Yuan Xue | Statistical Applications in Engineering | Best Researcher Award

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Assoc Prof. Dr. Yuan Xue | Statistical Applications in Engineering | Best Researcher Award

Chengdu University of Technology | China

Assoc Prof. Dr. Yuan Xue, an accomplished Associate Professor at Chengdu University of Technology, is a leading researcher in the specialized domain of earthquake statistics and geostatistical modeling, with a strong record of academic excellence, scientific innovation, and professional service. His research career is distinguished by substantial contributions to statistical inference in seismicity, the development of earthquake probability models, and the quantitative assessment of seismic hazard patterns across major fault systems in Sichuan, China. Over the years, he has independently led two provincial-level scientific research projects and participated as a principal contributor in two major national-level initiatives, including one supported by the National Key Research and Development Program and another funded by the National Natural Science Foundation of China. In addition, he has been involved in eight provincial-level scientific projects and has successfully completed a total of fifteen scientific and consultancy projects in both academic and applied settings. Dr. Xue has demonstrated prolific scholarly output, publishing seventeen peer-reviewed journal articles as first or corresponding author across SCI, Scopus, and other prestigious platforms, contributing significantly to advancements in earthquake statistical theory and practical seismic risk analysis. His Scopus academic profile further reflects his growing global impact, with an h-index of 26, 8 documents, and 174 citations, complementing his broader citation record of 18 citations in Web of Science and 88 citations in CNKI. He has also contributed to academic literature through the publication of three books with internationally recognized ISBNs and has secured four national invention patents, demonstrating the applied value and innovation of his work. Dr. Xue’s expertise extends to professional academic service, serving as a reviewer and editor of the South China Journal of Seismology, as well as collaborating with the Sichuan Earthquake Agency to carry out high-impact statistical inference studies on seismic patterns of major regional fault systems. His research achievements have been recognized through multiple awards, including two second prizes in National Land and Resources Science and Technology, a second prize in Sichuan Province Science and Technology Progress, and a prestigious first prize in the Sichuan Province On-site Statistics Society Excellent Achievement Award. As an active member of the Chinese Association for Applied Statistics, the Chinese Mathematical Society, and the Sichuan Association for Applied Statistics-where he also serves as Deputy Secretary-General, Dr. Xue continues to expand the role of statistical science in earthquake research, contributing meaningful advancements to national and regional seismic safety and hazard prediction efforts.

Profile: Scopus 

Featured Publications

Wei, D., Xue, Y., Wang, X., Liu, W., & He, J. (2025). Stability monitoring of deep soil in slope based on local strain and continuous vibration information analysis. Optical Fiber Technology,

Li, T., Tian, J., Pei, X., Guo, J., Chen, M., Xue, Y., & Meng, M. (2025). Shear strength indices predication model for coarse-grained soil based on particle gradation and moisture content information. Bulletin of Engineering Geology and the Environment,

Kaili Wang | Machine Learning and Statistics | Best Researcher Award

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Dr. Kaili Wang | Machine Learning and Statistics | Best Researcher Award

university of malaya | Malaysia

Dr. Kaili Wang is an accomplished economist and Doctoral Candidate in Financial Economics at the University of Malaya, with a strong academic foundation in quantitative analysis, holding a master’s degree in Quantitative Economics from Zhongnan University of Economics and Law and a bachelor’s degree in Statistics from Luoyang Normal University. She has extensive teaching experience, having served as a full-time faculty member at the Business School of Nantong University of Technology, where she contributed significantly to both academic research and student mentorship. Her research expertise encompasses financial security, green finance, and the operational efficiency of financial institutions, reflected in her monographs, including Analysis of RMB Internationalization Path from the Perspective of Financial Security (sole author) and Research on the Long-term Mechanism of Green Finance Development (second author). She has also led impactful research projects, such as the Jiangsu Provincial University Philosophy and Social Sciences Research Project on the operational efficiency of city commercial banks. Kaili Wang has demonstrated a strong commitment to student development, guiding participants in national and provincial financial competitions to notable achievements, including second and third prizes in the National ETF Elite Challenge and the “East Money Cup” National College Students’ Financial Challenge, and earning recognition as an Excellent Supervisor. Her work reflects a combination of rigorous empirical analysis and practical engagement with financial markets, emphasizing sustainable finance and strategic economic development. With a focus on integrating academic excellence with real-world financial insights, Kaili Wang continues to advance knowledge in financial economics while nurturing the next generation of economists and financial professionals through research, mentorship, and academic leadership. Her career demonstrates a sustained dedication to both scholarly contributions and fostering student success in competitive financial arenas.

