Lianhui Liang | Deep learning or Image processing | Excellence in Research Award

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Dr. Lianhui Liang | Deep learning or Image processing | Excellence in Research Award

Guangxi University | China 

Lianhui Liang is an academic researcher in electrical and information engineering with a strong focus on intelligent remote sensing analysis and advanced signal interpretation. His work centers on hyperspectral, multispectral, and LiDAR data understanding, Deep learning or Image processing  with applications spanning environmental monitoring, land surface analysis, and complex scene interpretation. His research integrates signal processing, pattern recognition, and deep learning techniques to enhance feature extraction, classification accuracy, and information fusion in high-dimensional remote sensing imagery. He has contributed significantly to spectral intelligence, including algorithm development for image inversion, target detection, and data fusion across heterogeneous sensors. His interdisciplinary approach bridges theoretical modeling with practical engineering applications, particularly in optical and microwave remote sensing. Through sustained collaboration with international research groups, his work reflects a global perspective on emerging challenges in remote sensing and artificial intelligence. He has actively engaged in advanced training programs related to remote sensing data processing, deep learning frameworks, and intelligent interpretation systems, strengthening the transfer of cutting-edge methods into applied research. His scholarly contributions include peer-reviewed publications, intellectual property development, and participation in research and development projects supported by public and industrial partners. Overall, his research advances intelligent remote sensing systems and contributes to the broader fields of geospatial analytics and artificial intelligence-driven Earth observation.

Citation Metrics (Google Scholar)

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Citations
271

Documents
7

h-index
7

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View Google Scholar Profile

Featured Publications


Prototype Similarity-Constraint Enhancement Network: A Few-Shot Class-Incremental Learning for Hyperspectral Image Classification

– Expert Systems with Applications, 2025
L. Yang, Y. Tan, L. Liang, H. Xu, T. Wu, Z. Huang, X. Li, Y. Tang

Cross-Stage Attention Edge Enhancement and Fourier-Wavelet Transformer Integrated Network for Hyperspectral Image Classification

– IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025
L. Liang, S. Yuan, Y. Zeng, Y. Lin, Y. Zhang, P. Xie, T. X. Wu

LHCF: Liquid Neural Network with Hierarchical Collaborative Fusion for Hyperspectral Image Classification

– Authorea Preprints, 2025
L. Liang, J. Zhang, S. Zhang, B. Tu, L. Yang, J. Li, A. Plaza

LKMA: Learnable Kernel and Mamba with Spatial-Spectral Attention Fusion for Hyperspectral Image Classification

– IEEE Transactions on Geoscience and Remote Sensing, 2025
L. Liang, J. Zhang, P. Duan, X. Kang, T. X. Wu, J. Li, A. Plaza

Cross-Domain Few-Shot Hyperspectral Image Classification with Local Entropy Adaptation Metric

– Authorea Preprints, 2025
Y. Zhang, Z. Liu, P. Duan, L. Lian

Jian Xia | Artificial Intelligence in Statistics | Research Excellence Award

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Dr. Jian Xia | Artificial Intelligence in Statistics | Research Excellence Award

Hubei University of Automotive Industry | China

Dr. Jian Xia is a dedicated materials scientist specializing in next-generation electronic and photonic devices, with a strong academic foundation and a growing record of impactful research. He obtained his Ph.D. degree from the School of Materials Science and Engineering at Huazhong University of Science and Technology, where he developed expertise in resistive switching devices, phase-change materials, and advanced optical memory technologies. After completing his doctoral studies, he joined the Hubei University of Automotive Technology as a lecturer, contributing actively to both teaching and research in the field of electronic materials and integrated circuit design. Dr. Xia’s research interests encompass memristors, phase-change memory, and photonic neuromorphic devices, all of which hold promising applications in high-performance computing, data storage, and artificial intelligence hardware. He has undertaken notable research projects, including the Open Fund of the Hubei Key Laboratory of Energy Storage and Power Battery and the Doctoral Scientific Research Foundation of Hubei University of Automotive Technology. With a citation index of 361 and a research portfolio of 20 SCI-indexed publications, Dr. Xia has contributed articles to leading international journals such as Nature Communications, Laser & Photonics Reviews, ACS Photonics, Applied Physics Letters, IEEE Electron Device Letters, and Science China Materials. His innovative contributions are further demonstrated by nine patents that are either published or under review, highlighting his commitment to advancing practical and technologically significant developments in electronic device engineering. Although he has yet to hold editorial appointments or professional memberships, his scholarly influence continues to grow through strong research visibility and future collaboration potential. Dr. Xia maintains an active academic presence on platforms such as ResearchGate and continues to advance pioneering research aimed at developing energy-efficient, high-density, and neuromorphic computing devices to meet the evolving demands of modern information technology.

