Anna Schiefer | Medicine and Dentistry | Research Excellence Award

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Ms. Anna Schiefer | Medicine and Dentistry | Research Excellence Award

Charité – Universitätsmedizin Berlin | Germany

Ms. Anna Schiefer is an emerging researcher whose work focuses on fracture-related infections, prosthetic joint infections, and regenerative approaches in orthopaedics and traumatology. Her research has been presented at several major international conferences, including the Fracture-Related Infections Workshop and Prosthetic Joint Infections Workshop hosted by the PRO-IMPLANT Foundation, as well as the 6th Congress of the European Society of Tissue Regeneration in Orthopaedics and Traumatology and multiple annual meetings of the European Bone and Joint Infection Society. She has contributed posters and oral presentations highlighting key findings from her doctoral research on infection characteristics and outcomes following intramedullary nailing in femur and tibia fractures. Her scholarly engagement began early, with participation in academic meetings such as the Material Driven Regeneration Annual Meeting, Orthopedic Science Day at Maastricht University, the Omkadering van Jonge Onderzoekers Initiative at KU Leuven, and the MOSA biomedical research conference. She has received competitive scholarships from the PRO-IMPLANT Foundation to support cohort studies on fracture-related and prosthetic joint infections, reflecting the clinical relevance of her work. Her contributions have earned notable recognition, including the Silver Prize for Free Papers at the 6th ESTROT Congress. Her 2026 journal article in Injury further underscores her contributions to infection research within trauma surgery.

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Featured Publication

**Schiefer, A., Renz, N., Steiner, G., Märdian, S., Stöckle, U., Trampuz, A., & Meller, S. (2026). Infection after intramedullary nailing for femur and tibia fractures: Characteristics and outcome analysis. Injury.

Petro Pavlenko | Engineering | Research Excellence Award

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Prof. Dr. Petro Pavlenko | Engineering | Research Excellence Award

Zhejiang Ocean University | China

Prof. Dr. Petro Pavlenko is a distinguished researcher whose contributions span engineering design, CAD/CAM/CAE/PDM systems, digital manufacturing, and integrated information environments for industrial applications. With an h-index of 4, 27 documents, and 53 citations, his scholarship reflects both depth and sustained relevance across engineering and information technology domains. His research encompasses automation of design processes, digital 3D modeling, production data management, logical-dynamic models for information security, digital twins, robotics, energy lifecycle management, and industrial information system integration. He has produced more than 250 scientific publications, including 43 international journal papers, alongside 9 patents and multiple influential textbooks and monographs on mathematical modeling, information systems, and production automation. His leadership roles include chairing specialized academic councils, contributing to expert committees in informatics and cybernetics, directing research laboratories, and guiding PhD program development. Collaborations with universities and research centers across Ukraine, Kazakhstan, Germany, France, Latvia, and Russia have supported advancements in automated manufacturing, robot trajectory planning, and industrial data technologies. His recent works focus on additive manufacturing, microstructure–hardness modeling, digital energy systems, and intelligent information support, reinforcing his impact on modern engineering innovation and computational design methodologies.

 

 

Citation Metrics (Scopus)

60

40

20

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0

Citations
53

Documents
27

h-index
4



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Featured Publications

Haiwei Wu | Engineering | Best Researcher Award

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Prof. Dr. Haiwei Wu | Engineering | Best Researcher Award

Jilin Agricultural University | China

Prof. Dr. Haiwei Wu is an emerging multidisciplinary researcher whose contributions span energy systems, machine learning, spectroscopy, and intelligent diagnostics. His recent research focuses on advanced computational methods applied to energy storage and electric vehicle systems, including the development of an attention-based multi-feature fusion physics-informed neural network for accurate state-of-health estimation of lithium-ion batteries and the application of queuing-theoretic models for sustainable EV charging infrastructure planning. Beyond energy research, he has contributed significantly to the use of mid-infrared spectroscopy combined with machine learning and support vector machines for the authentication and identification of biological and agricultural products, reflecting strong capabilities in analytical modeling and pattern recognition. His publications from 2022 to 2025 highlight expertise in spectral analysis, counterfeit detection, and quality assessment. In addition, he has explored applications of improved YOLOv8 for mechanical part inspection and contributed to research on task-driven cooperative inquiry learning in education. His innovative work is supported by several patents related to electric vehicle charging technologies, demonstrating a commitment to advancing practical, technology-driven solutions across sectors.