Profile: Orcid

Featured Publication

Wang, K. (2024). An analysis of the RMB internationalization path from the perspective of financial security.

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.

Youngjoo Kwon | Design of Experiments (DOE) | Research Excellence Award

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Prof. Youngjoo Kwon | Design of Experiments (DOE) | Research Excellence Award

Ewha Womans University | South Korea

Dr. Youngjoo Kwon is a highly accomplished professor in the College of Pharmacy and Graduate School of Pharmaceutical Sciences at Ewha Womans University, where she has held influential leadership roles including Director of the Ewha Drug Development Research Core Center, Chair of the Graduate School, and Director of a major convergence education program. After completing her Ph.D. in Analytical Chemistry at the University of Houston and postdoctoral training at Baylor College of Medicine, she established a research laboratory that integrates advanced analytical instrumentation such as HPLC, GC-MS, LC-MS/MS, and NMR with computational modeling and diverse biochemical, molecular, and cellular biology platforms. Her interdisciplinary research spans metabolite profiling of endogenous and xenobiotic compounds, development of isozyme-selective enzyme inhibitors, and elucidation of the non-canonical cytosolic functions of the transcription factor ELF3/ESX, particularly its interaction with MED23 in driving metastasis and drug resistance in various cancers. Additionally, her laboratory develops and evaluates small-molecule modulators against challenging disease targets related to cancer, fibrosis, and neurodegeneration. Over her prolific scientific career, Dr. Kwon has published more than 175 peer-reviewed documents, accumulated over 5,053 citations, and achieved an h-index of 35, underscoring both the breadth and lasting impact of her contributions to pharmaceutical sciences and biomedical research. Her work has appeared in leading journals and has resulted in patents and successful licensing initiatives, demonstrating strong translational value. Dr. Kwon’s achievements have earned her numerous honors from major scientific societies, including awards from the Korean Society of Applied Pharmacology, the Pharmaceutical Society of Korea, and a ministerial award from the Ministry of Trade, Industry and Energy. She is also deeply engaged in national regulatory and scientific policy activities, serving on advisory committees for the Ministry of Food and Drug Safety, the Korea Drug Development Fund, and several national research and technology evaluation boards. In addition, she contributes to the global scientific community through editorial roles in multiple international journals. Her research philosophy-rooted in mechanistic understanding, analytical innovation, and therapeutic development-continues to drive advancements in areas such as KRAS-mutant colorectal cancer, hepatic fibrosis, and metastatic progression, solidifying her standing as a leading scientist shaping next-generation drug discovery and disease-targeted interventions.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Khurshid Hussain | Artificial Intelligence in Statistics | Research Excellence Award

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Mr. Khurshid Hussain | Artificial Intelligence in Statistics | Research Excellence Award