Citation Metrics (Scopus)

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Citations
361

Documents
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5

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Featured Publication

 

Dujiang Yang | Clinical Trials and Statistical Designs | Research Excellence Award

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Mr. Dujiang Yang | Clinical Trials and Statistical Designs | Research Excellence Award

The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University | China

Mr. Dujiang Yang is an emerging clinician-scientist in Traditional Chinese Medicine Orthopedics & Traumatology at Southwest Medical University, whose rapid academic growth and extensive publication record have positioned him among the most productive young researchers in his field, he completed advanced training at the Affiliated Hospital of Traditional Chinese Medicine, where he served as a spine-track resident physician and postgraduate researcher under Professor Guoyou Wang, contributing deeply to multiple national and provincial scientific projects. As first author, Yang has published 37 SCI-indexed papers, including numerous Q1 journals such as Annals of the Rheumatic Diseases, Journal of Extracellular Vesicles, Advanced Science, Chemical Engineering Journal, Leukemia, and Angiogenesis, covering topics spanning musculoskeletal regeneration, tumor microenvironment immunology, ferroptosis in osteoarthritis, disc repair biology, metabolic bone disease, and translational nanotechnology. His overall research impact is reflected in an estimated h-index of 2, 42 documents, and over 7 citations, demonstrating strong recognition across basic and translational medicine communities. Beyond research, he has gained substantial clinical proficiency, mastering lumbar fusion procedures, spinal fixation, PVP/PKP, trauma management, and more than 200 independent suturing cases. Yang has earned major distinctions including multiple first-class scholarships, Outstanding Graduate awards at both undergraduate and postgraduate levels, Excellent Youth Researcher recognitions. His technical skillset includes Western blotting, RT-PCR, flow cytometry, cell culture, molecular assays, animal experiments, advanced literature analysis, and scientific writing using GraphPad Prism and ImageJ. Combining rigorous clinical training, high-level publication output, and cross-disciplinary research capability, DuJiang Yang represents a driven, evidence-focused young scholar with strong potential for future leadership in musculoskeletal medicine and regenerative therapeutics.

Profile: Scopus 

Featured Publications

Yang, D., Yang, L., Yang, J., & Wang, G. (2025). Dual-targeting biomimetic nanoplatforms for tumor microenvironment-immune remodeling. Chemical Engineering Journal, 526, 171226.

Yang, D., Yang, J., Xu, H., & Wang, G. (2025). Minimal dose, maximal scrutiny: A critical appraisal of the feasibility and functional implications of a reduced-volume Nordic hamstring exercise protocol. Scandinavian Journal of Medicine & Science in Sports, 35(12)

Yang, D., & Wang, G. (2025). Beyond quantity: The nonlinear association between HDL cholesterol and coronary atherosclerosis. Atherosclerosis, 411, 120561.

Yang, D., & Wang, G. (2025). MSC-delivered CXCL10 for solid tumors: Navigating the translational hurdles from precept to clinic. Biomedicine & Pharmacotherapy, 193, 118735.

Vikas Mehta | Statistical Computing and Programming | Research Excellence Award

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Dr. Vikas Mehta | Statistical Computing and Programming | Research Excellence Award

