Sergey Pulinets | Scientific Breakthroughs | Best Researcher Award

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Prof. Sergey Pulinets | Scientific Breakthroughs | Best Researcher Award

Prof. Sergey Pulinets | Space Research Institute of the Russian Academy of Sciences (RAS) | Russia

Prof. Sergey A. Pulinets is a leading geophysicist and space plasma physicist  in the fields of space plasma physics, ionospheric physics, and geophysics. A graduate of the Faculty of Physics at Lomonosov Moscow State University , he has held major scientific and administrative positions at IZMIRAN, the National Autonomous University of Mexico (UNAM), and the Institute of Applied Geophysics, before joining the Space Research Institute (IKI RAS) in 2009 as Chief Research Scientist. Prof. Pulinets is internationally recognized for his pioneering studies on ionization processes and their effects on the atmosphere, leading to the development of a comprehensive Lithosphere–Atmosphere–Ionosphere coupling model, widely used today for short-term earthquake precursor monitoring. He has led and participated in numerous space experiments aboard Soviet and Russian satellites and currently serves as the chief designer of the LAERT ionosonde-radar, part of the “Ionosonde-2025” satellite constellation under the Russian Federal Space Program. He has authored over 192 scientific publications, which have garnered 6,824 citations across 2,736 documents, with an h-index of 38 (Scopus). His work integrates multidisciplinary approaches to earthquake forecasting, as reflected in his monographs with Springer, AGU/Wiley, and IOP Publishing. Prof. Pulinets is a member of COSPAR, URSI, EMSEV, and the International Academy of Astronautics (IAA) and serves as an editor for MDPI Atmosphere and the RAS journal Geomagnetism and Aeronomy. He has reviewed for more than 30 international journals including JGR, Radio Science, and Natural Hazards. His scientific achievements have been recognized with VDNKh Bronze and Silver Medals, the Korolev Medal, and numerous honors from the Russian Federation of Cosmonautics. Holding 10 patents and one scientific discovery, Prof. Pulinets stands among the top 25 most-cited Russian scientists in geophysics.

Profiles: Scopus | Google Scholar | Orcid | Research Gate

Featured Publications 

Ouzounov, D., Inan, S., Kalenda, P., Neumann, L., Pulinets, S., Liu, J.-Y., Shen, X., Yan, R., Rušajová, J., Kafatos, M. C., et al. (2025, January 20). Multi-parameter study of the pre-earthquake phase associated with the Kahramanmaraş sequence in Türkiye on February 6th, 2023. EGUsphere Preprint. https://doi.org/10.5194/egusphere-egu24-6407

Smirnov, S., Pulinets, S., & Bychkov, V. (2024, December 9). Some effects of the Shiveluch Volcano eruption of 10 April 2023 on atmospheric electricity and the ionosphere. Atmosphere, 15(12), 1467. https://doi.org/10.3390/atmos15121467

Pulinets, S., & Velasco Herrera, V. M. (2024, August 5). Earthquake precursors: The physics, identification, and application. Geosciences, 14(8), 209. https://doi.org/10.3390/geosciences14080209

Pulinets, S., Mironova, I., Miklyaev, P., Petrova, T., Shitov, A., & Karagodin, A. (2024, January 27). Radon variability as a result of interaction with the environment. Atmosphere, 15(2), 167. https://doi.org/10.3390/atmos15020167

Pulinets, S. A. (2024, January 22). Physical bases of the short-term forecast of earthquakes. Astronomical and Astrophysical Transactions, 1476-3540. https://doi.org/10.17184/eac.8366

Liu, J.-Y. T., Shen, X., Chang, F.-Y., Chen, Y.-I., Sun, Y.-Y., Chen, C.-H., Pulinets, S., Hattori, K., Ouzounov, D., Tramutoli, V., et al. (2024, January 20). Spatial analyses on pre-earthquake ionospheric anomalies and magnetic storms observed by China seismo-electromagnetic satellite in August 2018. Geoscience Letters, 11(1), 20. https://doi.org/10.1186/s40562-024-00320-2

Grimalsky, V., Kotsarenko, A., Yutsis, V., Pulinets, S., & Del Razo Gonzalez, A. (2023, December 29). New insights into the simulations of electric currents for discharges and ULF magnetic-field perturbations: Applications to the Popocatepetl Volcano and a micro-discharge model. Remote Sensing, 16(1), 151. https://doi.org/10.3390/rs16010151

