112174. https://doi.org/10.1016/j.intimp.2024.112174

Nafiz Fahad | Computer Science | Best Researcher Award

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Mr. Nafiz Fahad | Computer Science | Best Researcher Award

Multimedia University | Malaysia

Mr. Nafiz Fahad is an emerging AI researcher at Multimedia University, Cyberjaya, Malaysia, recognized for his growing contributions to artificial intelligence in healthcare, computer vision, and natural language processing. His research focuses extensively on explainable AI, clinical decision support systems, and data-driven healthcare intelligence. According to Scopus, he has 19 indexed publications, 122 citations, and an h-index of 6, reflecting the influence and visibility of his scholarly work within the global research community. His scientific output spans chronic disease prediction, dementia analytics, lung disease classification, hypertension ontology development, wound-image segmentation, obesity prediction, and precision public health. These studies incorporate techniques such as deep learning, transfer learning, ensemble learning, hybrid architectures, and explainable machine learning to advance diagnostic accuracy and interpretability in medical AI systems. Beyond health-focused research, Fahad has also contributed high-impact work in fake news detection, generative AI, machine learning security, student performance prediction, agricultural disease detection, vision transformers for physics data, and federated learning enhanced with homomorphic encryption. His ongoing research extends to mental health analytics, EEG decoding models, diabetic retinopathy detection, and agentic AI solutions for healthcare innovation. Fahad’s growing academic recognition includes research awards, best paper achievements, and contributions to high-impact journals and conferences. His multidisciplinary scholarship positions him as a promising young researcher advancing applied AI at the intersection of healthcare, societal well-being, and intelligent systems.

Profiles: Scopus | Google Scholar | LinkedIn

Featured Publications

1. Ahmed, Z., Shanto, S. S., Rime, M. H. K., Morol, M. K., Fahad, N., Hossen, M. J., … (2024). The generative AI landscape in education: Mapping the terrain of opportunities, challenges and student perception. IEEE Access.

2. Mahamud, E., Fahad, N., Assaduzzaman, M., Zain, S. M., Goh, K. O. M., & Morol, M. K. (2024). An explainable artificial intelligence model for multiple lung diseases classification from chest X-ray images using fine-tuned transfer learning. Decision Analytics Journal, 12, 100499.

3. Ahmed, R., Fahad, N., Miah, M. S. U., Hossen, M. J., Morol, M. K., Mahmud, M., … (2024). A novel integrated logistic regression model enhanced with recursive feature elimination and explainable artificial intelligence for dementia prediction. Healthcare Analytics, 6, 100362.

4. Fahad, N., Goh, K. M., Hossen, M. I., Shopnil, K. M. S., Mitu, I. J., Alif, M. A. H., & Tee, C. (2023). Stand up against bad intended news: An approach to detect fake news using machine learning. Emerging Science Journal, 7(4), 1247–1259.

5. Hossain, M. N., Fahad, N., Ahmed, R., Sen, A., Al Huda, M. S., & Hossen, M. I. (2024). Preventing student’s mental health problems with the help of data mining. International Journal of Computing, 23(1), 101–108.

Surakasi Raviteja | Engineering | Excellence in Research Award

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Assist. Prof. Dr. Surakasi Raviteja | Engineering | Excellence in Research Award

Lendi Institute of Engineering and Technology | India

Dr. Surakasi Ravi Teja is a dedicated researcher whose work spans thermal engineering, nanofluids, biofuels, heat transfer augmentation, sustainable energy systems, and advanced materials science. His research expertise includes the experimental evaluation of thermophysical properties, development of nanomaterial-enhanced solar thermal fluids, ANN-based predictive modeling, biodiesel and pyrolysis-fuel combustion analysis, and CFD-driven optimization of thermal devices. With 77 Scopus-indexed publications, 960 citations, and an h-index of 17, he has established a strong scientific presence, contributing extensively to high-impact Scopus-, SCI-, and SCIE-indexed journals such as Frontiers in Heat and Mass Transfer, Journal of Nanomaterials, Materials Today: Proceedings, International Journal of Chemical Engineering, and Adsorption Science & Technology. His Q1–Q2 publications reflect significant advancements in areas including nanofluid stability, enhanced heat transfer, eco-friendly fuel blends with  , and nano-reinforced composite materials. His interdisciplinary works extend to solar water heating systems, cryogenic vessel design, adsorption-based separation technologies, and nanoparticle-assisted wastewater treatment. Several of his highly cited studies focus on waste-to-energy conversion, algae-oil biodiesel applications, and green-synthesized nanoparticles for environmental remediation, highlighting his contribution to sustainable and cleaner energy technologies. In addition to his research output, Dr. Teja serves as a reviewer for numerous national and international journals and holds editorial memberships, contributing to global scholarly communication and knowledge dissemination. His consistent research engagement, innovation-driven approach, and interdisciplinary collaborations underscore his impactful role in advancing thermal sciences, materials engineering, and renewable energy research.