Korean National Institute for International Education | South Korea

Dr. Vikas Mehta is a structural engineer and researcher specializing in seismic performance optimization, sustainable construction materials, and the application of advanced computational and machine learning methodologies to civil infrastructure systems. He completed his Ph.D. in Civil Engineering at Keimyung University, South Korea, where his award-winning doctoral research introduced innovative modifier-based and data-driven techniques for improving shear strength prediction and design accuracy in reinforced concrete beam-column joints. His expertise spans nonlinear finite element modeling, fragility analysis, physics-informed and graph-based machine learning, geospatial analytics, and performance-based seismic assessment, supported by strong proficiency in ETABS, OpenSees, SeismoSoft, Abaqus, MATLAB, Q-GIS, SPSS, Python, PyTorch, WEKA, and OriginPro. Dr. Mehta serves as a Postdoctoral Researcher at the Chonnam National University R&BD Foundation, contributing to advanced safety technologies for nuclear power plant structures under extreme hazard scenarios, including buckling resistance enhancement, retrofit optimization, and complex wind–terrain interaction studies. His professional background includes academic appointments in structural and construction engineering, where he taught subjects in earthquake engineering, finite element analysis, and structural systems while supervising graduate research and contributing to curriculum and laboratory development. Dr. Mehta has authored a substantial body of SCI-indexed research on seismic damage prediction, torsional behavior modeling, hybrid AI-mechanics frameworks, recycled and sustainable materials, computational methods, and structural performance evaluation, complemented by multiple patents in construction materials, damping devices, and waste-based composites. He has presented at leading international and national conferences and contributed to funded collaborative research, including projects involving global academic and industry partners. His professional affiliations include membership in ASCE, the Institute of Physics (AMInstP), IAEME (Fellow), and licensure as a Class-A engineer under the Himachal Pradesh Town and Country Planning Act. Dr. Mehta’s contributions to structural engineering and computational mechanics continue to gain international visibility, reflected in an h-index of 7, over 172 citations, and more than 19 published documents, underscoring his growing influence in machine learning–driven structural design, seismic resilience, and sustainable construction innovation.

Profiles: Scopus | Orcid

Featured Publications

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Corrigendum to “Adaptive simulation and data-driven hybrid modeling for predicting shear strength and failure modes of interior reinforced concrete beam-column joints”.

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Predictive framework for shear strength and failure modes of exterior reinforced concrete beam–column joints using machine learning. Structural Concrete. h.

Sagar, G. S., Mukthi, S., & Mehta, V. (2025). Analyzing compressive, flexural, and tensile strength of concrete incorporating used foundry sand: Experimental and machine learning insights. Archives of Computational Methods in Engineering.

Mehta, V., Thakur, M. S., & Chey, M. H. (2025). Enhancing seismic design accuracy of RC beam-column joints: Modifier-based approach for shear strength predictions. Structures.

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Adaptive simulation and data-driven hybrid modeling for predicting shear strength and failure modes of interior reinforced concrete beam-column joints. Structures.

Xu Ge | Statistical Applications in Engineering | Industrial Statistics Award

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Mr. Xu Ge | Statistical Applications in Engineering | Industrial Statistics Award

Shanghai Jiao Tong University | China

Mr. Xu Ge is a promising researcher specializing in control science, soft sensing, and intelligent systems, currently pursuing his Ph.D. at the UM-SJTU Joint Institute, Shanghai Jiao Tong University. He earned his Bachelor’s degree in Automation from the School of Mechanical Engineering and Automation at Harbin Institute of Technology (Shenzhen), where he consistently demonstrated academic excellence and technical innovation. Throughout his academic journey, Xu Ge has been recognized with numerous honors, including the prestigious National Scholarship, Topband Enterprise Scholarship, and First-Class Academic Scholarship. His university distinctions-Outstanding Student, Outstanding CYL Member, Outstanding Graduate, and Outstanding Thesis-further highlight his commitment to excellence. Xu has achieved remarkable success in national competitions, winning the ROBOCOM National First Prize, ROBOCON National Third Prize, the National Undergraduate Smart Car Competition (Outdoor Track) National Third Prize, and the National Undergraduate Mathematics Competition Provincial First Prize. His research experience reflects a strong interdisciplinary background bridging control engineering, machine learning, and system modeling. Notably, in the NSFC project “Online Estimation of Loads and Fatigue Life Prediction of Key Chassis Components under Random Driving Conditions,” he designed a soft-sensing framework that enables high-accuracy signal estimation through data-driven models and developed an embedded system for real-world vehicle testing. His collaboration with BYD on the “New Energy Vehicles Technology Program” showcased his expertise in robotics and deep learning, where he constructed datasets from BYD blade-battery modules and integrated neural networks with classical algorithms for precise robotic welding detection and operation. Xu Ge has contributed several impactful publications, including works in Mechanical Systems and Signal Processing and IEEE Transactions on Vehicular Technology, and papers accepted for presentation at IECON 2025. His accepted and submitted research covers a wide range of topics, such as vehicle sensor optimization, kernelized modeling for wheel load estimation, and battery electrochemical parameter identification through hybrid optimization methods. With his strong foundation in algorithm design, system integration, and data-driven control, Xu Ge continues to push the frontiers of intelligent mechanical systems and vehicular sensing technologies, aspiring to develop innovative, high-performance solutions that bridge theoretical advancements with industrial applications.