Shitov, A. V., Pulinets, S. A., & Budnikov, P. A. (2023, August). Effect of earthquake preparation on changes in meteorological characteristics (based on the example of the 2003 Chuya earthquake). Geomagnetism and Aeronomy, 63(6), 745–755. https://doi.org/10.1134/s0016793223600285

Maria Pinelli | Research Excellence | Best Researcher Award

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Dr. Maria Pinelli | Research Excellence | Best Researcher Award

Dr. Maria Pinelli | Radboud University Medical Center | Italy

Dr. Maria Pinelli is an Assistant Professor Junior (RTDa) at the Politecnico di Milano (Italy) in the Department of Management, Economics, and Industrial Engineering (ING-IND/35). Her academic and research work focuses on technological innovation in healthcare, with particular attention to Health Technology Assessment (HTA), innovation management in hospitals, and the integration of scanning and assessment processes to enhance healthcare value creation. She earned her Ph.D. from Politecnico di Milano in 2025 with a thesis titled “MedTech Innovation in Hospitals: Re-Framing the Integration between Scanning and Assessment and the Determinants of Value.” During her doctoral studies, she was a Visiting Ph.D. Student at Radboud University (Netherlands), collaborating on international research exploring hospital technology strategies. Her academic background also includes a Master’s Degree in Management Engineering with specialization in Sustainable Operations Management and Social Innovation and a Bachelor’s Degree in Industrial Engineering, both completed with honors. Dr. Pinelli has published extensively in high-impact international journals such as Health Policy, Technological Forecasting and Social Change, PLOS ONE, IEEE Journal of Translational Engineering in Health and Medicine, and IJERPH. Her works contribute to understanding the strategic, clinical, and socio-economic evaluation of medical technologies and the role of digital transformation and sustainability in healthcare systems. She has been actively involved in teaching and coordinating courses such as Innovation in Health and Social Care, Healthcare Management, and Economia e Organizzazione Aziendale at Politecnico di Milano and Humanitas University. Her contributions extend to international conferences, including EURAM, ISPOR, IPDMC, and Health Technology Assessment International, where she presented cutting-edge research on hospital innovation, inclusive healthcare technologies, and decision-making frameworks. Dr. Pinelli also serves as a reviewer for several leading journals, including the Journal of Medical Internet Research and Health Services Management Research. Beyond academia, she has contributed to practitioner conferences addressing the impact of AI and MedTech innovation in healthcare. Through her multidisciplinary expertise, international collaboration, and commitment to advancing healthcare innovation, Dr. Maria Pinelli represents a new generation of scholars bridging management engineering and medical technology for sustainable, patient-centered care.

Profiles: Google Scholar

Featured Publications 

Pinelli, M., Moglia, A., Marsilio, L., Rossi, M., Lettieri, E., Mainardi, L., & Manzotti, A. (2023). Mixed reality and artificial intelligence: A holistic approach to multimodal visualization and extended interaction in knee osteotomy. IEEE Journal of Translational Engineering in Health and Medicine, 10. https://doi.org/10.1109/JTEHM.2023.3335608

Pinelli, M., Manetti, S., & Lettieri, E. (2023). Assessing the social and environmental impact of healthcare technologies: Towards an extended social return on investment. International Journal of Environmental Research and Public Health, 20(6), 5224. https://doi.org/10.3390/ijerph20065224

Di Francesco, A., Pinelli, M., Lettieri, E., Toletti, G., & Galli, M. (2023). Towards a more inclusive society: The social return on investment (SROI) of an innovative ankle–foot orthosis for hemiplegic children. Sustainability, 15(5), 4361. https://doi.org/10.3390/su15054361

Pinelli, M., Gerardi, C., Lettieri, E., Maioru, M., Marone, L., Bertoldi, L., Navanteri, G., Costantini, M., Botti, C., & Pellini, F. (2024). Comparison of indocyanine green with conventional tracers for sentinel lymph node biopsy in breast cancer: A multidisciplinary evaluation of clinical effectiveness, safety, organizational and economic impact. PLOS ONE, 19(8), e0309336. https://doi.org/10.1371/journal.pone.0309336

Pinelli, M., Lettieri, E., Boaretto, A., Casile, C., Citro, G., Zazzaro, B., & Ravazzoni, A. (2022). Glucometer usability for 65+ type 2 diabetes patients: Insights on physical and cognitive issues. Sensors, 22(16), 6202. https://doi.org/10.3390/s22166202

