Yu Xiao | Data Science | Research Excellence Award

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Dr. Yu Xiao | Data Science | Research Excellence Award

Beijing Normal University | China

Yu Xiao He is a lecturer at Beijing Normal University with a strong background in decision science and operations research. He received his B.S. degree in Communication Engineering from Sichuan University, Chengdu, China, in 2014, and earned his Ph.D. in Management Science from the National University of Defense Technology, China, in 2020. He worked at the National University of Defense Technology from 2020 to 2022 before joining Beijing Normal University. His research focuses on multi-criteria decision analysis (MCDA) and rank aggregation, as well as graph theory and voting theory, addressing challenges in ranking, consensus building, and decision support. To date, he has published 24 documents, which have collectively received 158 citations, resulting in an h-index of 8, reflecting his growing influence in his fields of expertise. His contributions combine rigorous theoretical development with practical applications, aiming to improve methods for aggregating rankings and supporting complex decision-making processes. Recognized for his interdisciplinary approach, he integrates engineering, management, and social-choice methodologies in his work. Overall, Yu Xiao He is a rising scholar whose research is advancing both the theory and practice of multi-criteria decision-making, ranking aggregation, and graph-based modeling, offering valuable insights for academics and practitioners alike.

Profiles : Scopus | Orcid

Featured Publications

Xiao, Y., Wang, B., Deng, Y., & Wu, J. (2025). “From ratings to rankings: A complementary approach for student evaluations of teaching in higher education.” Studies in Educational Evaluation.

Zhu, H., Xiao, Y., Chen, D., & Wu, J. (2025). “A robust rating aggregation method based on temporal coupled bipartite network.” Information Processing & Management.

Li, G., Xiao, Y., & Wu, J. (2024). “Rank aggregation with limited information based on link prediction.” Information Processing & Management.

Xiao, Y., Zhu, H., Chen, D., Deng, Y., & Wu, J. (2023). “Measuring robustness in rank aggregation based on the error-effectiveness curve.” Information Processing & Management.

Xiao, Y., Deng, H.-Z., Lu, X., & Wu, J. (2021). “Graph-based rank aggregation method for high-dimensional and partial rankings.” Journal of the Operational Research Society.

Lan Xie | COVID-19 Analysis | Research Excellence Award

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Assoc. Prof. Dr. Lan Xie | COVID-19 Analysis | Research Excellence Award

Tsinghua University | China

Assoc. Prof. Dr. Lan Xie is a leading researcher in drug discovery and traditional Chinese medicine (TCM) integration with modern biomedical technologies. She earned her M.D. in Clinical Medicine from Peking University and a Ph.D. in Biology from Tsinghua University. Dr. Xie completed postdoctoral training at Tsinghua University and a visiting scholar program at the University of Pittsburgh. She has held faculty positions at Tsinghua University since 2014, currently serving as Associate Professor at the School of Basic Medical Sciences. Her research focuses on combining TCM with systems biology, multi-omics, and artificial intelligence to develop novel therapeutic strategies. She pioneered the Molecular Materia Medica database and an intelligent TCM formulation algorithm leveraging gene expression profiles and dysregulated disease pathways. Her work has been recognized with numerous awards, including the Huaxia Medical Science and Technology Award, International Award for Contribution to Chinese Medicine, and multiple Tsinghua University teaching excellence awards. Dr. Xie’s research achievements encompass high-throughput TCM bioactive component screening, single-cell omics-based mechanistic studies, and pathway-guided intelligent drug formulation. With 1,716 citations by 47 documents, 47 publications, and an h-index of 24, her contributions continue to advance modern medicine by bridging traditional knowledge and cutting-edge technology.

Profile : Scopus

Featured Publications

“A universal gene expression signature-based strategy for the high-throughput discovery of anti-inflammatory drugs.” Inflammation Research. 2025.

“Identification of the fruit of Brucea javanica as an anti-liver fibrosis agent working via SMAD2/SMAD3 and JAK1/STAT3 signaling pathways.” Journal of Pharmaceutical Analysis. 2025.

“Pulsatilla chinensis functions as a novel antihyperlipidemic agent by upregulating LDLR in an ERK-dependent manner.” Chinese Medicine United Kingdom. 2024.