Kiost | South Korea

Mr. Khurshid Hussain is a dynamic researcher whose work spans advanced automotive engineering, semiconductor design, integrated sensing and communications, and AI-driven signal processing, establishing him as a multidisciplinary contributor across next-generation wireless, cybersecurity, and intelligent vehicular systems. He holds a Master’s degree in Advanced Automotive Engineering from Sun Moon University, South Korea, where he specialized in high-performance millimeter-wave circuit design with emphasis on 60 GHz digital variable-gain amplifiers, beamforming architectures, low-power attenuators, and chip-level ISAC systems for secure and intelligent communication. His research extends into geomatics and remote sensing, focusing on multimodal mapping using optical, SAR, and LiDAR streams, change detection, 3D reconstruction, and uncertainty-aware geospatial pipelines, alongside self-supervised and weak-supervised learning approaches for large-scale spatial data modeling. He is the inventor of a patented transistor-array-based variable attenuator and has authored an expanding collection of peer-reviewed publications in leading journals such as Electronics, IEEE Access, Applied Sciences, and IEEE Transactions, addressing topics ranging from radar–communication co-design and ultrasonic 3D beamforming sensors to predictive maintenance of aerospace components, OTFS-based V2X ISAC architectures, and AI-enhanced signal intelligence. His scholarly profile includes 9 documents, 77 citations, and an h-index of 4, reflecting his growing influence in mmWave IC design, wireless sensing, and AI-integrated communication. Khurshid has delivered technical presentations at major international conferences covering maritime IT convergence, high-frequency amplifier design, battery analytics, advanced beamforming, and power-efficient RF front-end systems. His expertise spans Cadence, HFSS, Python, MATLAB, OrCAD, cybersecurity tools, and vector network analyzers, reinforced by experience in transceiver integration, AI-chip convergence, intrusion detection systems, battery research, and embedded engineering. Earlier, he completed his B.Sc. in Electrical Engineering with a focus on IoT-based renewable-energy automation, where he developed sensor-driven, cloud-connected, and energy-efficient systems. Fluent in English and active in multicultural environments, Khurshid is known for his creativity, leadership, communication skills, and passion for innovation, continually advancing secure, intelligent, and energy-efficient technologies for the automotive, wireless, and sensing industries.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Hussain, K., & Yoo, J. (2025). Low-latency marine-based OTFS echo parameter estimation enabled by AI. Sensors, 25(23), Article 7104. DOI: 10.3390/s25237104

Hussain, K., Ali, E. M., Hussain, W., Raza, A., & Elkamchouchi, D. H. (2025). Robust OTFS-ISAC for vehicular-to-base station end-to-end sensing and communication. Electronics, 14(21), Article 4340. DOI: 10.3390/electronics14214340

Hussain, K., Jeon, W., Lee, Y., Song, I., & Oh, I. (2025). CMOS-compatible ultrasonic 3D beamforming sensor system for automotive applications. Applied Sciences, 15(16), Article 9201. DOI: 10.3390/app15169201

Hussain, K., & Oh, I. (2024). Joint radar, communication, and integration of beamforming technology. Electronics, 13(8), Article 1531. DOI: 10.3390/electronics13081531

Hussain, K., & Oh, I. (2024). Review of joint radar, communication, and integration of beam-forming technology. Preprint. DOI: 10.20944/preprints202404.0208.v1

En Yu | Artificial Intelligence in Statistics | Excellence in Research Award

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Mr. En Yu | Artificial Intelligence in Statistics | Excellence in Research Award

