Ilya Levin | Artificial Intelligence | Research Excellence Award

Prof. Ilya Levin | Artificial Intelligence | Research Excellence Award

Professor | Holon Institute of Technology | Israel

Prof. Ilya Levin is a researcher at Holon Institute of Technology, specializing in artificial intelligence, machine learning, and educational technology. His research focuses on computational thinking, neural networks, and AI-driven learning systems. He has strong expertise in algorithm design and interdisciplinary innovation. His contributions are recognized through impactful publications and academic work. According to Scopus, he has 552 citations, 88 documents, and an h-index of 13, reflecting his significant impact in AI and education research.

 

Citation Metrics (Scopus)

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Featured Publications


Culture and Society in the Digital Age

– Information, 2021 (Citations: 275)


Massive open online courses – the modern concept in education and learning

– Vestnik Tomskogo State University, 2014 (Citations: 133)


Teaching machine learning in elementary school

– International Journal of Child-Computer Interaction, 2022 (Citations: 82)

 

Muhammad Furqan Zia | Artificial Intelligence | Young Scientist Award

Mr. Muhammad Furqan Zia | Artificial Intelligence | Young Scientist Award

Researcher | Université du Québec à Trois-Rivières | Canada

Mr. Muhammad Furqan Zia is an emerging researcher at Université du Québec à Trois-Rivières, specializing in artificial intelligence and semantic communication. His research focuses on explainable AI and intelligent communication systems, addressing transparency and efficiency challenges. He has skills in AI modeling, data analysis, and system design, contributing to scholarly publications. His work is gaining recognition in the research community. According to Scopus, he has 5 citations, 4 documents, and an h-index of 2, reflecting his growing academic impact.

 

Citation Metrics (Scopus)

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5

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View Scopus Profile View ORCID Profile View Google Scholar Profile

Featured Publications


An Advanced Non-Orthogonal Multiple Access Security Technique for Future Wireless Communication Networks

– RS Open Journal on Innovative Communication Technologies, 2020 (Citations: 27)

 

Lei Yao | Artificial Intelligence | Research Excellence Award

Mr. Lei Yao | Artificial Intelligence | Research Excellence Award

Ph.D. Candidate | Jilin University | China

Mr. Lei Yao is an advancing researcher whose work lies at the intersection of artificial intelligence, biomedical engineering, and intelligent monitoring systems. His research focuses on designing innovative AI-driven solutions for healthcare diagnostics, cognitive evaluation, physiological signal analysis, and smart livestock management. Through the integration of deep learning, multi-task learning, and generative models, he aims to improve the accuracy, efficiency, and scalability of real-world intelligent sensing applications.A core area of Mr. Yao’s work is biomedical signal processing, especially electrocardiogram (ECG) analysis. His contribution to MMS-Net, a multi-task learning framework, provides a transformative method for reconstructing full 12-lead ECG signals using only 3-lead inputs while simultaneously performing disease classification. This technology enhances diagnostic capabilities in low-resource settings and supports more accessible cardiology screening.Mr. Yao also investigates synthetic data generation using modern generative adversarial networks. His work on SGECG, a StarGAN-based system for ECG generation and augmentation, aids in overcoming data scarcity, a major limitation in machine-learning-based healthcare research.Beyond biomedical applications, Mr. Yao significantly contributes to smart agriculture and automaed animal health monitoring. His publication SideCow-VSS introduces a comprehensive video semantic segmentation dataset designed for intelligent dairy cow health assessment in smart ranch environments—an important advancement for precision livestock farming.His interdisciplinary research further includes cognitive assessment, demonstrated by MLCDT, a fine-grained multi-task learning model that enhances automated analysis of the clock drawing test, an essential tool in early detection of cognitive impairment.Overall, Mr. Lei Yao’s research integrates AI, signal processing, and intelligent sensing to create impactful solutions for healthcare, cognitive diagnostics, and smart agricultural systems.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

  1. Yao, L., Garmash, O., Bianchi, F., Zheng, J., Yan, C., Kontkanen, J., Junninen, H., … (2018). Atmospheric new particle formation from sulfuric acid and amines in a Chinese megacity. Science, 361(6399), 278–281.
    Citations: 611

  2. Xiao, S., Wang, M. Y., Yao, L., Kulmala, M., Zhou, B., Yang, X., Chen, J. M., Wang, D. F., … (2015). Strong atmospheric new particle formation in winter in urban Shanghai, China. Atmospheric Chemistry and Physics, 15(4), 1769–1781.
    Citations: 176

  3. Zheng, J., Ma, Y., Chen, M., Zhang, Q., Wang, L., Khalizov, A. F., Yao, L., Wang, Z., … (2015). Measurement of atmospheric amines and ammonia using the high-resolution time-of-flight chemical ionization mass spectrometry. Atmospheric Environment, 102, 249–259.
    Citations: 165

  4. Yan, C., Nie, W., Äijälä, M., Rissanen, M. P., Canagaratna, M. R., Massoli, P., … Yao, L., … (2016). Source characterization of highly oxidized multifunctional compounds in a boreal forest environment using positive matrix factorization. Atmospheric Chemistry and Physics, 16(19), 12,715–12,731.
    Citations: 164

  5. Wang, X., Hayeck, N., Brüggemann, M., Yao, L., Chen, H., Zhang, C., Emmelin, C., … (2017). Chemical characteristics of organic aerosols in Shanghai: A study by ultrahigh-performance liquid chromatography coupled with Orbitrap mass spectrometry. Journal of Geophysical Research: Atmospheres, 122(21), 11,703–11,722.
    Citations: 157

Mr. Lei Yao’s research significantly advances atmospheric chemistry by uncovering the mechanisms of new particle formation, characterizing organic aerosols, and improving high-resolution chemical detection technologies. His contributions enhance scientific understanding of air pollution sources, support policymakers in designing effective climate and air-quality interventions, and strengthen industrial environmental monitoring frameworks. Through high-impact studies published in globally respected journals, his work drives innovation in atmospheric measurement, fosters healthier urban environments, and informs global strategies for mitigating particulate pollution and its effects on human and environmental health.