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Featured Publications

Wu, H., Liu, J., Wang, Z., & Li, X. (2025). An attention-based multi-feature fusion physics-informed neural network for state-of-health estimation of lithium-ion batteries. Energies.

Wang, Z., Zou, J., Tu, J., Li, X., Liu, J., & Wu, H. (2025). Towards sustainable EV infrastructure: Site selection and capacity planning with charger type differentiation and queuing-theoretic modeling. World Electric Vehicle Journal.

He, T., Kaimin, W., & Wu, H. (2025). Research on the construction and implementation of a task-driven cooperative inquiry learning model for postgraduate students majoring in music education. Chinese Music Education, (05), 47–53.

Yang, C.-E., Wu, H., Yuan, Y., et al. (2025). Efficient recognition of plum blossom antler hats and red deer antler hats based on support vector machine and mid-infrared spectroscopy. Journal of Jilin Agricultural University, 1–7.

Yang, C.-E., Su, L., Feng, W.-Z., Zhou, J.-Y., Wu, H.-W., Yuan, Y.-M., & Wang, Q. (2023). Identification of Pleurotus ostreatus from different producing areas based on mid-infrared spectroscopy and machine learning. Spectroscopy and Spectral Analysis.

Yang, C.-E., Su, L., Feng, W., et al. (2023). Identification of Pleurotus ostreatus from different origins by mid-infrared spectroscopy combined with machine learning. Spectroscopy and Spectral Analysis, 43(02), 577–582.

Yang, C.-E., Wu, H.-W., Yang, Y., Su, L., Yuan, Y.-M., Liu, H., Zhang, A.-W., & Song, Z.-Y. (2022). A model for the identification of counterfeited and adulterated Sika deer antler cap powder based on mid-infrared spectroscopy and support vector machines. Spectroscopy and Spectral Analysis.

Yang, C.-E., Wu, H., Yang, Y., et al. (2022). Identification model of counterfeiting and adulteration of plum blossom antler cap powder based on mid-infrared spectroscopy and support vector machine. Spectroscopy and Spectral Analysis, 42(08), 2359–2365.

Fucan Huang | Engineering | Excellence in Research Award

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Dr. Fucan Huang | Engineering | Engineering | Excellence in Research Award

Shandong University of Science and Technology | China

Dr. Fucan Huang is an emerging researcher in mechanical fault diagnosis, known for advancing intelligent diagnostic methods through deep learning, multi-attention mechanisms, and cross-domain adaptability. His work focuses on improving fault detection accuracy in complex industrial environments, particularly under fluctuating conditions, imbalanced datasets, and multi-source domain challenges. He has contributed significantly to Measurement Science and Technology and Machines, co-authoring several influential papers. His research includes the development of an adaptive attenuation self-attention adversarial network for cross-domain diagnosis, a multi-source domain collaborative bearing fault method guided by multi-attention mechanisms, and innovative dual-domain vision transformer frameworks. These contributions enhance the robustness, generalizability, and interpretability of diagnostic models, strengthening intelligent maintenance systems and promoting safer, more efficient industrial operations.

Profile : Orcid

Featured Publications

An, Y., Zhang, D., Zhang, M., Xin, M., Wang, Z., Ding, D., Huang, F., & Wang, J. (2025). Residual attention-driven dual-domain vision transformer for mechanical fault diagnosis. Machines, 13(12), Article 1096.

Huang, F., Zhang, Q., Han, B., Wang, J., Zhang, Z., Ge, R., & Gong, H. (2025). Adaptive attenuation self-attention adversarial network for cross-domain fault diagnosis under imbalanced conditions. Measurement Science and Technology, 31 December 2025.

Ge, R., Zhang, Z., Wang, J., Wang, W., Fan, Z., & Huang, F. (2025). Multi-source domain bearing fault collaborative diagnosis method for unbalanced samples guided by multi-attention mechanism. Measurement Science and Technology, 30 November 2025.

Han, B., Huang, F., Qin, M., Qin, H., Wang, J., Zhang, Z., & Yu, Y. (2025). Dual-domain fused vision transformer for mechanical fault diagnosis under fluctuating working conditions. Measurement Science and Technology, 30 April 2025.