Huazhong University of Science and Technology | China

Mr. En Yu is a PhD student in the Department of Intelligence Science and Technology at Huazhong University of Science and Technology (HUST), where he also completed his M.S. and B.Eng. degrees, building a strong foundation in automation, intelligent systems, and multimodal learning. His research focuses on visual perception, spatial intelligence, and multimodal large language models (MLLMs), with pioneering contributions in image and video understanding, multimodal reasoning, and reinforcement learning–based alignment for foundation models. He has produced influential work, including research on anti-scaling laws and temporal hacking in video MLLMs, the development of future-prediction multimodal reasoning models, perception policy learning with RL for visual tasks, and breakthroughs in fully end-to-end multi-object tracking. His earlier work established new directions in cross-domain tracking with natural-language representations, contrastive multi-object tracking, and decoupled representation learning for relation-aware MOT. Yu has further advanced spatial intelligence through contributions to 3D multi-object tracking and open-vocabulary tracking, bridging perception, reasoning, and robust scene understanding. He has interned at MEGVII Technology in the Foundation Model Group under Xiangyu Zhang, at StepFun AI in the Multimodal LLM Group under Zheng Ge, and at the UCSB NLP Group under William Wang as a visiting PhD researcher, contributing to cutting-edge multimodal systems and video-language modeling. his work is rapidly shaping next-generation MLLMs and visual reasoning systems. He actively serves as a reviewer for top AI conferences including NeurIPS, CVPR, ICCV, ECCV, ICML, ICLR, and leading journals such as TMM and TCSVT. His current interests span synthetic multimodal data generation, supervised and reinforcement post-training for MLLMs, real-world navigation agents, game agents, and spatial perception in visual and multimodal foundation models. Outside research, he enjoys movies, singing, reading, ball games, swimming, and skiing.

Profile: Google Scholar 

Featured Publications

Yu, E., Zhao, L., Wei, Y., Yang, J., Wu, D., Kong, L., Wei, H., Wang, T., Ge, Z., et al. (2024). Merlin: Empowering multimodal LLMs with foresight minds. ECCV, 425–443.

Wei, H., Kong, L., Chen, J., Zhao, L., Ge, Z., Yu, E., Sun, J., Han, C., & Zhang, X. (2024). Small language model meets with reinforced vision vocabulary. arXiv Preprint, arXiv:2401.12503.

Yu, E., Lin, K., Zhao, L., Yin, J., Wei, Y., Peng, Y., Wei, H., Sun, J., Han, C., Ge, Z., et al. (2025). Perception-R1: Pioneering perception policy with reinforcement learning. NeurIPS.

Chen, S., Yu, E., Li, J., & Tao, W. (2024). Delving into the trajectory long-tail distribution for multi-object tracking. CVPR, 19341–19351.

Li, Z., Han, C., Ge, Z., Yang, J., Yu, E., Wang, H., Zhang, X., & Zhao, H. (2024). GroupLane: End-to-end 3D lane detection with channel-wise grouping. IEEE Robotics and Automation Letters, 24.

Jitae Kim | Econometrics and Statistical Economics | Excellence in Research Award

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Dr. Jitae Kim | Econometrics and Statistical Economics | Excellence in Research Award

Environmental Planning Institute | South Korea

Dr. Jitae Kim is a distinguished environmental and resource economist serving as a Senior Researcher at the Environmental Planning Institute of Seoul National University and as an Academic Research Professor with the Korea Research Foundation. He holds a Ph.D., M.A., and B.A. in Economics, completing all degrees at leading Korean universities, and has built a multidisciplinary research portfolio spanning environmental planning, climate economics, applied econometrics, labor-market dynamics, and carbon policy analysis. His scholarly work covers meta-regression valuation of biodiversity, cost–benefit assessments of ecological projects, econometric forecasting of energy demand, and empirical investigations of how climate extremes such as heatwaves and typhoons influence labor markets, wages, and informal work conditions. He has contributed extensively to research on carbon mitigation under the Korean Emissions Trading Scheme, the co-benefits of green remodeling, and the transition toward sustainable energy systems. His international collaborations include major research projects on climate-disaster-driven labor-market disruptions in the Philippines, conducted with academic partners at Ateneo de Manila University. His publications appear in respected international and Korean journals, complemented by multiple working papers, conference presentations, and policy-oriented studies. Based on publicly available academic profiles, he has 2 indexed documents and approximately 109 citations, with an estimated h-index of about 1, reflecting the early but growing influence of his work. Before advancing into academia and research leadership, he served in analytical roles with institutions such as the Korea Capital Market Institute and the Korea Labor Institute, contributing to evidence-based policy development in environmental, labor, and economic sectors. Through his expanding body of research, Dr. Kim continues to shape discussions on just transition, climate-risk adaptation, sustainable energy planning, and equitable climate-finance allocation, establishing himself as a rising scholar dedicated to bridging empirical analysis with practical environmental policy solutions.