Jyoti Srivastava | Research Excellence | Best Researcher Award

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Dr. Jyoti Srivastava | Research Excellence | Best Researcher Award

Dr. Jyoti Srivastava | Moffitt Cancer Center | United States

Dr. Jyoti Srivastava, Senior Research Scientist in the Department of Tumor Microenvironment and Metastasis at Moffitt Cancer Center, is an accomplished molecular biologist with over 18 years of pioneering experience spanning cancer biology, immuno-oncology, and therapeutic discovery. Her multidisciplinary research integrates molecular genetics, pharmacology, redox biology, and genomics to uncover mechanisms driving tumor progression, metastasis, and drug resistance. At Moffitt, Dr. Srivastava has made groundbreaking discoveries in melanoma, elucidating how redox and nitrosylation signaling pathways modulate immune evasion and therapeutic resistance in NRAS-driven cancers. Her work has identified actionable targets and led to the development of innovative RNAi-, PROTAC-, and small-molecule–based therapeutics that have advanced toward preclinical and clinical evaluation. Previously at Arrowhead Pharmaceuticals and Yale University, she spearheaded translational research programs that delivered clinical candidates for lung diseases and cancer, while uncovering novel oncogenic pathways such as AEG-1/MTDH in hepatocellular carcinoma and non-alcoholic steatohepatitis (NASH). Dr. Srivastava’s contributions—reflected in over 30 peer-reviewed publications, invited talks at major international conferences, and successful therapeutic innovations—underscore her leadership in bridging fundamental discoveries with clinical application, advancing next-generation strategies to combat cancer and chronic diseases.

Profiles: Google Scholar

Featured Publications 

Yoo, B. K., Santhekadur, P. K., Gredler, R., Chen, D., Emdad, L., Bhutia, S., … & Fisher, P. B. (2011). Increased RNA-induced silencing complex (RISC) activity contributes to hepatocellular carcinoma. Hepatology, 53(5), 1538–1548. https://doi.org/10.1002/hep.24221

Santhekadur, P. K., Das, S. K., Gredler, R., Chen, D., Srivastava, J., Robertson, C., … & Fisher, P. B. (2012). Multifunction protein staphylococcal nuclease domain containing 1 (SND1) promotes tumor angiogenesis in human hepatocellular carcinoma through a novel pathway involving NF-κB and miR-221. Journal of Biological Chemistry, 287(17), 13952–13958. https://doi.org/10.1074/jbc.M111.323899

Sarkar, D., & Fisher, P. B. (2013). AEG-1/MTDH/Lyric: Clinical significance. Advances in Cancer Research, 120, 39–74. https://doi.org/10.1016/B978-0-12-401676-7.00002-0

Srivastava, J., Siddiq, A., Emdad, L., Santhekadur, P. K., Chen, D., Gredler, R., … & Fisher, P. B. (2012). Astrocyte elevated gene-1 promotes hepatocarcinogenesis: Novel insights from a mouse model. Hepatology, 56(5), 1782–1791. https://doi.org/10.1002/hep.25841

Santhekadur, P. K., Akiel, M., Emdad, L., Gredler, R., Srivastava, J., … & Fisher, P. B. (2014). Staphylococcal nuclease domain containing-1 (SND1) promotes migration and invasion via angiotensin II type 1 receptor (AT1R) and TGF-β signaling. FEBS Open Bio, 4, 353–361. https://doi.org/10.1016/j.fob.2014.03.001

Darvaish Khan | Material Science | Research Excellence Award

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Dr. Darvaish Khan | Material Science | Research Excellence Award