Yucheng Lu | Neuroscience | Research Excellence Award

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Prof. Yucheng Lu | Neuroscience | Research Excellence Award

Linyi People's Hospital | China

Prof. Yucheng Lu is a distinguished researcher whose scholarly contributions span cancer biology, immunology, and translational biomedical sciences. With 352 citations, 26 indexed publications, and an h-index of 13, he has established a strong research footprint in molecular oncology and disease pathology. Over his academic career, he has published 40 peer-reviewed papers, including 25 as first or corresponding author, reflecting consistent leadership in scientific inquiry. His work encompasses cutting-edge topics such as tumor-associated macrophage regulation in glioma, prognostic biomarkers in low-grade glioma, colorectal cancer therapeutics, and single-cell transcriptomics in esophageal cancer. In addition, he has explored metabolic and immunological disease interactions, cancer proliferation mechanisms, and neural electrophysiological responses. As a principal investigator, he has led 7 provincial and municipal research projects and contributed to 8 national and ministerial-level initiatives, demonstrating strong project management and interdisciplinary collaboration. His research excellence has earned 3 Science and Technology Achievement Awards, alongside innovations represented by 1 invention patent and 6 software copyrights. Through these achievements, Prof. Lu continues to advance biomedical research with significant scientific, clinical, and technological impact.

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Featured Publications

Shi, H., Cheng, Y., Chao, D., Song, Q., Han, L., Li, H., Lu, Y., & Wang, M. (2025). Spatiotemporal profiling of endocytic regulators in the immunosuppressive TAM microenvironment of glioma. Brain Research, 150086. (In press)

Author names not provided. (2025). Identification of CDKN3 overexpression as a marker of poor prognosis and potential therapeutic target in low-grade glioma. Scientific Reports.

Author names not provided. (2025). Okanin suppresses the growth of colorectal cancer cells by targeting Peroxiredoxin 5. Advanced Science.

Shi, K., Li, Y., Yang, L., Zhang, Z., Guo, D., Zhang, J., & Lu, Y. (2022). Profiling transcriptional heterogeneity of epithelium, fibroblasts, and immune cells in esophageal squamous cell carcinoma by single-cell RNA sequencing. The FASEB Journal, 0892-6638.

Zhao, J. Z., Lu, Y. C., Wang, Y. M., Xiao, B. L., Li, H. Y., Lee, S. C., & Wang, L. J. (2022). Association between diabetes and acute lymphocytic leukemia, acute myeloid leukemia, non-Hodgkin lymphoma, and multiple myeloma. International Journal of Diabetes in Developing Countries, 0973-3930.

Shi, K., Zhang, J. Z., Yang, L., Li, N. N., Yue, Y., Du, X. H., Zhang, X. Z., Lu, Y. C., & Guo, D. (2021). Protein deubiquitylase USP3 stabilizes Aurora A to promote proliferation and metastasis of esophageal squamous cell carcinoma. BMC Cancer, 1471-2407.

Lu, Y., Lv, B., & Song, Q. (2019). Transcranial electrical stimulation motor-evoked potentials in a spinal cord ischaemia rabbit model. Chinese Neurosurgical Journal, 2057-4967.

Lu, Y. C., Wang, P., Wang, J., Ma, R., & Lee, S. C. (2019). PCNA and JNK1-Stat3 pathways respectively promote and inhibit diabetes-associated centrosome amplification by targeting the ROCK1/14-3-3σ complex in human colon cancer HCT116 cells. Journal of Cellular Physiology.

Bo Zhang | Computer Science | Research Excellence Award

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Assoc. Prof. Dr. Bo Zhang | Computer Science | Research Excellence Award