“Mechanism study of Xiaoyao San against nonalcoholic steatohepatitis-related liver fibrosis based on a combined strategy of transcriptome analysis and network pharmacology.” Pharmaceuticals. 2024.

Mauro Gallegati | computational economics | Best Researcher Award

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Prof. Mauro Gallegati | computational economics | Best Researcher Award

Università Politecnica delle Marche | Italy

Mauro Gallegati is an influential economist internationally recognized for his contributions to complexity economics, agent-based modeling, and financial instability analysis. He serves as a Full Professor at the Università Politecnica delle Marche, building on earlier academic appointments at the Universities of Teramo, Pescara, and Urbino. His academic foundation includes a Laurea in Political Science and a PhD in Economics under the supervision of Hyman Minsky, shaping his long-standing interest in credit dynamics, business fluctuations, and systemic risk. Over the course of his career, he has held numerous visiting positions at leading global institutions, including Cambridge, Stanford, MIT, Columbia, Kyoto, ETH Zurich, Santa Fe Institute, and the Bank of International Settlements, reflecting the international demand for his expertise. His research encompasses econophysics, income distribution, macroeconomic network models, credit propagation, and financial fragility, resulting in widely cited publications and collaborations with scholars such as Stiglitz, Battiston, and Greenwald. He has coordinated major European research projects, contributed to editorial leadership across multiple journals and book series, and received notable distinctions including the JEBO Best Paper Prize, the WEHIA Prize, DOSI Prize, KNAPP Prize, and Presidential Medals. He continues to advance interdisciplinary economic research and the development of agent-based methodologies for understanding complex economic systems.

Profile : Google Scholar

Featured Publication

Battiston, S., Gatti, D.D., Gallegati, M., Greenwald, B., & Stiglitz, J.E. (2012). “Liaisons dangereuses: Increasing connectivity, risk sharing, and systemic risk” in Journal of Economic Dynamics and Control, 36(8), 1121–1141.

Caiani, A., Godin, A., Caverzasi, E., Gallegati, M., Kinsella, S., & Stiglitz, J.E. (2016). “Agent based-stock flow consistent macroeconomics: Towards a benchmark model” in Journal of Economic Dynamics and Control, 69, 375–408.

Gatti, D.D., Di Guilmi, C., Gaffeo, E., Giulioni, G., Gallegati, M., & Palestrini, A. (2005). “A new approach to business fluctuations: heterogeneous interacting agents, scaling laws and financial fragility” in Journal of Economic Behavior & Organization, 56(4), 489–512.

Battiston, S., Gatti, D.D., Gallegati, M., Greenwald, B., & Stiglitz, J.E. (2007). “Credit chains and bankruptcy propagation in production networks” in Journal of Economic Dynamics and Control, 31(6), 2061–2084.

Tola, V., Lillo, F., Gallegati, M., & Mantegna, R.N. (2008). “Cluster analysis for portfolio optimization” in Journal of Economic Dynamics and Control, 32(1), 235–258.

Umme Habiba | Machine Learning and AI Applications | Research Excellence Award

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Mrs. Umme Habiba | Machine Learning and AI Applications | Research Excellence Award

North Dakota State University(NDSU) | United States

Umme Habiba is a dedicated researcher and educator in computer science whose work centers on machine learning, deep learning, transformer-based architectures, explainable AI, and swarm intelligence, particularly within medical data analysis. She is pursuing her Ph.D. and M.Sc. in Computer Science at North Dakota State University, where she has gained extensive teaching experience as an instructor of record and graduate teaching assistant across several undergraduate courses. Her research contributions span clinical text mining, medical risk prediction, brain–computer interface modeling, IoT security, and usability analysis of mHealth applications, with publications in reputable international journals. She has also collaborated on projects involving mobile sensor–based spatial analysis, voice-controlled IoT automation systems, and hybrid ML models for network intrusion detection. Her academic journey began with a bachelor’s degree in Computer Science and Engineering, where she developed a strong foundation in data-driven system design and intelligent applications. She has received consistently high teaching evaluations and has demonstrated a commitment to interdisciplinary research and student learning. Her long-term goal is to contribute impactful solutions at the intersection of artificial intelligence and healthcare while advancing as both a researcher and an educator.