Dr. Darvaish Khan | Sapienza University of Rome | Italy

Dr. Darvaish Khan is a distinguished postdoctoral researcher at the Department of Chemical Engineering, Materials, and Environment, Sapienza University of Rome, Italy, with an extensive academic and research background in materials science, solid-state physics, and energy materials. He earned his Ph.D. in Materials Science and Engineering from Shanghai Jiao Tong University, China, following a Master’s from Liverpool Hope University, UK, and an M.Sc. in Solid State Physics from the University of Peshawar, Pakistan. Dr. Khan’s research primarily focuses on the design, synthesis, and characterization of metal hydrides, composites, and alloys for advanced hydrogen storage and energy applications. His expertise spans hydrogen-matter interactions, phase transitions in nanostructured environments, and modeling of solid-state metal hydrides using COMSOL Multiphysics. He has developed innovative materials through solid-state mechanochemical, hydrothermal, and wet-impregnation/infiltration methods, utilizing advanced characterization tools such as XRD, SEM, TEM, BET, DSC, TGA, FTIR, XPS, Raman spectroscopy, and Sieverts-type PCT for analyzing structural, thermal, and gas sorption properties. His work significantly contributes to improving the thermodynamics and kinetics of hydrogen sorption in metal hydrides and nanocomposites, addressing global challenges in sustainable hydrogen energy systems. Dr. Khan’s impactful research has been published in top-tier international journals, including Interdisciplinary Materials, Journal of Alloys and Compounds, ACS Applied Materials & Interfaces, Chemical Engineering Journal, and the International Journal of Hydrogen Energy. He has also served as a guest speaker at international conferences, received multiple research excellence awards, and is a reviewer for international scientific journals. As an HEC-approved Ph.D. supervisor and member of the American Chemical Society and International Society of Hydrogen Energy, Dr. Khan continues to advance interdisciplinary innovations in hydrogen storage, nanostructured materials, and sustainable energy technologies, contributing meaningfully to the global transition toward a hydrogen-based clean energy future.

Profiles: Google Scholar

Featured Publications 

Zhu, W., Panda, S., Lu, C., Ma, Z., Khan, D., Dong, J., Sun, F., Xu, H., Zhang, Q., & Zou, J. (2020). Using a self-assembled two-dimensional MXene-based catalyst (2D-Ni@Ti₃C₂) to enhance hydrogen storage properties of MgH₂. ACS Applied Materials & Interfaces, 12(45), 50333–50343.

Ma, Z., Panda, S., Zhang, Q., Sun, F., Khan, D., Ding, W., & Zou, J. (2021). Improving hydrogen sorption performances of MgH₂ through nanoconfinement in a mesoporous CoS nano-boxes scaffold. Chemical Engineering Journal, 406, 126790.

Ma, Z., Zou, J., Khan, D., Zhu, W., Hu, C., Zeng, X., & Ding, W. (2019). Preparation and hydrogen storage properties of MgH₂-trimesic acid-TM MOF (TM = Co, Fe) composites. Journal of Materials Science & Technology, 35(10), 2132–2143.

Khan, D., Zou, J., Zeng, X., & Ding, W. (2018). Hydrogen storage properties of nanocrystalline Mg₂Ni prepared from compressed 2MgH₂–Ni powder. International Journal of Hydrogen Energy, 43(49), 22391–22400.

Ma, Z., Zhang, Q., Panda, S., Zhu, W., Sun, F., Khan, D., Dong, J., Ding, W., & Zou, J. (2020). In situ catalyzed and nanoconfined magnesium hydride nanocrystals in a Ni-MOF scaffold for hydrogen storage. Sustainable Energy & Fuels, 4(9), 4694–4703.

Sayed Abdul Majid Gilani | Emerging Technologies | Best Researcher Award

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Dr. Sayed Abdul Majid Gilani | Emerging Technologies | Best Researcher Award

Dr. Sayed Abdul Majid Gilani | Birmingham City University | United Kingdom

Dr. Sayed Abdul Majid Gilani is an accomplished researcher in electrical and electronic engineering, specializing in embedded systems, automation, and control engineering. His multidisciplinary research integrates hardware design, sensor networks, and artificial intelligence to develop innovative and energy-efficient solutions for real-world challenges. With over a decade of experience in academia and applied research, Dr. Gilani has contributed significantly to the advancement of embedded control technologies, renewable energy optimization, and industrial automation systems. His work emphasizes intelligent system design, IoT-based automation, and the integration of machine learning algorithms for enhanced performance and sustainability. Dr. Gilani has published extensively in high-impact journals and presented at leading international conferences, reflecting his global engagement and scientific rigor. He has also supervised numerous research projects and guided students in developing practical applications of emerging technologies. His research outputs demonstrate a strong commitment to technological innovation that bridges the gap between theory and application. Recognized for his academic excellence and collaborative research initiatives, Dr. Gilani continues to advance cutting-edge developments that contribute to the evolution of smart, adaptive, and efficient engineering systems—making him a deserving candidate for the Best Researcher Award.