Profiles: Scopus | Google Scholar | ORCID | Staff Profile

Featured Publications

  1. Sathish, T., Vijayalakshmi, A., Surakasi, R., Ahalya, N., Rajkumar, M., … (2024). DeepNNet 15 for the prediction of biological waste to energy conversion and nutrient level detection in treated sewage water. Process Safety and Environmental Protection, 189, 636–647.

  2. Senthil, T. S., Puviyarasan, M., Babu, S. R., Surakasi, R., & Sampath, B. (2023). Industrial robot-integrated fused deposition modelling for the 3D printing process. In Development, Properties, and Industrial Applications of 3D Printed Polymer Materials

  3. Lakshmaiya, N., Surakasi, R., Nadh, V. S., Srinivas, C., Kaliappan, S., … (2023). Tanning wastewater sterilization in the dark and sunlight using Psidium guajava leaf-derived copper oxide nanoparticles and their characteristics. ACS Omega, 8(42), 39680–39689.

  4. Nirmal Kumar, K., Dinesh Babu, P., Surakasi, R., Kumar, P. M., & Ashokkumar, P. (2022). Mechanical and thermal properties of bamboo fiber–reinforced PLA polymer composites: A critical study. International Journal of Polymer Science, 2022(1), 1332157.

  5. Vennila, T., Karuna, M. S., Srivastava, B. K., Venugopal, J., & Surakasi, R. (2023). New strategies in treatment and enzymatic processes: Ethanol production from sugarcane bagasse. In Human Agro-Energy Optimization for Business and Industry (pp. 219–240).

Qing Bao | Forensic Science | Editorial Board Member

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Dr. Qing Bao | Forensic Science | Editorial Board Member

Institute of Forensic Science of Shanghai Municipal Public Security Bureau | China

Dr. Qing Bao is an active researcher in pattern recognition, forensic science, and intelligent analysis technologies, with a strong focus on advancing computational methodologies that elevate the scientific rigor of evidence interpretation. His scholarly work integrates machine learning with forensic applications, enabling more accurate, reliable, and automated assessments across digital and physical investigation domains. He has contributed to internationally indexed journals with impactful research on semi-supervised learning, biometric enhancement, and anti-forensics techniques. His publication in Pattern Recognition introduces a semi-supervised prototype-based framework designed to mitigate the challenges posed by noisy labels in complex classification tasks. Complementing this, his research on noise transfer matrix analysis provides a significant advancement in the detection of anti-forensics video forgery, offering innovative insights into noise modeling for multimedia evidence authentication. He has further contributed a coarse-to-fine computational approach for rectifying distorted latent fingerprints, improving the precision and interpretability of crime-scene fingerprint analysis. Collectively, his research outputs underscore a commitment to bridging machine intelligence with forensic investigation, driving methodological innovation and enhancing real-world forensic practices. His work continues to influence the domains of digital forensics, biometric identification, and advanced image processing through rigorous experimentation, collaborative contributions, and forward-looking analytical frameworks.