Northwest Polytechnic University | China

Assoc. Prof. Dr. Bo Zhang is an accomplished researcher whose work spans remote sensing, geospatial intelligence, environmental monitoring, and machine learning–driven Earth observation analytics. With 252 citations,  an h-index of 7, and 5, i10-index publications, his scholarly contributions demonstrate a growing and impactful presence in environmental data science. His research advances high-resolution satellite image processing, atmospheric pollutant estimation, digital elevation model reconstruction, and intelligent geospatial mapping. He has produced notable work on transfer learning–enhanced remote sensing, sparse-sample super-resolution mapping, neural-network–based PMx estimation, land surface temperature retrieval, and ozone concentration modeling. His publications in leading journals such as IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Science Bulletin, Remote Sensing, and Indoor and Built Environment highlight his expertise in integrating artificial intelligence with satellite observations to address environmental challenges. His research also contributes to epidemiological spatial analysis and geospatial data fusion, offering multidisciplinary value in Earth system science. Through continuous work on novel algorithms and high-fidelity environmental datasets, he has strengthened the scientific foundation for climate monitoring, pollution assessment, and large-scale geospatial modeling, positioning him as a significant contributor to advanced remote sensing and environmental informatics.

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Featured Publications

Yang, C., Zhang, B., Zhang, M., Wang, Q., & Zhu, P. (2025). Research on decision-making strategies for multi-agent UAVs in island missions based on Rainbow Fusion MADDPG algorithm. Drones, 9(10), 673.

Zhang, B., Shi, Z., Hong, D., Wang, Q., Yang, J., Ren, H., & Zhang, M. (2025). Super-resolution reconstruction of the 1 arc-second Australian coastal DEM dataset. Geo-Spatial Information Science, 1–21.


Zhang, B., Xiong, W., Ma, M., Wang, M., Wang, D., Huang, X., Yu, L., Zhang, Q., & others. (2022). Super-resolution reconstruction of a 3 arc-second global DEM dataset. Science Bulletin, 67(24), 2526–2530.


Pan, D., Zhang, M., & Zhang, B. (2021). A generic FCN-based approach for road-network extraction from VHR remote sensing images using OpenStreetMap as benchmarks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.


Zhang, B., Zhang, M., Kang, J., Hong, D., Xu, J., & Zhu, X. (2019). Estimation of PMx concentrations from Landsat 8 OLI images based on a multilayer perceptron neural network. Remote Sensing, 11(6), 646.


Zhu, B., Liu, J., Fu, Y., Zhang, B., & Mao, Y. (2018). Spatio-temporal epidemiology of viral hepatitis in China (2003–2015): Implications for prevention and control policies. International Journal of Environmental Research and Public Health, 15(4), 661.

Lingmin Zhang | Pharmacology, Toxicology and Pharmaceutical Science | Research Excellence Award

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Prof. Lingmin Zhang | Pharmacology, Toxicology and Pharmaceutical Science | Research Excellence Award

Guangzhou Medical University | China

Prof. Lingmin Zhang is a leading researcher whose work integrates pharmaceutics, biomedical materials, and gene delivery, contributing significantly to advanced therapeutic strategies, particularly in lung cancer and inflammatory diseases. With 3,077 citations , 79 publications, and an h-index of 27, the researcher's scholarly impact is widely recognized. The work focuses on innovative nano-based and biomimetic delivery platforms, including nano-PROTACs, exosomes, microfluidic nanovesicles, and CRISPR/Cas9 carriers, offering transformative possibilities for targeted and precision medicine. Supported by major grants from the National Natural Science Foundation of China (projects 82572415, 82072047, 81700382), the researcher has developed cutting-edge strategies such as reprogramming tumor-associated macrophages, overcoming drug resistance in lung cancer, and reversing epigenetic silencing through nanoparticle-mediated gene delivery. Influential publications in high-impact journals—including Journal of Controlled Release, Drug Resistance Updates, ACS Nano, Angewandte Chemie, Advanced Science, and Molecular Cancer—highlight breakthroughs in nano-therapeutics, PROTAC technologies, artificial exosomes, and nucleic-acid delivery systems. Collectively, these contributions position the researcher at the forefront of translational nanomedicine, with ongoing work offering new directions for precision oncology, regenerative strategies, and next-generation drug delivery platforms.

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Featured Publication

He, M., Peng, Q., Yang, Q., Guan, X., Liu, Q., Chen, R., Zhou, D., Wang, L., Zhang, Y., Li, S., Su, J., & Zhang, L. (2026). In situ reprogramming of tumor associated macrophages with versatile nano-epigenetic inhibitor for lung cancer therapy. Journal of Controlled Release, 2026, 114497.