Profile: Google Scholar

Featured Publications

Ge, X., Li, M., Zhou, J., Qiu, Y., & Zhang, M. (2026). MMSE noncausal FIR based wheel force soft-sensing under Bernoulli-uniform prior. Mechanical Systems and Signal Processing, 242, 113601.

Ge, X., Zhang, M., Zhou, J., Chen, W., Li, X., & Li, M. (2025). Vehicle sensor configuration optimization for tire force estimation based on Min-Max SDP. In IECON 2025 – 51st Annual Conference of the IEEE Industrial Electronics Society.

Michael Pitton | Descriptive and Inferential Statistics | Best Researcher Award

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Prof. Dr. Michael Pitton | Descriptive and Inferential Statistics | Best Researcher Award

Medical University of Mainz | Germany

Professor Dr. Michael Pitton is a distinguished German physician-scientist and expert in diagnostic and interventional radiology. A graduate of the Johannes Gutenberg University Mainz, he completed his medical studies and advanced clinical training in internal medicine, cardiology, radiology, and neuroradiology at leading German university hospitals, including the University Medical Center Mainz and the Deutsches Herzzentrum Berlin. His academic achievements include a habilitation on functional and morphological aspects of endovascular aneurysm therapy, followed by his appointment as university lecturer and senior consultant in interventional radiology. Professor Pitton has held successive leadership positions and currently serves as the Acting Director of the Department of Diagnostic and Interventional Radiology and Head of the Section of Interventional Radiology at the University Medical Center Mainz. He also holds European Board Certification in Interventional Radiology (EBIR) and the European Certification for Endovascular Specialists (CIRSE) and is a certified DEGIR instructor across all modules. Combining clinical excellence with managerial insight, he earned a Master of Health Business Administration, reflecting his engagement in healthcare management and innovation. Professor Pitton has an extensive scientific record, with approximately 127 publications, an h-index of around 33, and more than 6,771 citations, underscoring his influence in vascular and interventional radiology. His research contributions have advanced the understanding and treatment of aneurysms, transjugular intrahepatic portosystemic shunt (TIPS) interventions, and image-guided oncologic therapies. Recognized with numerous national and international awards, his work bridges academic medicine, translational research, and health leadership. Professor Pitton exemplifies excellence in clinical radiology, academic scholarship, and interdisciplinary collaboration, contributing significantly to the development of interventional radiology in Europe.

Profiles: Scopus | Orcid

Featured Publications

Graafen, D., Bart, W., Halfmann, M. C., Müller, L., Hobohm, L., Yang, Y., Neufang, A., Espinola-Klein, C., Pitton, M. B., Kloeckner, R., Varga-Szemes, A., & Emrich, T. (2022). In vitro and in vivo optimized reconstruction for low-keV virtual monoenergetic photon-counting detector CT angiography of lower legs.

Gairing, S. J., Kuchen, R., Müller, L., Cankaya, A., Weerts, J., Kapucu, A., Sachse, S., Zimpel, C., Stoehr, F., Pitton, M. B., Mittler, J., Straub, B. K., Marquardt, J. U., Schattenberg, J. M., Labenz, C., Kloeckner, R., Weinmann, A., Galle, P. R., Wörns, M. A., & Foerster, F. (2022.). 13C-Methacetin breath test predicts survival in patients with hepatocellular carcinoma undergoing transarterial chemoembolization.

Müller, L., Hahn, F., Mähringer-Kunz, A., Stoehr, F., Gairing, S. J., Foerster, F., Weinmann, A., Galle, P. R., Mittler, J., Pinto Dos Santos, D., Pitton, M. B., Düber, C., Fehrenbach, U., Auer, T. A., Gebauer, B., & Kloeckner, R. (2022). Prevalence and clinical significance of clinically evident portal hypertension in patients with hepatocellular carcinoma undergoing transarterial chemoembolization.