Profile: ORCID

Featured Publications

  • Xia, Q., Lee, F., Xie, L., Yang, S., Bao, Q., & Chen, Q. (2026). CPSL: A semi-supervised framework with class prototype-based modeling for combating noisy labels. Pattern Recognition. Advance online publication. https://doi.org/10.1016/j.patcog.2025.112318

  • Bao, Q., Wang, Y., Hua, H., Dong, K., & Lee, F. (2024). An anti-forensics video forgery detection method based on noise transfer matrix analysis. Sensors, 24(16), 5341. https://doi.org/10.3390/s24165341

  • Bao, Q., Wang, Y., Gao, C., Sha, L., & Lee, F. (2023). A coarse-to-fine approach for rectifying distorted latent fingerprints from crime scenes. IEEE Access, 11, 123456–123467. https://doi.org/10.1109/access.2023.3344465

Nuno Moutinho | Economics, Econometrics and Finance | Editorial Board Member

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Prof. Dr. Nuno Moutinho | Economics, Econometrics and Finance | Editorial Board Member

Polytechnic Institute of Bragança | Portugal

Prof. Dr. Nuno Moutinho is an accomplished researcher specializing in Finance, Corporate Governance, Financial Markets, and Applied Economics, with strong expertise in event-study methodologies. His work provides valuable evidence on how financial markets respond to major global shocks, including cyber-attacks, corporate misconduct, IT outages, political events such as U.S. presidential elections, and corporate crises like the Evergrande collapse. He also conducts significant research on syndicated loan spreads, examining how borrower-country governance structures and financial system characteristics influence international lending dynamics. Prof. Dr. Nuno Moutinho’s research is published in high-impact, ABS-ranked and Scopus/WoS-indexed journals, including Finance Research Letters, International Review of Economics & Finance, Quarterly Review of Economics and Finance, Journal of Banking Regulation, Tourism Economics, and Corporate Governance. His contributions demonstrate strong interdisciplinary reach across sectors such as aviation, hospitality, insurance, biotechnology, fossil fuel, and renewable energy. With 25 Scopus-indexed publications, 31 citations, and an h-index of 3, Prof. Dr. Nuno Moutinho has established a solid scholarly footprint supported by international collaborations and frequent conference contributions. He has also authored books in finance and serves as a reviewer for respected journals, reinforcing his role in advancing empirical financial research and market-based governance insights.

Profiles: Scopus | Google Scholar | ORCID

Featured Publications

Martins, A. M., Albuquerque, B., Sardinha, L., & Moutinho, N. (2025). Impact of elections on the cannabis market: An event study for the 2024 US presidential election. International Review of Economics & Finance, Article 104683.

Martins, A. M., Moutinho, N., & Cró, S. (2025). Stock market effects of major cyber-attacks: Evidence for breached and cybersecurity listed firms. Journal of Banking Regulation, 1–10.

Martins, A. M., Albuquerque, B., Sardinha, L., & Moutinho, N. (2025). Presidential elections and secretary appointment: An event study for US biotechnology and drugs. Finance Research Letters, Article 108125.

Martins, A. M., Albuquerque, B., Sardinha, L., & Moutinho, N. (2025). 2024 US presidential elections: An event study for US and non-US fossil fuel and renewable listed firms. International Review of Financial Analysis, Article 104430.

Albuquerque, B., Cró, S., Moutinho, N., & Martins, A. M. (2025). Stock market effects of CrowdStrike IT outage on largest listed hotel companies. Tourism Economics, Article 13548166251321212.

Jean-Paul Montagner | Earth and Planetary Sciences | Best Researcher Award

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Prof. Jean-Paul Montagner | Earth and Planetary Sciences | Best Researcher Award

