Abdallah Al-Zubi | Data Science | Best Researcher Award

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Mr. Abdallah Al-Zubi | Data Science | Best Researcher Award

Abdallah Al-Zubi at University Of Nebraska Lincoln | United States

Mr. Abdallah Alzubi is an accomplished AI engineer and researcher with over eight years of experience in machine learning, data science, and software engineering. Currently pursuing a Ph.D. in AI Engineering at the University of Nebraska-Lincoln, his research focuses on developing MEMS-based analog computing architectures for real-time signal processing, human activity recognition, and structural health monitoring. His contributions span both academic research and industry innovation, including the establishment of the AI department at John Wiley and Sons in Jordan, as well as collaborations on cutting-edge projects funded by the Intelligence Advanced Research Projects Activity (IARPA). He is recognized for bridging theoretical AI research with impactful business and healthcare applications.

Professional Profile:

Education:ย 

Mr. Abdallah Alzubi is a proficient AI engineer and researcher specializing in data science, machine learning, and software engineering, with extensive academic and professional experience. He is currently pursuing a Ph.D. in AI Engineering at the University of Nebraska-Lincoln, USA, focusing on MEMS-based Analog Computing. He also holds an M.S. in AI Engineering from the same institution, where he completed his thesis on Gradient-Based Multi-Time-Scale Trainable Continuous Time Recurrent Networks, as well as an M.S. in Data Science from Princess Sumaya University for Technology, Jordan, with research on Pathfinder Optimization clustering techniques. His academic journey began with a B.S. in Computer Engineering from Jordan University of Science & Technology, where he developed an automated Arabic optical character recognition system.

Experience:

Mr. Alzubi serves as a Research Assistant at the University of Nebraska-Lincoln, where he develops MEMS-based hardware simulations for structural health monitoring and signal denoising using TensorFlow and Keras, while also designing AI models for seismic structural assessments and human activity detection. Previously, as an AI Engineer at John Wiley & Sons (NJ), he pioneered the establishment of their AI Department in Jordan, enhancing speech recognition systems, building big data-driven article recommendation engines, and improving sentiment analysis accuracy. Earlier in his career, he worked as a Software Engineer at Globitel, Jordan, where he created mobile proximity matching services for taxi dispatching and developed secure authentication solutions (Mobile Connect) for telecom clients. As a Solution Developer at ILS Saudi Co. Ltd, he implemented ERP systems to optimize operations across manufacturing, HR, and finance. At SEDCO, Jordan, he further contributed by enhancing customer queuing management systemsโ€”reducing communication latency sevenfoldโ€”and integrating smart advertising and multilingual functionalities.

Research Interest:

His research interests span across MEMS-based analog computing for low-power AI applications, machine learning for structural health monitoring and earthquake response, human activity recognition in healthcare, natural language processing for speech recognition and sentiment analysis, and big data analytics for real-time AI system design.

Publications Top Noted:

  • Automated System for Arabic Optical Character Recognition with Lookup Dictionary
    Year: 2012
    Citations: 21

  • Automated System for Arabic Optical Character Recognition
    Year: 2012
    Citations: 9

  • G-CTRNN: A Trainable Low-Power Continuous-Time Neural Network for Human Activity Recognition in Healthcare Applications
    Year: 2025

  • A Novel MEMS Reservoir Computing Approach for Classifying Human Acceleration Activity Signal
    Year: 2025

  • Distributed and Automated Machine Learning in Big Data Stream Analytics
    Year: 2019
    Citations: 1

Conclusion:

Mr. Abdallah Al-Zubi exemplifies the qualities of a forward-thinking researcher in AI and Data Science. His innovative work on MEMS-based analog computing, coupled with contributions to structural health monitoring, human activity recognition, and big data-driven AI, positions him as a global leader in next-generation artificial intelligence research. His unique blend of academic rigor, industry leadership, and impactful real-world applications makes him a highly deserving candidate for the Best Researcher Award. With his ongoing contributions, he is poised to play a critical role in shaping the future of low-power AI systems and intelligent infrastructure solutions.