Moumita Mukherjee | Machine Learning and Statistics | Best Researcher Award

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Dr. Moumita Mukherjee | Machine Learning and Statistics | Best Researcher Award

Charite-University Medicine Berlin | Germany

Dr. Moumita Mukherjee is an accomplished health economist and digital health researcher with expertise in health systems research, machine learning applications in healthcare, and interdisciplinary teaching. She holds a PhD in Economics from the University of Calcutta, an MBA in Entrepreneurship, Innovation and Project Development from International Telematic University, and an MSc in Data Science from the University of Europe for Applied Sciences, Germany. Her professional experience spans both academic and applied research environments, including positions at Charite-University Medicine Berlin, the Indian Institute of Public Health in Shillong, and the Berlin School of Business and Innovation. She has contributed extensively to global health research focusing on digital transformation, equity in healthcare access, and the use of data-driven methods for improving health outcomes. Her body of work includes numerous peer-reviewed publications in leading journals such as Scientific Reports, Journal of Health, Population and Nutrition, Journal of Health Management, and International Journal for Equity in Health, as well as book chapters and authored volumes addressing child health, nutrition, and health equity. In her current role at Charite-University Medicine Berlin, she lectures on digital health and artificial intelligence, supervises master’s theses, and mentors students. With advanced technical proficiency in Python, STATA, and NVivo, she applies econometric, machine learning, and deep learning models to address complex public health and policy questions. Her interdisciplinary approach integrates health economics, digital innovation, and policy analysis to support equitable and sustainable health systems worldwide. Through her research, teaching, and mentorship, Dr. Moumita Mukherjee continues to bridge data science and health economics to shape the future of evidence-based global health policy and digital healthcare transformation.

Profiles: Google Scholar | Orcid

Featured Publications

Kiran Sree Pokkuluri | Machine Learning and Statistics | Excellence in Research Award

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Prof. Dr. Kiran Sree Pokkuluri | Machine Learning and Statistics | Excellence in Research Award

Shri Vishnu Engineering College For Women | India

Prof. Dr. Kiran Sree Pokkuluri is a distinguished academician, researcher, and innovator in the field of Artificial Intelligence and Machine Learning with an illustrious career of academic and research excellence. Currently serving as Professor and Head of the Department of Computer Science and Engineering at Shri Vishnu Engineering College for Women, he has significantly contributed to advancing computational intelligence and data-driven innovation in academia and industry. He holds a Ph.D. in Artificial Intelligence from JNTU-Hyderabad and has an impressive scholarly record with over 100 research publications in reputed SCI and Scopus-indexed journals, a citation count exceeding 653, an h-index above 13, and an Documents exceeding 152, reflecting the global impact of his research. His research areas include Deep Learning, Healthcare Analytics, Bioinformatics, IoT Power Optimization, Big Data Analytics, and Cloud Computing. Dr. Sree has authored six textbooks with ISBNs on Artificial Intelligence, Machine Learning, and Deep Learning, and has filed and published six patents in the domains of AI and intelligent systems. His innovations such as the Hybrid Deep Neural ZF Network (HDNZF-Net) have set new benchmarks in real-time speech enhancement for speech-impaired individuals and IoT optimization. He has completed five major funded projects and collaborated with premier institutions including Stanford University through the UIF program, fostering cross-disciplinary innovation. A recognized thought leader, Dr. Sree serves as Editor-in-Chief, editorial board member, and reviewer for multiple international journals. His remarkable achievements have earned him prestigious recognitions like the Bharat Excellence Award and Rashtriya Ratan Award, and he has been featured in Marquis Who’s Who in the World. As Global Vice President of the World Statistical Data Analysis Research Association (WSA) and a member of professional bodies such as IEEE, ISTE, CSI, and IAENG, Dr. Kiran Sree continues to inspire excellence in AI-driven research, education, and technological innovation.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Venkatachalam, B., Pokkuluri, K. S., Suguna Kumar, S., Dhandapani, A., & Bhonsle, M. (2025). Adaptive fuzzy heuristic algorithm for dynamic data mining in IoT integrated big data environments. Journal of Fuzzy Extension and Applications, 6(3), 615–636.