Profiles: Google Scholar | Scopus | LinkedIn | Research Gate

Featured Publications 

Gilani, S. A. M., & Faccia, A. (2021). Broadband connectivity, government policies, and open innovation: The crucial IT infrastructure contribution in Scotland. Journal of Open Innovation: Technology, Market, and Complexity, 8(1), 1. https://doi.org/10.3390/joitmc8010001

Gilani, S. A. M., Copiaco, A., Gernal, L., Yasin, N., Nair, G., & Anwar, I. (2023). Savior or distraction for survival: Examining the applicability of machine learning for rural family farms in the United Arab Emirates. Sustainability, 15(4), 3720. https://doi.org/10.3390/su15043720

Gilani, S., Gernal, L., Tantry, A., Yasin, N., & Sergio, R. (2022). Leadership styles adopted by Scottish micro-businesses during the COVID-19 pandemic. In Proceedings of the International Conference on Business and Technology (pp. 144–156). Springer.

Al Jaghoub, J., Suleiman, A., Takshe, A. A., Moussa, S., Gilani, S. A. M., Sheikh, S., & others. (2024). The role of innovation in waste management for enterprises: A critical review of the worldwide literature. In Technology-Driven Business Innovation (pp. 453–464). Springer.

Gernal, L., Tantry, A., Gilani, S. A. M., & Peel, R. (2024). The impact of online learning and soft skills on college student satisfaction and course feedback. In Technology-Driven Business Innovation: Unleashing the Digital Advantage (pp. 42–54). Springer.

Gilani, S. A. M., Tantry, A., Askri, S., Gernal, L., & Sergio, R. (2023). Adoption of machine learning by rural farms: A systematic review. In Proceedings of the International Conference on Computing and Informatics (pp. 324–335). Springer.

Barham Farraj | Robotics Engineering | Best Researcher Award

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Mr. Barham Farraj | Robotics Engineering | Best Researcher Award

Mr. Barham Farraj | kromberg & schubert | Slovakia 

The researcher is a highly motivated and results-oriented Service and Development Engineer specializing in robotics, LiDAR systems, and autonomous driving technologies. His work focuses on bridging the gap between development and practical deployment of intelligent robotic systems, with a strong emphasis on perception, mapping, and navigation using LiDAR-based solutions. He has demonstrated exceptional technical expertise through hands-on experience at the Vehicle Research Center in Győr, Hungary, contributing significantly to autonomous vehicle research, system integration, and performance optimization. A key highlight of his research is the development of a real-time LiDAR-based urban road and sidewalk detection system for autonomous vehicles. This project integrates advanced LiDAR sensing with ROS2, C++, Python, and MATLAB, enabling robust environmental perception and accurate object classification in complex urban settings. By leveraging point cloud processing and machine learning techniques, his work enhances vehicle awareness, paving the way for safer and more efficient autonomous navigation. He has also contributed to major academic and industrial initiatives, including building and programming autonomous racing vehicles for international competitions such as RoboRacer and F1TENTH, and leading simulation-based testing in Gazebo and Foxglove environments. His research extends to transforming ROS1-based algorithms into ROS2 for improved modularity and scalability across multi-vehicle systems. In his current role at Kromberg & Schubert Automotive, Slovakia, he develops embedded applications and perception systems for industrial mobile platforms, integrating sensor data and diagnostics for enhanced reliability. His teaching and mentoring roles at Széchenyi István University reflect his dedication to knowledge transfer and educational impact in autonomous robotics. Through his combined research, engineering practice, and leadership, he has contributed to advancing LiDAR-driven perception, real-time mapping, and autonomous vehicle intelligence, marking him as a promising innovator in the field of intelligent mobility and robotic automation.

Profiles: Orcid

Featured Publications 

Barham Farraj, B. J., Alabdallah, A., Unger, M., & Horváth, E. (2025, October 31). Enhancing autonomous navigation: Real-time LiDAR detection of roads and sidewalks in ROS 2. Engineering Proceedings, 113(24). https://doi.org/10.3390/engproc2025113024

Krecht, R., Alabdallah, A. M. A., & Barham Farraj, B. J. (2025, October 28). Evaluation of SLAM methods for small-scale autonomous racing vehicles. Engineering Proceedings, 113(9). https://doi.org/10.3390/engproc2025113009

Alabdallah, A., Barham Farraj, B. J., & Horváth, E. (2025, October 28). ROS 2-based framework for semi-automatic vector map creation in autonomous driving systems. Engineering Proceedings, 113(13). https://doi.org/10.3390/engproc2025113013

Ivis Garcia | Research Excellence | Best Researcher Award

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Dr. Ivis Garcia | Research Excellence | Best Researcher Award