Zhang, L., He, L., Lin, Y., Wei, J., Tang, S., Lei, X., Lin, X., Zhou, D., Fu, L., Li, Y., He, J., Liang, L., & Yu, X. (2026). The novel strategy to overcome drug-resistant lung cancer: Dual targeting delivery of PROTAC to inhibit cancer-associated fibroblasts and lung cancer cells. Drug Resistance Updates, 84, 101316.

Chen, S., Chen, E., Su, J., Gong, Y., Tang, S., Qin, A., Shen, A., Tang, S., & Zhang, L. (2025). Magnetically navigated nano-PROTAC ameliorates acute lung injury. Journal of Nanobiotechnology, 23, 622.

Li, X., Qin, Z., Wang, S., Zhang, L., & Jiang, X. (2025). Microfluidics-assembled nanovesicles for nucleic acid delivery. Accounts of Chemical Research, 58, 570–582.

Liang, L., Peng, W., Qin, A., Zhang, J., Chen, R., Zhou, D., Zhang, X., Zhou, N., Yu, X., & Zhang, L. (2024). Intracellularly synthesized artificial exosome treats acute lung injury. ACS Nano, 18(32), 21009–21023.

Guan, X., Xu, X., Tao, Y., Deng, X., He, L., Lin, Z., Chang, J., Huang, J., Zhou, D., Yu, X., Wei, M., & Zhang, L. (2024). Dual targeting and bioresponsive nano-PROTAC induced precise and effective lung cancer therapy. Journal of Nanobiotechnology, 22, 692.

Zhang, L., Lin, Y., Li, S., Guan, X., & Jiang, X. (2023). In situ reprogramming of tumor-associated macrophages with internally and externally engineered exosomes. Angewandte Chemie International Edition, 62(11), e202217089.

Liang, L., Cen, H., Huang, J., Qin, A., Xu, W., Wang, S., Chen, Z., Tan, L., Zhang, Q., Yu, X., Yang, X., & Zhang, L. (2022). The reversion of DNA methylation-induced miRNA silence via biomimetic nanoparticles-mediated gene delivery for efficient lung adenocarcinoma therapy. Molecular Cancer, 21(1), 186.

Zhang, H., Peng, R., Chen, S., Shen, A., Zhao, L., Tang, W., Wang, X., Li, Z., Zha, Z., Yi, M., & Zhang, L. (2022). Versatile nano-PROTAC-induced epigenetic reader degradation for efficient lung cancer therapy. Advanced Science, 9(29), 2202039.

Zhang, L., Wang, L., Xie, Y., Wang, P., Deng, S., Qin, A., Zhang, J., Yu, X., Zheng, W., & Jiang, X. (2019). Triple-targeting delivery of CRISPR/Cas9 to reduce the risk of cardiovascular diseases. Angewandte Chemie International Edition, 58(36), 12404–12408.

Judith Röske | Biochemistry, Genetics and Molecular Biology | Women Research Award

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Mrs. Judith Röske | Biochemistry, Genetics and Molecular Biology | Women Research Award

University of Luebeck | Germany

Mrs. Judith Röske is a dedicated researcher with a strong focus on molecular virology, antiviral drug discovery, and protease-targeted therapeutic development, contributing to 13 scientific publications across high-impact journals. Her work explores the binding behavior of small-molecule inhibitors to viral 3C proteases, including SARS-CoV-2, EV-D68, EV-A71, and HAV, as well as host proteases such as cathepsins and calpain-1. With expertise in photometry, nanoDSF, MST, and SPR, she has optimized methods for determining key biochemical parameters such as IC₅₀, Tm, and Kᴅ, enabling the effective screening of lead compounds for broad-spectrum antivirals. Her research further investigates RNA-binding mechanisms in HAV 3C protease, shedding light on dual-targeting strategies that may advance anti-picornaviral drug development. She has contributed to influential studies on SARS-CoV-2 main protease inhibitors, including work on novel warhead chemistries, α-ketoamide derivatives, and diastereomeric optimization, reinforcing her impact in antiviral medicinal chemistry. Additionally, earlier contributions in transplant biology and liver preservation highlight her versatility in biochemical and molecular research. Through rigorous structural, kinetic, and biophysical analyses, her body of work adds valuable insight into protease inhibition and therapeutic innovation, supported by a growing citation record within the scientific community.