Profile : Orcid

Featured Publication

PSO-optimized TabTransformer architecture with feature engineering for enhanced cervical cancer risk prediction, 2026

David Almorza | Statistical Analysis | Best Researcher Award

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Dr. David Almorza | Statistical Analysis | Best Researcher Award

University of Cádiz | Spain

Dr. David Almorza Gomar is a Profesor Titular in the Department of Statistics and Operational Research at the University of Cádiz, Spain. He earned his Ph.D. in Mathematics from the University of Cádiz in 1998, with a doctoral thesis on the characterization of the Pólya distribution. Over his academic career, he has authored more than 85 publications. According to Google Scholar, his work has been cited 379 times, and he holds an h-index of 11. His early research focused on environmental statistics, probability distributions and genetics, while more recently he has explored applied statistics in education, well‑being (happiness), and sports, particularly university football. Among his notable contributions is a 2022 study evaluating an experience of “academic happiness” through football, published in the International Journal of Environmental Research and Public Health, showing how rule changes promoted fair play and reduced disciplinary sanctions. He has also applied multivariate statistical techniques to maritime safety in a recent work on the Paris MoU inspections. For his scientific achievements, he has been recognized by the Genetic Society of Argentina with a medal. In sum, Dr. Almorza is a versatile statistician whose interdisciplinary research spans mathematics, genetics, education, and sport, contributing both theoretical insight and practical societal impact.

Profiles : Scopus | Orcid

Featured Publications

Bazco Nogueras, E., Sanagustín-Fons, V., & Almorza-Gomar, D. (2025). “Job stress in industrial company: The impact of gender, age and seniority on tension levels” in Anduli.

Almorza Salas, D. (2025). “La imprenta en Cádiz: 1960, 1961 y 1962” in Gaditana-Logía.

Prieto, J. M., Almorza, D., Amor-Esteban, V., & Endrina, N. (2025). “Review of ship risk analyses through deficiencies found in port state inspections” in Journal of Marine Science and Engineering.

Prieto, J. M., Almorza, D., Amor-Esteban, V., Muñoz-Perez, J. J., & Jigena-Antelo, B. (2025). “Identification of risk patterns by type of ship through correspondence analysis of port state control: A differentiated approach to inspection to enhance maritime safety and pollution prevention” in Oceans.

Almorza, D., Prieto, J. M., Amor-Esteban, V., & Piniella, F. (2024). “Port state control inspections under the Paris Memorandum of Understanding and their contribution to maritime safety: Additional risk classifications and indicators using multivariate techniques” in Journal of Marine Science and Engineering.

Hisao Nakai | Public Health Analytics | Best Researcher Award

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Dr. Hisao Nakai | Public Health Analytics | Best Researcher Award

Faculty of Nursing, University of Kochi | Japan

Dr. Hisao Nakai is an Associate Professor in the Faculty of Nursing at the University of Kochi, specializing in disaster nursing, disaster management, and GIS‑based risk assessment. Holding a Ph.D. in Health Sciences from Kanazawa University, he has published 28 documents, which have been cited 107 times by 96 documents, resulting in an h-index of 7. His research centers on vulnerable populations—such as medically dependent children, older adults, and people with mental illness—and uses participatory ICT/IoT systems like K‑DiPS, which he helped develop, to support personalized disaster readiness, evacuation planning, power backup, and business continuity. He has applied GIS to simulate evacuation routes (e.g., for tsunamis) and assess environmental risks, especially for those with special needs. Academically, he has held roles at Kanazawa Medical University and Kochi University and has received awards including a Japanese Public Health Society poster prize. He has also led national surveys on disaster information sharing among caregivers of children requiring medical care. Through his interdisciplinary, community‑oriented work, Dr. Nakai is advancing equitable disaster resilience for people often overlooked in traditional emergency planning, combining practical applications with innovative research in disaster preparedness and nursing science.

Profile : Scopus

Featured Publications

Nakai, H., Oe, M., Nagayama, Y., Tokuoka, M., Yamaguchi, C., & Tanaka, K. (2025). “A retrospective study on evacuation and long-term displacement among home-visit psychiatric nursing service users in the aftermath of the 2024 Noto Peninsula Earthquake” in International Journal of Environmental Research and Public Health.

Oe, S., Nakai, H., Nagayama, Y., Oe, M., & Yamaguchi, C. (2025). “Factors associated with worsening post-earthquake psychiatric symptoms in patients receiving psychiatric visiting nurse services during the 2024 Noto Peninsula Earthquake: A retrospective study” in Psychiatry International.