Dr. Ivis Garcia | Texas A&M University | United States

Dr. Ivis García, Ph.D., AICP, is an Associate Professor in the Department of Landscape Architecture and Urban Planning at Texas A&M University, with a distinguished record of scholarship, teaching, and community engagement in housing, urban policy, and social equity. Her research is grounded in the principles of community development, participatory planning, and social justice, with a particular emphasis on advancing diversity, equity, and inclusion within urban systems. Dr. García’s work focuses on asset-based community development (ABCD) approaches that empower marginalized populations to build capacity and resilience through locally driven solutions. She explores the intersections of housing policy, disaster recovery, gentrification, and displacement, particularly within Latino and Puerto Rican communities in the United States and the Caribbean. Her doctoral dissertation, “The Puerto Rican Identity: Reconstructing Ownership in the Face of Change,” set the foundation for a research agenda that bridges cultural identity with community-based planning and equitable housing strategies. Through her collaborations with organizations such as the Puerto Rican Cultural Center, Texas Appleseed, and Foundation for Puerto Rico, Dr. García integrates academic research with real-world impact, informing equitable policy design and participatory decision-making. She has been a Ford Foundation Fellow, Emerging Poverty Scholar, and recipient of numerous professional awards, including theTexas APA Student Project Award and the  Curriculum Innovation Award from the Lincoln Institute of Land Policy. Her research has contributed to national dialogues on resilient housing, participatory governance, and social vulnerability in urban environments, often linking theory to applied planning practice. By engaging communities directly in the research process, Dr. García exemplifies the model of a scholar-activist—translating knowledge into meaningful action that promotes inclusive, just, and sustainable urban futures. Her work continues to inspire transformative practices in housing equity and community resilience across diverse urban landscapes.

Profiles: Orcid

Featured Publications 

García, I. (2025). Earthship architecture as a pathway to post-hurricane resilience and energy independence: A case study analysis in Puerto Rico. Urban Science, 9(11), 446. https://doi.org/10.3390/urbansci9110446

Kim, M., García, I., Goetz, E., Hanlon, B., Monkkonen, P., Pendall, R., Pfeiffer, D., Reece, J., & Whittemore, A. (2025). Bring zoning back into the planning curricula. Journal of the American Planning Association. https://doi.org/10.1080/01944363.2025.2455162

García, I. (2025). Residential green infrastructure: Unpacking motivations and obstacles to single-family-home tree planting in diverse, low-income urban neighborhoods. Sustainability, 17(16), 7412. https://doi.org/10.3390/su17167412

García, I. (2025). When the map does not tell the whole story: Integrating community voices into GIS gentrification analysis. Land, 14(8), 1510. https://doi.org/10.3390/land14081510

García, I., Jackson, A., Lee, C. A., Chrisinger, B., & Greenlee, A. J. (2025). On the outside looking in: Latina/o/x and African American student perspectives on community-engaged courses. Journal of Planning Education and Research. https://doi.org/10.1177/0739456X251339979

García, I. (2025). The poorer the neighborhood, the harder it is to reach the park: A GIS equity analysis from Salt Lake City. Sustainability, 17(9), 3774. https://doi.org/10.3390/su17093774

Tengping Jiang | Robotics Engineering | Best Researcher Award

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Dr. Tengping Jiang | Robotics Engineering | Best Researcher Award

Dr. Tengping Jiang | Nanjing Normal University | China

Dr. Tengping Jiang is an accomplished researcher and Associate Professor at the School of Geography, Nanjing Normal University, where he also serves as Deputy Director of the Department of Surveying and Mapping Engineering. His research focuses on 3D reconstruction, scene understanding, point cloud processing, and deep learning-based computer vision, with applications spanning intelligent transportation systems, digital twin cities, and plant phenotyping. Dr. Jiang earned his Ph.D. from the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, under the supervision of Prof. Bisheng Yang, and later conducted visiting research at the Eastern Institute of Technology, Ningbo, guided by Prof. Wenjun Zeng (IEEE Fellow). His scholarly contributions have advanced the integration of artificial intelligence with geospatial technologies, particularly through the development of innovative neural network architectures for semantic segmentation and structural feature extraction from LiDAR and urban scene point clouds. His highly cited works, published in leading journals such as ISPRS Journal of Photogrammetry and Remote Sensing and IEEE Transactions on Geoscience and Remote Sensing, include groundbreaking studies like RailSeg, LWSNet, and ShrimpSeg, which address complex challenges in automated urban and environmental data interpretation. Dr. Jiang has received multiple prestigious research grants, including the NSFC Young Scientists Fund (2025–2027) and the Natural Science Foundation of Jiangsu Province Young Scientists Fund (2024–2027). His projects emphasize fine-grained scene extraction, LiDAR data fusion, and energy-efficient modeling of urban environments. Beyond research, Dr. Jiang contributes extensively to academic service, serving on the Youth Editorial Boards of Plant Phenotype, Agriculture Communications, and Climate Smart Agriculture, and as a reviewer for top-tier conferences like CVPR and NeurIPS. Through his interdisciplinary expertise, Dr. Jiang continues to push the boundaries of 3D geospatial intelligence and its transformative applications in smart and sustainable cities.