Profiles : Scopus | Orcid

Featured Publications

Theodoropoulou, M. A., El Kilani, H., Mantzourani, C., Jochmans, D., Neyts, J., Zhang, K., Röske, J., Kokotou, M. G., Hilgenfeld, R., & Kokotos, G. (2025). Thiazolyl 4-carboxylate ketone as a new warhead for a highly potent SARS-CoV-2 main protease inhibitor. European Journal of Medicinal Chemistry, 25(11), 118436.

Akula, R. K., El Kilani, H., Metzen, A., Röske, J., Zhang, K., Göhl, M., Arisetti, N., Marsh, G. P., Maple, H. J., Cooper, M. S., et al. (2025). Structure-based optimization of pyridone α-ketoamides as inhibitors of the SARS-CoV-2 main protease. Journal of Medicinal Chemistry, 68(1).

Cooper, M. S., Zhang, L., Ibrahim, M., Zhang, K., Sun, X., Röske, J., Göhl, M., Brönstrup, M., Cowell, J. K., Sauerhering, L., et al. (2022). Diastereomeric resolution yields highly potent inhibitor of SARS-CoV-2 main protease. Journal of Medicinal Chemistry.

Bernard, V., Gebauer, N., Dinh, T., Stegemann, J., Feller, A. C., & Merz, H. (2014). Applicability of next-generation sequencing to decalcified formalin-fixed and paraffin-embedded chronic myelomonocytic leukaemia samples. International Journal of Clinical and Experimental Pathology.

Le Minh, K., Berger, A., Eipel, C., Kuhla, A., Minor, T., Stegemann, J., & Vollmar, B. (2011). Uncoupling protein-2 deficient mice are not protected against warm ischemia/reperfusion injury of the liver. Journal of Surgical Research, 167.

Stegemann, J., Hirner, A., Rauen, U., & Minor, T. (2010). Use of a new modified HTK solution for machine preservation of marginal liver grafts. Journal of Surgical Research.

Koetting, M., Stegemann, J., & Minor, T. (2010). Dopamine as additive to cold preservation solution improves postischemic integrity of the liver. Transplant International, 23.

Minor, T., Stegemann, J., Hirner, A., & Koetting, M. (2009). Impaired autophagic clearance after cold preservation of fatty livers correlates with tissue necrosis upon reperfusion and is reversed by hypothermic reconditioning. Liver Transplantation.

Stegemann, J., & Minor, T. (2009). Energy charge restoration, mitochondrial protection and reversal of preservation-induced liver injury by hypothermic oxygenation prior to reperfusion. Cryobiology.

Stegemann, J., Hirner, A., Rauen, U., & Minor, T. (2009). Gaseous oxygen persufflation or oxygenated machine perfusion with Custodiol-N for long-term preservation of ischemic rat livers? Cryobiology.

Le Minh, K., Kuhla, A., Abshagen, K., Minor, T., Stegemann, J., Ibrahim, S., Eipel, C., & Vollmar, B. (2009). Uncoupling protein-2 deficiency provides protection in a murine model of endotoxemic acute liver failure. Critical Care Medicine.

Manekeller, S., Seinsche, A., Stegemann, J., & Hirner, A. (2008). Optimising post-conditioning time of marginal donor livers. Langenbeck's Archives of Surgery.

Manekeller, S., Schuppius, A., Stegemann, J., Hirner, A., & Minor, T. (2007). Role of perfusion medium, oxygen and rheology for endoplasmic reticulum stress-induced cell death after hypothermic machine preservation of the liver. Transplant International.

Chao Wang | Computer Science | Research Excellence Award

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Mr. Chao Wang | Computer Science | Research Excellence Award