Hany Mahbuby | Data Science | Best Researcher Award

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Dr. Hany Mahbuby | Data Science | Best Researcher Award

Assistant Professor at Shahid Beheshti University, Iran

Dr. Hany Mahbuby ๐Ÿ‡ฎ๐Ÿ‡ท is an Assistant Professor at the Faculty of Civil, Water, and Environmental Engineering, Shahid Beheshti University, Iran. ๐ŸŽ“ With a PhD in Geodesy (2022), he excels in data assimilation, gravity field modeling, ionosphere research, groundwater estimation, and GNSS remote sensing. ๐ŸŒ His innovative approach merges GRACE and GLDAS data with groundwater well observations to create a high-resolution groundwater storage anomaly grid, addressing critical water resource challenges. ๐Ÿ’ง His research blends numerical modeling, optimization, and spectral analysis, underscoring his technical prowess. ๐Ÿ“Š Despite a growing academic profile, increased international visibility, competitive research funding, and broader community engagement could further enhance his impact. ๐ŸŒ Overall, Dr. Mahbuby stands out as a promising researcher whose expertise and dedication position him well for future recognition and contributions in his field. ๐ŸŒŸ

Professional Profileย 

๐ŸŽ“ Education

Dr. Hany Mahbuby ๐Ÿ‡ฎ๐Ÿ‡ท earned his BSc in Geomatics and Surveying Engineering from Amirkabir University of Technology (Tehran Polytechnic) in 2007, laying a strong technical foundation for his academic journey. ๐Ÿ“ He pursued an MSc in Geodesy at the University of Tehran (2016), deepening his expertise in spatial data science and geospatial modeling. ๐Ÿ“Š His academic trajectory culminated in a PhD in Geodesy from K. N. Toosi University of Technology (2022), where he advanced his research in numerical modeling, data assimilation, and gravity field analysis. ๐Ÿ›ฐ๏ธ His interdisciplinary education equips him with robust knowledge to tackle complex challenges in environmental remote sensing, groundwater estimation, and GNSS applications. ๐ŸŒ His academic path reflects a dedication to excellence and a commitment to addressing real-world environmental issues through science and innovation. ๐Ÿ’ก

๐Ÿ›๏ธ Professional Experience

Dr. Hany Mahbuby ๐Ÿ‡ฎ๐Ÿ‡ท brings a progressive professional journey marked by academic excellence and teaching commitment. ๐Ÿ“š He began his academic career as a Lecturer from September 2017 to May 2023 at Shahid Beheshti University, where he contributed to foundational courses in geomatics and geodesy while mentoring students. ๐Ÿ‘จโ€๐Ÿซ In July 2023, he advanced to Assistant Professor, demonstrating recognition of his contributions and readiness for leadership roles. ๐Ÿš€ His work involves integrating remote sensing, groundwater monitoring, and numerical modeling, aligning with cutting-edge environmental and engineering challenges. ๐Ÿ›ฐ๏ธ His consistent teaching experience, combined with his research leadership, positions him as a valuable academic asset. ๐Ÿ“ˆ His career reflects a commitment to both education and impactful research, making him a well-rounded scholar in his field. ๐ŸŒŸ

๐Ÿ”ฌ Research Interest

Dr. Hany Mahbuby ๐Ÿ‡ฎ๐Ÿ‡ท has diverse and innovative research interests, rooted in addressing critical environmental and engineering challenges. ๐ŸŒ He focuses on data assimilation, merging satellite-based and ground-based observations to enhance groundwater modeling and environmental monitoring. ๐Ÿ’ง His expertise extends to gravity field modeling and ionosphere studies, applying GNSS remote sensing to understand Earth system dynamics. ๐Ÿ›ฐ๏ธ He is particularly passionate about integrating GRACE and GLDAS data with observed groundwater level anomalies to create fine-scale groundwater storage models using statistical and spectral analysis. ๐Ÿ“Š His interests also include numerical optimization, ensuring that computational models are both efficient and accurate. โš™๏ธ This interdisciplinary focus on environmental remote sensing and numerical modeling underscores his drive to produce impactful research that bridges theory and practical applications. ๐Ÿ”—