Pokkuluri, K. S., Sarkar, P., Birchha, V., Mathariya, S. K., Veeramachaneni, V., & others. (2025). Intelligent reasonable optimization for virtual machine provisioning in hybrid cloud using fuzzy AHP and cost-effective autoscaling. SN Computer Science, 6(7), 1–15.

Sivanuja, M., Raju, P. J. R. S., Prasad, M., RR, P. B. V., Kumar, K. S., & Pokkuluri, K. S,. (2025). A novel ensemble-based deep learning framework combining CNN and transfer learning models for enhanced wildfire detection. In Proceedings of the 2025 International Conference on Computational Robotics, Testing and Applications.

Alzubi, J. A., Pokkuluri, K. S., Arunachalam, R., Shukla, S. K., Venugopal, S., & others. (2025). A generative adversarial network-based accurate masked face recognition model using dual scale adaptive efficient attention network. Scientific Reports, 15(1), 17594.

Pokkuluri, K. S., Chandanan, A. K., Mishra, A. K., Jyothi, D., Lavanya, M. S. S. L., & others. (2025). Deep learning-enhanced intrusion detection and privacy preservation for IIoT networks. In Proceedings of the 2025 4th International Conference on Distributed Computing and Electrical Systems.

Om Sambhaji Shelke | Operations Research and Statistical Optimization | Excellence in Research Award

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Dr. Om Sambhaji Shelke | Operations Research and Statistical Optimization | Excellence in Research Award

Sinomune Pharmaceutical Co. Ltd | China

Dr. Om Sambhaji Shelke is a highly accomplished pharmaceutical scientist with extensive expertise in the formulation and development of topical, semisolid, solid, and liquid drug products. Holding a Ph.D. in Pharmacy and an M. Pharmacy from Savitribai Phule Pune University, he has over a decade of experience across global markets including the US, EU, China, Hong Kong, and India. Currently serving as Chief Scientist at Sinomune Pharmaceutical Co. Ltd. in Wuxi, Jiangsu, China, Dr. Shelke leads the development of generic topical products for the NMPA market. He is skilled in Quality by Design (QbD)-based development of creams, ointments, gels, shampoos, and solutions, with specialization in novel formats such as emulgel, organogel, nanogel, solid lipid nanoparticles, suspensions, and toothpaste. He also holds three granted patents and has published multiple scientific and technical articles. Throughout his career, he has received multiple awards recognizing his innovation, knowledge sharing, and leadership, including the StarFire Award. Dr. Shelke has held pivotal roles at leading pharmaceutical and consumer healthcare companies such as Prinbury Biopharm Co. Ltd., Encube Ethicals Pvt Ltd., Bright Future Pharmaceuticals Ltd., Unilever Industries Pvt Ltd., Abbott Healthcare Pvt Ltd., Dr. Reddy’s Laboratories, and Glenmark Pharmaceuticals Ltd., contributing to both regulatory-compliant NDA, ANDA, and 505(b)(2) products as well as OTC, cosmetic, and personal care formulations. His professional journey reflects a consistent commitment to scientific excellence, innovative product development, and leadership in cross-functional teams, positioning him as a prominent figure in global pharmaceutical research and development.

Profiles: Google Scholar | Orcid

Featured Publications

F. Jie, O. Shelke, Z. Yijie, C. Yulan, & L. Yongbo. (2025). Q1 and Q2 selection, Q3, IVRT, IVPT, pharmacokinetic and pharmacodynamic evaluation of topical generic product. Drug Development and Industrial Pharmacy, 51(6), 555–565.

J. Feng, O. S. Shelke, Y. Chen, Z. Zhang, X. Tang, & Y. Zhu. (2025). IVRT and IVPT of desonide lotion and cream: Correlation with human bioequivalence study. Journal of Pharmaceutical Innovation, 20(5), 196.

S. Krishna Phani Chandra, S. Om Sambhaji, & N. Shorgar. (2025). Quantification of leniolisib in rat plasma using LC-MS/MS: Method development, validation, and pharmacokinetic study. African Journal of Biological Sciences, 7(7), 121–142.

S. Om. (2025). Editorial article: The transformative impact of AI in pharmaceutical drug product development. Insights of Pharmatech, 1(2), 1.