Paris Cité University, IPGP | France

Prof. Jean-Paul Montagner, based at the Institut de Physique du Globe de Paris, France (Scopus ID: 7004338438), is an eminent French seismologist internationally recognized for his groundbreaking research on the Earth’s deep structure, mantle dynamics, and seismic anisotropy. His pioneering contributions to seismic tomography, anisotropy inversion, and the understanding of mantle convection have significantly advanced global geophysics. According to Scopus, he has authored 156 scientific publications with 7,550 citations from 4,671 documents and holds an h-index of 46. His research spans a broad spectrum including mantle and core structure, seismic wave propagation in heterogeneous and anisotropic media, global and regional seismology, geophysical instrumentation, and planetary seismology. Prof. Jean-Paul Montagner has been instrumental in developing large-scale seismological networks such as GEOSCOPE and has led international collaborations integrating seismological data from multiple observatories. His work on three-dimensional Earth models and vectorial tomography has laid the foundation for modern seismic imaging of velocity and anisotropy structures. He has coordinated major European research and training programs, including the European RTN SPICE, ITN QUEST, and Erasmus Mundus GeoDES Doctoral School, fostering next-generation scientific excellence in global seismology. A recipient of numerous prestigious awards—including the Inge Lehmann Medal (AGU, 2021), Beno Gutenberg Medal (EGU, 2010), CNRS Bronze Medal (1988), and election as Fellow of the AGU (2004) Prof. Jean-Paul Montagner’s scientific influence extends across continents. He has served as editor, reviewer, and scientific board chair for leading journals and international programs, and as panelist for ERC Advanced Grants, AGU Fellows Selection Committee, and various European and Indo-French research committees. His intellectual leadership is further evidenced by his roles in organizing numerous high-level international workshops and conferences bridging seismology, geodynamics, and Earth system science. Prof. Jean-Paul Montagner’s research innovations continue to shape the understanding of Earth’s internal structure, seismic anisotropy, and dynamic processes linking geophysics with planetary exploration.

Profiles: Scopus | Google Scholar | ORCID | ResearchGate | LinkedIn

Featured Publications

• Montagner, J.-P., Romanowicz, B., Dongmo Wamba, M., & Burgos, G. (2025). Upwellings and mantle ponding zones in the lower mantle transition zone (660–1000 km). Geosciences, 15(11), 413. https://doi.org/10.3390/geosciences15110413

• Aminian, M. A., Crawford, W. C., Stutzmann, E., & Montagner, J.-P. (2025). Shallow crustal structures of the Indian Ocean derived from compliance function analysis. Geophysical Journal International, 242(3). https://doi.org/10.1093/gji/ggaf253

• Tang, L., Igel, H., Montagner, J.-P., & Hadziioannou, C. (2024). Seasonality of microseisms in Southern California from 6C ground motions. ESSOAr Preprint. https://doi.org/10.22541/essoar.172901301.13982448/v1

• Tang, L., Igel, H., Montagner, J.-P., & Vernon, F. (2024). Seismic anisotropy from 6C ground motions of ambient seismic noise. Journal of Geophysical Research: Solid Earth, 129(6). https://doi.org/10.1029/2024JB028959

• Tang, L., Igel, H., Montagner, J.-P., & Vernon, F. L. (2024). Seismic anisotropy from 6C ground motions of ambient seismic noise. Authorea Preprint. https://doi.org/10.22541/au.170967620.01260055/v1

Mukku Pavan Kumar | Space Exploration Technologies | Young Scientist Award

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Assoc. Prof. Dr. Mukku Pavan Kumar | Space Exploration Technologies | Young Scientist Award

Lendi Institute of Engineering and Technology | India

Dr. Mukku Pavan Kumar is a distinguished researcher from VIT-AP University, Amaravati, India, specializing in radiation-hardened memory circuits, in-memory computing architectures, and energy-efficient hardware accelerators for advanced space and GPU applications. His pioneering research focuses on the modeling, analysis, and design of radiation-tolerant SRAM and MRAM systems, leading to significant advancements in soft error resilience and self-recoverable circuit architectures. Dr. Mukku Pavan Kumar’s scholarly contributions include 12 Scopus-indexed publications with 118 citations from 78 documents and an h-index of 7 (Scopus Author ID: 57211979910, ORCID: 0000-0002-0756-8390). His research has been featured in high-impact journals such as IEEE Access, Microelectronics Reliability, Integration, Microsystem Technologies, and International Journal of Circuit Theory and Applications (Wiley). He has presented his works at leading IEEE conferences, including ISCAS, TENCON, ICEFEET, and DICCT, and holds a patent for a self-recoverable radiation-resistant memory cell designed for aerospace electronics. Recognized with multiple Best Paper Awards and the Best Researcher Award from VIT-AP University, his research significantly advances space-grade VLSI system reliability and next-generation chip design. In addition, Dr. Kumar serves as a peer reviewer for reputed journals such as IEEE Access, Wiley’s Journal of Electrical and Computer Engineering, and Microelectronics Reliability, and actively contributes to collaborative R&D initiatives focused on radiation-resilient chip design, AI-driven hardware accelerators, and space electronics innovation.