๐Ÿ… Award and Honor

While Dr. Hany Mahbuby ๐Ÿ‡ฎ๐Ÿ‡ท demonstrates strong research achievements and a progressive academic career, his current record does not yet highlight specific awards and honors from national or international bodies. ๐ŸŒ Nonetheless, his innovative contributions to data assimilation and groundwater storage modeling stand as testament to his research impact and technical prowess. ๐Ÿ›ฐ๏ธ His dedication to interdisciplinary research, commitment to mentoring, and technical expertise make him a strong candidate for future awards and recognitions. ๐Ÿ† By expanding his research collaborations, increasing high-impact publications, and engaging in international scientific communities, Dr. Mahbuby is well-positioned to earn accolades that celebrate his contributions to environmental engineering and geodesy. ๐ŸŒŸ With continued growth and strategic engagement, his promising career trajectory is likely to attract honors and recognition in the near future. ๐Ÿ’ช

๐Ÿ› ๏ธ Research Skill

Dr. Hany Mahbuby ๐Ÿ‡ฎ๐Ÿ‡ท possesses a robust skill set that enables him to tackle complex challenges in environmental remote sensing and numerical modeling. ๐Ÿ“Š His expertise in data assimilation allows him to integrate satellite-based and ground-based observations for accurate groundwater modeling, essential for sustainable water management. ๐Ÿ’ง He excels in gravity field analysis and ionosphere modeling, applying GNSS remote sensing techniques to enhance understanding of Earthโ€™s geophysical processes. ๐Ÿ›ฐ๏ธ Proficient in numerical optimization, he designs efficient and precise computational models that bridge theory and real-world applications. โš™๏ธ Additionally, his skills in statistical analysis and spectral analysis ensure that his models are both reliable and innovative. ๐Ÿ“ˆ This interdisciplinary skill set empowers him to contribute significantly to hydrology, geodesy, and environmental engineering, making him a valuable researcher. ๐ŸŒŸ

Publications Top Note ๐Ÿ“

1. Assimilation of in-situ groundwater level data into the obtained groundwater storage from GRACE and GLDAS for spatial downscaling
Authors: Hany Mahbuby, Mehdi Eshagh
Year: 2025
Source: Journal of Hydrology

2. Investigating the prediction ability of the ionospheric continuity equation during the geomagnetic storm on May 8, 2016
Authors: Hany Mahbuby, Yazdan Amerian
Year: 2025
Source: Journal of Geodetic Science

3. Regional ionospheric electron density modeling by assimilation of GPS-derived TEC into IRI-provided grids on May 8, 2016
Authors: Hany Mahbuby, Yazdan Amerian
Year: 2023
Source: Advances in Space Research

4. Improving the performance of time-varying spherical radial basis functions in regional VTEC modeling with sparse data
Authors: Hany Mahbuby, Yazdan Amerian
Year: 2022
Source: Advances in Space Research

5. Application of the nonlinear optimisation in regional gravity field modelling using spherical radial base functions
Authors: Hany Mahbuby, Yazdan Amerian, Amirhossein Nikoofard, Mehdi Eshagh
Year: 2021
Source: Studia Geophysica et Geodaetica

6. Regional Assimilation of GPS-Derived TEC into GIMs
Authors: Hany Mahbuby, Yazdan Amerian
Year: 2021
Source: Pure and Applied Geophysics

7. Total electron content modeling in terms of spherical radial basis functions over Iran
Authors: Sh. Khoshgovari, Y. Amerian, H. Mahbuby
Year: 2020
Source: Journal of the Earth and Space Physics

8. Local gravity field modeling using spherical radial basis functions and a genetic algorithm
Authors: Hany Mahbuby, Abdolreza Safari, Ismael Foroughi
Year: 2017
Source: Comptes Rendus Geoscience