Nitta, Y., Hashimoto, R., Shimizu, Y., Nakai, Y., & Nakai, H. (2025). “Adherence to outpatient care among individuals with pre‐existing psychiatric disorders following the 2024 Noto Peninsula Earthquake: A retrospective study” in Psychiatry and Clinical Neurosciences Reports.

Nakai, H., Oe, M., & Nagayama, Y. (2024). “Factors related to evacuation intention when a Level 4 evacuation order was issued among people with mental health illnesses using group homes in Japan: A cross-sectional study” in Medicine.

Nakai, H., Ishii, K., & Sagino, T. (2024). “Turnover intention among staff who support older adults living alone in Japan: A cross-sectional study” in Social Sciences.

Eva Ternon | Environmental Data Analysis | Best Researcher Award

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Mrs. Eva Ternon | Environmental Data Analysis | Best Researcher Award

CNRS/Laboratory of Oceanography of Villefranche | France

Dr . Eva Ternon is a chemical oceanographer and natural‑products chemist whose work spans atmospheric deposition, seawater biogeochemistry and the chemical ecology of harmful microalgae. After obtaining her PhD on atmospheric deposition in the Mediterranean Sea at the Laboratory of Oceanography of Villefranche (LOV), she held positions in France, the USA and Monaco, working on topics such as algicidal compounds, benthic organism chemistry and toxin‑producing dinoflagellates. In October 2024 she secured a permanent CNRS researcher position at LOV after ranking 1st/120 in the national contest for the “Science to Society” section. Her current research focuses on the chemical ecology of toxic dinoflagellates (particularly Ostreopsis cf. ovata), aerosols of phycotoxins, mucus‑mediated microalgal interactions and discovery of novel toxin families. She has published around 27 peer‑reviewed documents (14 as 1st or 2nd author), been cited ~493 times by ~402 documents, and holds an approximate h‑index of 13. She leads major projects including a MSCA Global Fellowship and H2020 CHEMICROS. Her discoveries of two new toxin families earned her the Nice Côte d’Azur Metropole Entrepreneurship Award in 2022, and she was among the interviewees for an ERC CoG call in 2024. With her dual expertise and interdisciplinary trajectory, she is advancing our understanding of how external drivers and chemical interactions shape harmful algal blooms and air‑sea toxin transfer.

Profiles : Scopus | Orcid

Featured Publications

Alexander, K. L., Naman, C. B., Iwasaki, A., Mangoni, A., Leao, T., Reher, R., Petras, D., Kim, H., Ternon, E., Caro-Diaz, E. J. E., et al. (2025). “Fatuamide A, a Hybrid PKS/NRPS Metallophore from a Leptolyngbya sp. Marine Cyanobacterium Collected in American Samoa.” Journal of Natural Products.

Ternon, E., Dinasquet, J., Cancelada, L., Rico, B., Moore, A., Trytten, E., Prather, K. A., Gerwick, W. H., & Lemée, R. (2024). “Sea-Air Transfer of Ostreopsis Phycotoxins Is Driven by the Chemical Diversity of the Particulate Fraction in the Surface Microlayer.” Environmental Science & Technology.

Fleming, L. E., Landrigan, P. J., Ashford, O. S., Whitman, E. M., Swift, A., Gerwick, W. H., Heymans, J. J., Hicks, C. C., Morrissey, K., White, M. P., et al. (2024). “Enhancing Human Health and Wellbeing through Sustainably and Equitably Unlocking a Healthy Ocean’s Potential.” Annals of Global Health.

Lanceleur, R., Gémin, M.-P., Blier, A.-L., Meslier, L., Réveillon, D., Amzil, Z., Ternon, E., Thomas, O. P., & Fessard, V. (2024). “Toxic Responses of Metabolites Produced by Ostreopsis cf. ovata on a Panel of Cell Types.” Toxicon.

Skelton, Z. R., McCormick, L. R., Kwan, G. T., Lonthair, J., Neira, C., Clements, S. M., Martz, T. R., Bresnahan, P. J., Send, U., Giddings, S. N., et al. (2024). “Organismal Responses to Deteriorating Water Quality during the Historic 2020 Red Tide off Southern California.” Elementa: Science of the Anthropocene.