Profiles: Orcid

Featured Publications 

Jiang, T., Wang, Y., Liu, S., Zhang, Q., Zhao, L., & Sun, J. (2023). Instance recognition of street trees from urban point clouds using a three-stage neural network. ISPRS Journal of Photogrammetry and Remote Sensing, 109, 305–334. https://doi.org/10.1016/j.isprsjprs.2023.04.010

Jiang, T., Zhang, Q., Liu, S., Liang, C., Dai, L., Zhang, Z., Sun, J., & Wang, Y. (2023). LWSNet: A point-based segmentation network for leaf–wood separation of individual trees. Forests, 14(7), 1303. https://doi.org/10.3390/f14071303

Jiang, T., Liu, S., Zhang, Q., Xu, X., Sun, J., & Wang, Y. (2023, September). Segmentation of individual trees in urban MLS point clouds using a deep learning framework based on cylindrical convolution network. International Journal of Applied Earth Observation and Geoinformation, 123, 103473. https://doi.org/10.1016/j.jag.2023.103473

Jiang, T., Yang, B., Wang, Y., Dai, L., Qiu, B., Liu, S., Li, S., Zhang, Q., Jin, X., & Zeng, W. (2023). RailSeg: Learning local–global feature aggregation with contextual information for railway point cloud semantic segmentation. IEEE Transactions on Geoscience and Remote Sensing, 61, 5704929. https://doi.org/10.1109/TGRS.2023.3319950

Jiang, T., Wang, Y., Zhang, Z., Liu, S., Dai, L., Yang, Y., Jin, X., & Zeng, W. (2023). Extracting 3-D structural lines of buildings from ALS point clouds using graph neural network embedded with corner information. IEEE Transactions on Geoscience and Remote Sensing, 61, 5702615. https://doi.org/10.1109/TGRS.2023.3278589

Shadi Shayan | Emerging Technologies | Best Researcher Award

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Dr. Shadi Shayan | Emerging Technologies | Best Researcher Award

Dr. Shadi Shayan | Adelaide University | Australia

Dr. Shadi Shayan’s research lies at the intersection of project management, smart technologies, and social sustainability, focusing on how large-scale urban innovation programs can effectively manage social risks and deliver equitable outcomes. His scholarly work explores the dynamic relationships between technological transformation, social response, and governance frameworks in smart city development. By integrating change management models with risk management processes, Dr. Shayan has developed innovative frameworks that address the socio-demographic dimensions of smart city transitions—bridging theory, practice, and policy. His doctoral research, “Integrating change models and risk management processes: A framework to manage social risks in smart city programs”, provides a comprehensive model for mitigating community resistance and fostering inclusive participation in technologically driven urban initiatives. Dr. Shayan’s publications in leading journals such as Smart Cities, Sustainable Cities and Society, and International Journal of Construction Management advance understanding of how social factors, demographic variables, and stakeholder perceptions influence the success of smart city and infrastructure projects. A consistent theme in his research is the application of systems thinking and socio-technical analysis to enhance decision-making in project and program management. He also examines the evolving roles of professionals, including engineers and quantity surveyors, in adapting to emerging technological and societal challenges. Dr. Shayan’s work has significant implications for both academia and industry. It informs policy frameworks for smart urban governance, supports organizational strategies for managing social risk, and contributes to sustainable and resilient infrastructure planning. Through interdisciplinary collaborations and active engagement with the Smart Cities Council Australia New Zealand, he connects research with real-world impact—helping shape cities that are not only technologically advanced but also socially responsible and inclusive.