S. Gadge, O. S. Shelke, R. Pingale, P. Palande, S. Tandale, P. Sonawane, … (2025). Development and evaluation of a polyherbal neem-based emulgel enriched with herbal oils for enhanced topical delivery and antibacterial efficacy. Journal of Chemical Health Risks, 15(3), 2189–2209.

Guo Tian | Machine Learning and Statistics | Best Researcher Award

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Assoc Prof. Dr. Guo Tian | Machine Learning and Statistics | Best Researcher Award

Tsinghua University | China

Assoc Prof. Dr. Guo Tian is an accomplished young chemical engineer whose research lies at the frontier of sustainable catalysis and CO₂/CO conversion. He earned his Bachelor’s degree in Chemical Engineering under Prof. Xuezhi Duan at the East China University of Science and Technology and pursued his doctoral studies in Chemical Engineering at Tsinghua University under the guidance of Prof. Fei Wei. Following his doctoral training, he joined Southwest Jiaotong University as an Associate Professor and Principal Investigator. At only twenty-five years of age, Guo has led pioneering work on high-pressure thermo-catalytic systems, including the design of a reactor capable of stable operation at up to 60 bar integrated with surface-enhanced infrared absorption spectroscopy (SEIRAS) for in-situ monitoring of reaction intermediates. His studies have revealed critical mechanistic pathways in CO/CO₂ conversion using bifunctional catalysts, identifying oxygenate intermediates as key to improving the traditional methanol-to-hydrocarbons (MTH) mechanism. Drawing inspiration from biological systems, he has advanced the concept of bio-inspired multifunctional catalysts and introduced the innovative idea of “catalytic shunt” strategies to enhance selectivity and efficiency. Combining experimental research with density-functional theory (DFT) and micromodel simulations, his work bridges molecular-level understanding with reactor-scale engineering. Dr. Tian has authored numerous influential publications in high-impact journals such as Nature Sustainability, Nature Communications, ACS Catalysis, and the Journal of the American Chemical Society. Notable among these are “Efficient syngas conversion via catalytic shunt” (Nature Sustainability), and “Upgrading CO₂ to sustainable aromatics via perovskite-mediated tandem catalysis” (Nature Communications). According to his Scopus profile, he has authored 14 documents, accumulated around 297 citations, and holds an h-index of 9, reflecting a strong and growing impact in the field. His expertise includes thermochemical measurement and data analysis, catalytic materials design, reactor and reaction-system development, in-situ spectroscopy (SEM, XRD, XPS, XAS), and DFT-based theoretical modeling. Integrating theory, advanced characterization, and engineering innovation, Guo Tian’s vision focuses on transforming CO₂ and CO into high-value sustainable fuels such as aviation fuel components, contributing to global carbon-neutral energy goals. Through his scientific rigor, leadership, and creativity, he has rapidly emerged as a rising star in heterogeneous catalysis and sustainable chemical engineering.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

M. Zhao, Q. Wu, X. Chen, H. Xiong, G. Tian, L. Yan, F. Xiao, & F. Wei. (2025). Entropy-governed zeolite intergrowth. Journal of the American Chemical Society.

Z. Wang, X. Liu, G. Tian, Z. Wang, L. Li, F. Lu, Y. Yu, Z. Li, F. Wei, & C. Zhang. (2025). Research advances in coal-based syngas to aromatics technology. Clean Energy, 9(5), 136–152.

J. He, G. Tian, D. Liao, Z. Li, Y. Cui, F. Wei, C. Zeng, & C. Zhang. (2025). Mechanistic insights into methanol conversion and methanol-mediated tandem catalysis toward hydrocarbons. Journal of Energy Chemistry.

H. Xiong, Y. C. Wang, X. Liang, M. Zhao, G. Tian, G. Wang, L. Gu, & X. Chen. (2025). In situ quantitative imaging of nonuniformly distributed molecules in zeolites. Journal of the American Chemical Society, 147(32), 28965–28972.

Z. Li, J. Chen, G. Xu, Z. Tang, X. Liang, G. Tian, F. Lu, Y. Yu, Y. Wen, & J. Yang. (2025). Constructing three-dimensional covalent organic framework with aea topology and flattened spherical cages. Chemistry of Materials, 37(5), 1942–1948.