Wan Siti Nur Atirah Wan Mohd Azemin | Optimization Techniques | Best Researcher Award

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Dr. Wan Siti Nur Atirah Wan Mohd Azemin | Optimization Techniques | Best Researcher Award

Universiti Sains | Malaysia

Dr. Wan Siti Nur Atirah Wan Mohd Azemin is a Senior Lecturer with a PhD in Animal Cell Biotechnology from Universiti Sultan Zainal Abidin (UniSZA), an MSc in Bioscience, and a BSc in Industrial Biology from Universiti Teknologi Malaysia (UTM). Her research expertise spans cancer biology, green nanotechnology, and bioinformatics, with a focus on therapeutic peptides, antimicrobial mechanisms, and computational protein analyses. Dr. Azemin’s current work emphasizes the green synthesis of silver nanoparticles using Pandanus amaryllifolius extracts for antimicrobial textile applications, with dual potential against pathogenic microbes and breast cancer cells. Her previous studies on HepTH1-5 peptides, marine-derived antimicrobial compounds, and computational biology have established a strong foundation in cytotoxicity, antimicrobial activity, and protein interaction networks. She has published extensively in high-impact journals and presented at international conferences. Recognized for her contributions, she has received multiple awards, including gold and silver medals in international innovation competitions, and holds a copyright for her innovative nanoparticle-based antimicrobial PPE research. Beyond research, she actively engages in educational and alumni initiatives, promoting science and innovation. Dr. Azemin’s work reflects a commitment to sustainable, translational solutions in biomedical and nanotechnology applications, bridging fundamental research with practical healthcare and environmental impact.

Profiles : Scopus | Orcid

Featured Publications

Hassan, H.; Norizham, I. M.; Mohd, M. H.; Mohamad Zin, N.; Bustami, Y.; Azemin, W.‑A.; Dual‑Spectrum Antimicrobial Nylon for Healthcare: Pandanus amaryllifolius Silver Nanoparticles Combat ESKAPK Pathogens and Fungal Infections. Fibers and Polymers. 2025‑10‑24.

Azemin, W.‑A.; Ab Rashid, S.; Philip, N.; Ali, A. M.; Shamsir, M. S.; Fish‑derived hepcidins in cancer treatment: a scoping review. Beni‑Suef University Journal of Basic and Applied Sciences. 2025‑01‑28.

Mendu, C.; Ab Rashid, S.; Azemin, W.‑A.; Philip, N.; Current antibiotics for leptospirosis: Are still effective? Heliyon. 2025‑01‑15. (Conceptualization)

Salikin, N. H.; Keong, L. C.; Azemin, W.‑A.; Philip, N.; Yusuf, N.; Daud, S. A.; Ab Rashid, S.; Combating multidrug‑resistant (MDR) Staphylococcus aureus infection using terpene and its derivative. World Journal of Microbiology and Biotechnology. 2024.

Razali, S. A.; Ishak, N. F.; Azemin, W.‑A.; Low, C.‑F.; Shamsir, M. S.; Riding the wave of innovation: immunoinformatics in fish disease control. PeerJ. 2023.

Hatice Zeynep Kosar |  Interdisciplinary Data Insights | Global Insight Excellence Award

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Ms. Hatice Zeynep Kosar |  Interdisciplinary Data Insights | Global Insight Excellence Award

Dokuz Eylül University | Turkey

Dr Hatice Zeynep Kosar holds a PhD in Laboratory Animal Science from Dokuz Eylül University (Turkey), an Associate Degree in Law from Anadolu University and a Bachelor of Veterinary Medicine from Uludağ University (Türkiye). At Dokuz Eylül University’s Multidisciplinary Department of Laboratory Animal Science she has contributed to advancing experimental research infrastructure and ethical standards. Her research centres on laboratory animal facility design and the application of the 3R (Replacement, Reduction, Refinement) principles in animal experiments. She co-authored a 2024 study on physical conditions in conventional laboratory animal facilities and a 2025 article in the African Journal of Urology examining differences between countries in experimental partial nephrectomy procedures. She holds a patent application (No: 2024-GE-122346) for a platform serving as a transport unit and safety cabin for laboratory animals. She is a member of the Springer Nature Research Communities (Biomedical Research, Research Data) and participates in COST Action CA21139 (“Improving the Quality of Biomedical Science with 3R Concepts”). Her contributions emphasise the ethical and scientific rigour of animal experimentation and call for harmonised global standards in this area. This global-insight excellence award nomination honours her efforts to merge animal welfare with rigorous experimental design and to promote international research ethics.