Profiles: Scopus | Google Scholar | ORCID | ResearchGate

Featured Publications

  • Mukku, P. K., & Lorenzo, R. (2023). A review on radiation‐hardened memory cells for space and terrestrial applications. International Journal of Circuit Theory and Applications, 51(1), 475–499. https://doi.org/10.1002/cta.3678

  • Mukku, P. K., & Lorenzo, R. (2023). Design and analysis of radiation hardened 10T SRAM cell for space and terrestrial applications. Microsystem Technologies, 29(10), 1489–1500. https://doi.org/10.1007/s00542-023-07589-2

  • Mukku, P. K., & Lorenzo, R. (2023). Double node upset immune RHBD-14T SRAM cell for space and satellite applications. IEEE Access, 11, 96256–96271. https://doi.org/10.1109/ACCESS.2023.3321957

  • Mukku, P. K., & Lorenzo, R. (2024). An efficient radiation hardening SRAM cell to mitigate single and double node upset soft errors. Microelectronics Reliability, 152, 115303. https://doi.org/10.1016/j.microrel.2024.115303

  • Satapathy, S. C., Bhateja, V., & Das, S. (2018). Smart intelligent computing and applications. In Proceedings of the Second International Conference on Smart Computing and Informatics (SCI) (Vol. 1). Springer. https://doi.org/10.1007/978-981-13-1921-1_1

Theano Kokkinaki | Psychology | Women Researcher Award

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Prof. Theano Kokkinaki | Psychology | Women Researcher Award

University of Crete | Greece

Professor Theano Kokkinaki is a distinguished developmental psychologist whose pioneering research focuses on mother–infant and father–infant interaction, intersubjectivity, emotion, and imitation in early development. Her work integrates micro-analysis of spontaneous interactions, cross-cultural studies, and neuroscientific approaches to understanding emotional coordination and social communication in infancy. She has authored and co-authored numerous influential publications in high-impact journals such as Frontiers in Psychology, European Journal of Developmental Psychology, Infant and Child Development, and Journal of Reproductive and Infant Psychology. Her seminal studies on infant imitation, emotional coordination, and vocal communication are widely cited internationally, reflecting her major contribution to developmental and intersubjective psychology. Professor Kokkinaki leads and participates in multiple national and international research projects funded by the European Union (Horizon Europe, Next Generation EU) and the Hellenic Foundation for Research and Innovation, focusing on topics such as premature infant development, autonomic nervous system maturation, and psychosocial factors in early growth. Her research impact is recognized through extensive citations, invitations as a guest editor and reviewer for leading psychology and pediatric journals, and awards from organizations including the Society of Cretan Scientists and the Lego Foundation. As a guest associate editor for Frontiers in Psychology and editorial board member for over ten international journals, she contributes to the global advancement of developmental and behavioral science. Her innovative findings on early emotional communication and intersubjectivity continue to shape research, theory, and practice in developmental psychology worldwide. According to her Google Scholar profile, Professor Kokkinaki has published extensively, with 1,266 total citations, an h-index of 16, and an i10-index of 23, underscoring her significant scholarly influence and lasting contribution to the field.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

  • Trevarthen, C., Kokkinaki, T., & Fiamenghi, G. A. Jr. (1999). What infants’ imitations communicate: With mothers, with fathers and with peers. Cambridge University Press.

  • Kokkinaki, T., & Kugiumutzakis, G. (2000). Basic aspects of vocal imitation in infant-parent interaction during the first 6 months. Journal of Reproductive and Infant Psychology, 18(3), 173–187.

  • Kugiumutzakis, G., Kokkinaki, T., Makrodimitraki, M., & Vitalaki, E. (2005). Emotions in early mimesis. In Emotional Development (pp. 161–182).

  • Keller, H., Papaligoura, Z., Künsemueller, P., Völker, S., Papaeliou, C., Lohaus, A., & Kokkinaki, T. (2003). Concepts of mother-infant interaction in Greece and Germany. Journal of Cross-Cultural Psychology, 34(6), 677–689.

  • Kokkinaki, T., & Vasdekis, V. G. S. (2015). Comparing emotional coordination in early spontaneous mother–infant and father–infant interactions. European Journal of Developmental Psychology, 12(1), 69–84