North China University of Technology | China

Mr. Chao Wang is an accomplished researcher whose work spans vehicular networks, IoT security, blockchain mechanisms, and food engineering applications, reflecting a multidisciplinary impact. With 809 citations, an h-index of 12, and 16 i10-index publications, he has established a strong scholarly presence supported by numerous high-impact journal articles and competitive conference papers. His research contributions include advanced blockchain-based frameworks for secure communication, innovative privacy-preserving data-sharing models, anomaly detection algorithms for intelligent vehicles, and distributed system security. He has also co-authored influential studies on anti-glycation mechanisms, food bioactive compounds, and cellular protection. His publications from 2021 to 2025 demonstrate consistent output across IEEE Transactions, Future Generation Computer Systems, Food Biomacromolecules, and other reputable venues. His work on collaborative quality control, CAN bus anomaly detection, distributed GAN attack resistance, and multi-party payment channels represents notable advancements in secure systems. He has also contributed to reviews on AGEs inhibition, IoV security, NGS applicability, and blockchain-enabled vehicular applications. Beyond technical innovation, his research extends to biologically focused studies that explore glycation inhibition, fermentation mechanisms, and cellular oxidative protection. Across domains, his scholarly contributions continue to advance secure intelligent systems, data integrity solutions, and interdisciplinary applications, reinforcing his role as a productive and influential researcher.

Profiles : Orcid | Google Scholar

Featured Publications

Bao, C., Niu, Z., He, B., Li, Y., Han, S., Feng, N., Huang, H., Wang, C., Wang, J., & others. (2025). A novel high‐protein composite rice with anti‐glycation properties prepared with crushed rice flour, whey protein and lotus seed proanthocyanidins. Food Biomacromolecules, 2(1), 23–34.

He, Y., Zhou, Z., Wu, B., Xiao, K., Wang, C., & Cheng, X. (2024). Game-theoretic incentive mechanism for collaborative quality control in blockchain-enhanced carbon emissions verification. IEEE Transactions on Network Science and Engineering.

Li, Q., Xiao, K., Yi, C., Yu, F., Wang, W., Rao, J., Liu, M., Zhang, L., Mu, Y., Wang, C., & others. (2024). Inhibition and mechanism of protein nonenzymatic glycation by Lactobacillus fermentum. Foods, 13(8), 1183.

Wang, C., Xu, X., Xiao, K., He, Y., & Yang, G. (2024). Traffic anomaly detection algorithm for CAN bus using similarity analysis. High-Confidence Computing, 4(3), 100207.

Xiao, K., Li, J., He, Y., Wang, X., & Wang, C. (2024). A secure multi-party payment channel on-chain and off-chain supervisable scheme. Future Generation Computer Systems, 154, 330–343.

Feng, N., Feng, Y., Tan, J., Zhou, C., Xu, J., Chen, Y., Xiao, J., He, Y., Wang, C., & others. (2023). Inhibition of advance glycation end products formation, gastrointestinal digestion, absorption and toxicity: A comprehensive review. International Journal of Biological Macromolecules, 249, 125814.

Wu, Q., Kong, Y., Liang, Y., Niu, M., Feng, N., Zhang, C., Qi, Y., Guo, Z., Xiao, J., & others. (2023). Protective mechanism of fruit vinegar polyphenols against AGEs-induced Caco-2 cell damage. Food Chemistry: X, 19, 100736.

Wang, C., Liu, X., He, Y., Xiao, K., & Li, W. (2023). Poisoning the competition: Fake gradient attacks on distributed generative adversarial networks. In Proceedings of the IEEE International Conference on Mobile Ad Hoc and Smart Systems.

Xu, X., Wang, L., Wang, C., Zhu, H., Zhao, L., Yang, S., & Xu, C. (2023). Intelligent connected vehicle security: Threats, attacks and defenses. Journal of Information Science & Engineering, 39(6).

Wang, C., Jiang, L., He, Y., Yang, G., & Xiao, K. (2023). Age of information-based channel scheduling policy in IoT networks under dynamic channel conditions. In China Conference on Wireless Sensor Networks (pp. 88–98).

Zhou, J., Wang, C., Luo, M., Liu, X., Xu, X., & Chen, S. (2023). Spatial-temporal based multi-head self-attention for in-vehicle network intrusion detection system. SSRN 4581213.

Wang, C., Wang, S., Cheng, X., He, Y., Xiao, K., & Fan, S. (2022). A privacy and efficiency-oriented data sharing mechanism for IoTs. IEEE Transactions on Big Data, 9(1), 174–185.

Li, Q., Li, L., Zhu, H., Yang, F., Xiao, K., Zhang, L., Zhang, M., Peng, Y., Wang, C., & others. (2022). Lactobacillus fermentum as a new inhibitor to control advanced glycation end-product formation during vinegar fermentation. Food Science and Human Wellness, 11(5), 1409–1418.