Conclusion

In conclusion, Dr. Hany Mahbuby ๐Ÿ‡ฎ๐Ÿ‡ท stands out as a dedicated and innovative researcher whose expertise in geodesy, data assimilation, and groundwater modeling positions him to make impactful contributions to environmental engineering. ๐ŸŒ His educational background, professional experience, and research skills reflect a commitment to advancing scientific knowledge and solving real-world challenges. ๐Ÿ’ก While opportunities remain to expand his international recognition, secure competitive grants, and deepen community engagement, his trajectory is promising. ๐Ÿš€ With continued effort toward high-impact publications, global collaborations, and societal impact, Dr. Mahbuby is poised to become a leading figure in his field. ๐Ÿ† His dedication and technical prowess make him a deserving candidate for recognition and support as an emerging leader in environmental remote sensing and numerical modeling. ๐ŸŒŸ

Dr. Haochen Li | Machine Learning | Best Researcher Award

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Dr. Haochen Li | Machine Learning | Best Researcher Award

Dr. Haochen Li, Taiyuan University of Science and Technology, China

Dr. Haochen Li is an accomplished researcher specializing in electrical engineering, with a strong emphasis on power electronics, power systems, and data-driven optimization techniques. His academic journey has been marked by significant contributions to the development of intelligent power flow control and renewable energy integration. His research focuses on applying advanced machine learning techniques, such as graph-based neural networks, to improve power grid stability, reliability, and efficiency. With multiple high-impact publications in top-tier journals, Haochen Li has made notable strides in tackling challenges in microgrid systems, power flow optimization, and spatiotemporal power predictions. His innovative approaches have garnered recognition from the research community, positioning him as a leading figure in modern electrical power system advancements.

Profile:

Orcid

Scopus

Education:

Dr.ย  Haochen Li has pursued a rigorous academic path, building expertise in electrical engineering and control systems. He completed his undergraduate studies in Electrical Engineering and Automation, followed by a masterโ€™s degree in Power Electronics and Electric Drives, where he specialized in microgrid system control technologies. Currently, he is pursuing a Ph.D. in Control Engineering, focusing on the application of data mining techniques in power systems. His educational background has provided him with a strong foundation in both theoretical and applied research, enabling him to develop innovative solutions for optimizing power system performance.

Experience:

Dr. Haochen Li has been actively involved in academia and research, contributing to the advancement of electrical and control engineering. He is currently associated with the Taiyuan University of Science and Technology, where he engages in cutting-edge research on power flow optimization and renewable energy integration. His experience spans multiple collaborative projects, where he has worked alongside leading experts to develop intelligent algorithms for power system management. Through his academic endeavors, he has gained expertise in modeling and simulation of power systems, integrating artificial intelligence techniques into energy management, and analyzing grid uncertainties for enhanced performance.

Research Interests:

Dr. Haochen Liโ€™s research interests revolve around the intersection of power systems and data science, with a particular focus on:

  • Power Flow Optimization โšก โ€“ Developing intelligent algorithms to enhance the efficiency of electricity transmission.

  • Renewable Energy Integration ๐ŸŒ โ€“ Designing predictive models for wind and solar energy systems.

  • Graph Neural Networks in Power Systems ๐Ÿค– โ€“ Utilizing AI-driven techniques for improving grid stability and reliability.

  • Spatiotemporal Data Analysis โณ โ€“ Leveraging big data approaches to enhance power grid forecasting.

  • Microgrid System Control ๐Ÿ”‹ โ€“ Implementing advanced control strategies for distributed energy resources.

Awards:

Dr. Haochen Liโ€™s contributions to power system research have been recognized through various academic and research accolades. His outstanding work in data-driven optimization for power flow calculations has been acknowledged by prestigious institutions. Additionally, his research on renewable energy forecasting has earned him recognition in international conferences and journal publications. His ability to bridge theoretical research with practical applications has positioned him as a key innovator in the field.