Profile : Orcid

Featured Publications

Koşar, H.Z. (2024). Are there differences between countries in the application of experimental partial nephrectomy procedures? 5th International Ethics Congress. Writing – review and editing, Conceptualization.

Yılmaz, O., & Koşar, H.Z. (2024). Konvansiyonel laboratuvar hayvan tesisinde, aktif kullanım süresince, mekanlar arasındaki fiziksel şartlarda farklılık var mıdır? Laboratuvar Hayvanları Bilimi ve Uygulamaları Dergisi.

Koşar, H.Z., & Yılmaz, O. (2023). A case of ulcerative pododermatitis in Balb/c mice. 5th National Laboratory Animal Science Congress, İstanbul, Türkiye. 18 September 2023. Conference Paper.

Koşar, H.Z., Yılmaz, O., & Keskinoğlu, P. (2025). Are there differences between countries in the application of experimental partial nephrectomy procedures? [Journal Title not specified] Conceptualization.

Koşar, H.Z. (2023). Are there differences between countries in the application of the 3R rule in experimental animal research? 5th National Laboratory Animal Science Congress, İstanbul, Türkiye. 18 September 2023. Conference Paper.

Anatoly Vershinin | Algorithm Development | Best Researcher Award

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Prof. Anatoly Vershinin | Algorithm Development | Best Researcher Award

Lomonosov Moscow State University | Russia

Professor Anatoly Vershinin is a distinguished computational mechanics researcher at Lomonosov Moscow State University, holding a Doctorate in Physical and Mathematical Sciences. Graduating with honors from the Faculty of Mechanics and Mathematics in 2006, he has been a core member of the Chair of Computational Mechanics since 2009. With an h-index of 11 and over 321 citations, Professor Vershinin has authored 51 journal articles, 4 books, and holds 33 patents, contributing significantly to numerical modeling, high-performance computing, and computational mechanics. His research focuses on numerical discretization methods for nonlinear partial differential equations and parallel algorithms for massively parallel computing systems, underpinning the industrial structural engineering software CAE Fidesys. He has led or contributed to 11 research projects and multiple consultancy initiatives in collaboration with institutes such as the Schmidt Institute of Physics of the Earth and Saudi Aramco Moscow Innovation Center. An active member of the International Program Committee for “Advanced Mechanics: Structure, Materials, Tribology,” he bridges academia and industry, driving innovations in structural analysis and computational methods. His contributions have earned recognition for advancing numerical methods, high-performance simulations, and practical engineering applications, establishing him as a leading figure in computational mechanics research.

Profiles : Scopus | Orcid | Research Gate

Featured Publications

Yarushina, V. M.; Podladchikov, Y. Y.; Vershinin, A. V. (2025). “A Micromechanical Model for Mineral Replacement Reactions and Associated Deformation: From Pore Clogging to Solid Volume Increase” in American Journal of Science.

Ampilov, Y. P.; Vershinin, A. V.; Kunchenko, D. S.; Petrovsky, K. A.; Safuanova, K. R. (2025). “Prediction of Thin-Layer Thickness Using Seismic Full-Waveform Modeling” in Moscow University Geology Bulletin.

Levin, V. A.; Vershinin, A. V. (2024). “CAE Fidesys as the Implementation of Fundamental Results of Computational Mechanics into Industry” in International Scientific Conference “Advanced Mechanics: Structure, Materials, Tribology”, Samarkand, Uzbekistan, 23-26 сентября 2024. Abstracts

Levin, V. A.; Vershinin, A. V.; Yakovlev, M. Ya; Levchegov, I. O.; Zhmurovsky, A. A. (2024). “Computed Tomography Based Stress-Strain Analysis of Heterogeneous Models of Rocks and Biological Tissues Using Unstructured Meshes” in Russian Physics Journal.

Vershinin, A.; Ampilov, Y.; Levin, V.; Petrovsky, K. (2024). “Full waveform modeling in seismic exploration based on a digital geological model using spectral element method on GPU” in 16th World Congress on Computational Mechanics and 4th Pan American Congress on Computational Mechanics.