Wu, Q., Liang, Y., Kong, Y., Zhang, F., Feng, Y., Ouyang, Y., Wang, C., Guo, Z., & others. (2022). Role of glycated proteins in vivo: Enzymatic glycated proteins and non-enzymatic glycated proteins. Food Research International, 155, 111099.

Wang, C., Cheng, X., Li, J., He, Y., & Xiao, K. (2021). A survey: Applications of blockchain in the Internet of Vehicles. EURASIP Journal on Wireless Communications and Networking, 2021(1), 77.

Xu, S., Chen, X., Wang, C., He, Y., Xiao, K., & Cao, Y. (2021). A lattice-based ring signature scheme to secure automated valet parking. In Wireless Algorithms, Systems, and Applications.

Leema Nelson | Computer Science | Research Excellence Award

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Dr. Leema Nelson | Computer Science | Research Excellence Award

Chitkara University | India 

Dr. Leema Nelson is an accomplished researcher whose scholarly contributions span machine learning, clinical decision support systems, composite materials, signal processing, and intelligent diagnostic frameworks. With a total of 1206 citations, an h-index of 17, and 29 i10-index publications, her research demonstrates both depth and sustained impact across interdisciplinary domains. She has produced numerous high-quality peer-reviewed articles, many in leading Elsevier journals such as Applied Soft Computing and Materials & Design, focusing on neural network optimization, characterization of metal-matrix composites, wear modelling, and advanced computational methods. Her work in clinical data classification, including diabetes and PCOS diagnosis, highlights the integration of artificial intelligence into healthcare decision-making. In recent years, she expanded her research into video smoke detection, cyber-security–based email filtering, audio source separation, and welding parameter optimization using intelligent algorithms. Her studies in deepfake detection, text recognition, and clinical support systems reflect her continuing advancements in data-driven AI models. She has also contributed extensively to IEEE conferences, presenting innovations in masked face detection, ultrasound image analysis, mobile app frameworks, and disease prediction models. Overall, her scientific output reflects strong productivity, interdisciplinary expertise, and meaningful contributions to both computational intelligence and applied engineering research.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Jibinsingh, B. R., & Nelson, L. (2025). FL-WOSP: Federated learning with Walrus Optimization for sepsis prediction using MIMIC-III physiological and clinical data. Pattern Recognition. Advance online publication.

Batra, H., & Nelson, L. (2024). ESD: E-mail spam detection using cybersecurity-driven header analysis and machine learning-based content analysis. International Journal of Performability Engineering, 20(4).

Nelson, L. (2024). Data-driven clinical decision support system using neural network topology optimization for PCOS diagnosis. Journal of Soft Computing and Data Mining.

Batra, H., & Nelson, L. (2024). A three-stage deepfake detection framework using deep learning models with multimedia data. International Journal of Intelligent Systems and Applications.

Shanmuga Priya, M., Pavithra, A., & Leema, N. (2024). Character/word modelling: A two-step framework for text recognition in natural scene images. Computer Science.

Batra, H., & Nelson, L. (2023). DCADS: Data-driven computer aided diagnostic system using machine learning techniques for polycystic ovary syndrome. International Journal of Performability Engineering, 19(3).

Kumar, V. A., Rao, C. V. R., & Leema, N. (2023). Audio source separation by estimating the mixing matrix in underdetermined condition using successive projection and volume minimization. International Journal of Information Technology, 15(4), 1831–1844.

Ramesh, A., Sivapragash, M., Ajith Kumar, K. K., & Leema, N. (2023). Investigating the quality of TIG-welded aluminium alloy 5086 using the online acoustic emission and optimization of welding parameters using global best-based modified artificial bee colony algorithm. Transactions of the Indian Institute of Metals, 1–14.

Pranshu Kumar Soni, & Leema, N. (2023). PCP: Profit-driven churn prediction using machine learning techniques in banking sector. International Journal of Performability Engineering, 19(5), 303–311.

Vettum Perumal, S., Suyamburajan, V., Chidambaranathan, V. S., & Nelson, L. (2023). Characterization of microstructure and mechanical behaviour in activated tungsten inert gas welded dissimilar AA joint of AA 5083 and AA 6061 alloys. Journal of the Institution of Engineers (India): Series D, 1–9.