Profiles: Scopus | Google Scholar 

Featured Publication

Kim, J., Hong, J. H., & Kim, J. (2025). Energy consumption forecasting of neighborhood living facilities: A panel regression approach.

Bahri Baran Kocak | Artificial Intelligence in Statistics | Big Data Analytics Award

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Dr. Bahri Baran Kocak | Artificial Intelligence in Statistics | Big Data Analytics Award

Dicle University | Turkey

Dr. Bahri Baran Kocak is a dedicated scholar in aviation management, serving as an Assistant Professor at Dicle University’s School of Civil Aviation, where he integrates teaching, research, and academic service with a strong interdisciplinary outlook. Holding a Ph.D. in Aviation Management from Anadolu University, his doctoral research focused on perceptual mapping of Turkish airline services on Twitter within the framework of positioning theory, reflecting his deep interest in digital consumer behavior and aviation analytics. His expertise spans AI techniques, multidimensional and time-series analysis, social media analytics, consumer behavior, psycholinguistics, and structural equation modeling, enabling him to produce research that blends methodological precision with practical relevance for the aviation industry. He has authored impactful journal articles on topics such as airline consumer engagement across platforms like Instagram and YouTube, consumer–brand relationships, web search behavior in airline markets, and deep learning-based airport demand forecasting using Google Trends. His book chapters further demonstrate his breadth, including studies on emoji engagement in airline social media communication and the role of big data in aviation innovation. Across his scholarly contributions, Kocak has consistently examined the intersection of digital behavior, marketing analytics, and aviation management, contributing valuable insights to both academic and industry audiences. According to available academic indexing sources, he has produced 3 documents, accumulated approximately 26 citations, and holds an h-index of 3, reflecting growing recognition of his work within the research community. His academic profile demonstrates a clear commitment to advancing knowledge in aviation management, digital analytics, and consumer engagement, supported by a strong analytical skill set and an expanding body of scholarly output.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Kocak, B. B. (2025). Utilizing online-centered big data in the airline industry. In Book chapter.

Koçak, B. B. (2025). How to use GenAI as a rater in marketing: A comprehensive GenAI-based content coding framework. Yönetim Bilimleri Dergisi.

KOÇAK, B. B. (2023). Comparison of artificial intelligence techniques for the UK air passenger short-term demand forecasting: A destination insight study. Journal of Aviation.

Koçak, B. B. (2021). Fly “With us”! Impact of consumer–brand relationship on consumer engagement: An empirical investigation on Turkish airline Instagram pages. Tüketici ve Tüketim Araştırmaları Dergisi, 13(2), 253–282.

Koçak, B. B. (2022). More than a thousand words!: Emoji engagement on Turkish airline Instagram pages. In Cases on developing effective research plans for communications and media studies.

Kocak, B. B., & Atalik, O. (2019). Perceptual maps of Turkish airline services for different periods using supervised machine learning approach and multidimensional scaling. International Journal of Sustainable Aviation.

Ki Ryong Kwon | Artificial Intelligence in Statistics | Best Faculty Award

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Prof. Ki Ryong Kwon | Artificial Intelligence in Statistics | Best Faculty Award