Profiles: Google Scholar | LinkedIn

Featured Publications 

Shayan, S., & Kim, K. P. (2025). Social responses and change management strategies in smart city transitions: A socio-demographic perspective. Smart Cities, 8(6), 188. https://doi.org/10.3390/smartcities8060188

Shayan, S., & Kim, K. P. (2023). Understanding correlations between social risks and sociodemographic factors in smart city development. Sustainable Cities and Society, 89, 104320. https://doi.org/10.1016/j.scs.2022.104320

Shayan, S., & Kim, K. P. (2022). A conceptual framework to manage social risks for smart city development programs. In Resilient and responsible smart cities (pp. 77–86). Springer, Cham. https://doi.org/10.1007/978-3-030-98423-6_6

Shayan, S., Kim, K. P., Ma, T., & Nguyen, T. H. D. (2020). The first two decades of smart city research from a risk perspective. Sustainability, 12(21), 9280. https://doi.org/10.3390/su12219280

Shayan, S., & Kim, K. P., & Tam, V. (2019). Critical success factor analysis for effective risk management at the execution stage of a construction project. International Journal of Construction Management, 22(3), 379–386. https://doi.org/10.1080/15623599.2019.1624678

Yong Liu | Research Excellence | Innovative Research Award

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Assoc. Prof. Dr. Yong Liu | Research Excellence | Innovative Research Award

Assoc. Prof. Dr Yong Liu | Tianjin University | China

Dr. Yong Liu is an Associate Professor at the School of Electrical and Information Engineering, Tianjin University, China. With an extensive record of scholarly contributions, he has authored and co-authored over 100 technical papers, three books or book chapters, and more than 50 patents in electrical engineering. His research primarily focuses on ageing evaluation, defect diagnosis, and performance monitoring of outdoor insulators and power cables under complex atmospheric and electrical conditions. Dr. Liu’s pioneering work integrates advanced sensing technologies, signal processing, and artificial intelligence to improve the reliability and safety of high-voltage power transmission systems. His studies on leakage current characteristics, surface discharges, and magnetic field-based condition evaluation have significantly advanced diagnostic techniques for high-voltage alternating current (HVAC) and direct current (HVDC) equipment. Notable recent contributions include research on multi-scale leakage current feature extraction using graph neural networks, magnetic field feature analysis for power cable evaluation, and dynamic discharge behavior of ice-covered insulators under DC voltages. He has made substantial progress in understanding the electro-thermal and mechanical ageing mechanisms of polymeric insulators and cables, developing novel monitoring strategies and predictive models for insulation failure. His publications in leading journals such as IEEE Transactions on Dielectrics and Electrical Insulation, IEEE Access, Energies, and Polymers demonstrate his sustained excellence and influence in high-voltage engineering and applied materials science. As a member of the Chinese Society for Electrical Engineering (CSEE) and the Institute of Electrical and Electronics Engineers (IEEE), Dr. Liu actively contributes to international collaboration and academic exchange. His innovative research continues to support the development of smart grid technologies, advanced cable diagnostics, and climate-resilient power systems, positioning him as a leading scholar in electrical insulation and power engineering research.

Profile: Orcid

Featured Publications 

Liu, Y., Lin, M., Wei, H., Duan, X., Li, Z., & Fu, Q. (2025). Cable outer sheath defect identification using multi-scale leakage current features and graph neural networks. Energies, 18(21), 5687. https://doi.org/10.3390/en18215687

Liu, Y., Wang, M., Huang, Y., Han, T., & Du, B. (2024). Feature extraction of magnetic field for condition evaluation of HVAC power cable. IEEE Transactions on Dielectrics and Electrical Insulation. https://doi.org/10.1109/TDEI.2023.3342774

Liu, Y., Li, C., Yin, F., Du, B. X., & Farzaneh, M. (2024). Nonlinear traits of leakage current and dynamic actions of surface discharges on ice-covered insulators under DC voltages. IEEE Transactions on Dielectrics and Electrical Insulation. https://doi.org/10.1109/TDEI.2024.3373549

Liu, Y., Guo, Y., Wang, B., Li, Q., Gao, Q., & Wan, Y. (2024). Research on influencing factors and wind deflection warning of transmission lines based on meteorological prediction. Energies, 17(11), 2612. https://doi.org/10.3390/en17112612

Liu, Y., Xin, Y., Huang, Y., Du, B., Huang, X., & Su, J. (2024). Optimal design and development of magnetic field detection sensor for AC power cable. Sensors, 24(8), 2528. https://doi.org/10.3390/s24082528

Liu, Y., Xin, Y., Du, B., Huang, X., & Su, J. (2024, March 22). Optimal design and development of magnetic field detection sensor for AC power cable [Preprint]. Preprints. https://doi.org/10.20944/preprints202403.1352.v1