Pukyong National University | South Korea

Professor Ki-Ryong Kwon is an eminent and highly respected scholar in electronics engineering, artificial intelligence, and computer science, serving as a leading Professor in the Division of Computer Engineering and AI at Pukyong National University, South Korea. he pursued his academic journey at Kyungpook National University, where he completed his bachelor’s, master’s, and doctoral degrees in Electronics Engineering, later advancing his research expertise through a prestigious postdoctoral fellowship at the University of Minnesota under the mentorship of Prof. Ahmed H. Tewfik, followed by a visiting scholar appointment at Colorado State University that further broadened his international academic exposure. Throughout his long-standing academic career, Professor Kwon has demonstrated exceptional leadership by serving as Dean of the College of Engineering, Vice-Dean of Engineering, Director of the Artificial Intelligence Lab, Director of the Center for Start-up Foundation, Director of the Center of IP Transfer, and Vice-Director of Industry-University Foundation Cooperation, contributing extensively to academic development, research infrastructure advancement, and student innovation ecosystems. Beyond the university environment, he has played influential strategic roles as Chairman of the Global Fintech Industry Promotion Center, Vice-Chairman of the Korea Cloud Association, Vice-Chairman of the Busan Federation of Service Industry, and Chair of the 4th Industrial Revolution Leadership Promotion Team for Busan City, where he has been instrumental in guiding regional and national initiatives in AI-driven transformation, digital economy growth, and emerging technology integration. His contributions to the global research community include major leadership roles in IEEE, the Korea Multimedia Society, the Korea Information Processing Society, and multiple international conferences where he has served as General Chair, Industrial Chair, Program Chair, and Organizing Chair. His research encompasses deep learning, digital watermarking, image forensics, signal processing, marine AI applications, smart digital-twin systems, cybersecurity, and intelligent multi-agent architectures. With approximately 118 published research documents, around 1,309 citations, and an estimated h-index in the mid-20s, he maintains a strong and influential academic footprint. Over his career, he has been honored with numerous Best Paper Awards, national recognitions, institutional leadership awards, and international distinctions that reflect his outstanding dedication to research excellence, innovation leadership, and the advancement of technology-driven societal development.

Profile: Scopus

Abuchi Elebo | Design of Experiments (DOE) | Editorial Board Member

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Dr. Abuchi Elebo | Design of Experiments (DOE) | Editorial Board Member

Ahmadu Bello University | Nigeria

Dr. Abuchi Elebo is a highly driven analytical chemist and interdisciplinary researcher whose work bridges environmental science, materials chemistry, and data-driven modeling. Born on 24 July 1994 in Kaduna State, Nigeria, he completed his B.Sc. in Industrial Chemistry and subsequently earned his M.Sc. and Ph.D. in Analytical Chemistry from Ahmadu Bello University, Zaria. Over the years, he has amassed significant experience across academia and education, serving as a part-time lecturer at ABU, a senior education officer with the Kaduna State Universal Basic Education Board, and a laboratory instructor and research assistant in high-impact laboratories. His technical expertise spans chromatography (HPLC, GC, TLC), spectroscopic techniques (IR, NMR, UV-Vis, AAS, ICP-MS), and mass spectrometry, which he couples with modern statistical methods such as response-surface methodology and artificial intelligence to design and validate experimental protocols. He has published on corrosion inhibition using expired drugs, green nanoparticle synthesis, and biosorption from plant materials, among other topics, in high-quality peer-reviewed journals. His scientific contributions are quantified by an h-index of 3, demonstrating that at least that many of his papers have each received a comparable number of citations-an accepted metric of both productivity and impact in academia. Dr. Elebo is a member of the Chemical Society of Nigeria, the American Society for Microbiology, and holds professional teaching certification from the Teacher Registration Council of Nigeria. Alongside his research, he is passionate about teaching, mentorship, and community service, with prior voluntary engagement in secondary education during his NYSC service. His growing body of work reflects a consistent commitment to scientific excellence, capacity building, and sustainable solutions to environmental pollution leveraging both experimental and computational strategies..

Profiles: Scopus

Featured Publications

Elebo, A., & Abubakar, S. (n.d.). Elucidating the efficacy of vanillin-tryptophan Schiff base ligand for mitigating carbon steel corrosion: Weight loss, electrochemical, soft-computing, DFT, and MD-simulation.