Publications:

  • Physics-Guided Chebyshev Graph Convolution Network for Optimal Power Flow

    • Publication Year: 2025

  • Graph Attention Convolution Network for Power Flow Calculation Considering Grid Uncertainty

    • Publication Year: 2025

  • Joint Missing Power Data Recovery Based on Spatiotemporal Correlation of Multiple Wind Farms

    • Publication Year: 2024

  • Spatiotemporal Coupling Calculation-Based Short-Term Wind Farm Cluster Power Prediction

    • Publication Year: 2023

Conclusion:

Dr. Haochen Li is a highly dedicated researcher whose work has significantly contributed to the field of power system engineering. His expertise in artificial intelligence, power flow optimization, and renewable energy forecasting has positioned him as a thought leader in the integration of smart grid technologies. With a strong publication record, ongoing innovative research, and a commitment to enhancing power system reliability, he is a deserving candidate for the Best Researcher Award. His ability to merge theoretical advancements with real-world applications showcases his potential to lead future innovations in intelligent power systems.

Dr. XInbo MA | Machine Learning | Best Researcher Award

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Dr. XInbo MA | Machine Learning | Best Researcher Award

Dr. XInbo MA, Northeastern University, China

โ€‹

Ma Xinbo is a prominent figure in the field of geotechnical engineering, currently serving as an Associate Professor at the College of Resources and Civil Engineering, Northeastern University, Shenyang, China. His scholarly pursuits focus on the intelligent detection of internal fractures in mine rock masses, utilizing advanced imaging techniques to enhance the safety and efficiency of mining operations.

Profile:

Scopusโ€‹

Education:

Professor Ma earned his Ph.D. in Geotechnical Engineering from Northeastern University, Shenyang, China, in 2010. His doctoral research laid the foundation for his ongoing commitment to advancing mining safety through technological innovation.โ€‹

Experience:

Throughout his career, Professor Ma has held several academic and research positions. Prior to his current role, he served as a Lecturer and then as an Associate Professor at the same institution. His professional journey reflects a steadfast dedication to both teaching and research in geotechnical engineering.โ€‹

Research Interests:

Professor Ma’s research interests are centered around the application of intelligent detection methods in mining engineering. A notable area of his work includes the development of techniques for identifying internal fractures in mine rock masses using borehole camera images. This research aims to improve the understanding of rock mass integrity, which is crucial for the safety and sustainability of mining operations.โ€‹

Publications:

Professor Ma Xinbo has contributed to several scholarly publications, including:โ€‹

  1. “Abcb1 is Involved in the Efflux of Trivalent Inorganic Arsenic from Brain Microvascular Endothelial Cells” by Man Lv, Ziqiao Guan, Jia Cui, Xinbo Ma, Kunyu Zhang, Xinhua Shao, Meichen Zhang, Yanhui Gao, Yanmei Yang, Xiaona Liu. This study explores the role of Abcb1 in mediating arsenic efflux in brain microvascular endothelial cells. Published in 2024. โ€‹
  2. “Liberal Arts in Chinaโ€™s Modern Universities: Lessons from the Great Catholic Educator and Statesman, Ma Xiangbo” by You Guo Jiang. This article discusses the contributions of Ma Xiangbo to liberal arts education in modern China. Published in Frontiers of Education in China, Volume 7, Issue 3, in 2012. โ€‹
  3. “Catholic Intellectuals in Modern China and Their Bible Translation: Li Wenyu and Ma Xiangbo” by Xiaochun Hong. This paper examines the roles of Li Wenyu and Ma Xiangbo in Bible translation efforts in modern China. Published in the Journal of the Royal Asiatic Society, Volume 33, Issue 2, in 2023.

Awards and Recognitions:

Professor Ma’s excellence in research and academia has been acknowledged through various awards and honors. In 2016, he was honored as an Outstanding Graduate of Dalian Maritime University, reflecting his early commitment to academic excellence. He also received the National Scholarship, awarded to the top 0.2% of students by China’s Ministry of Education, in both 2013 and 2016. These accolades highlight his dedication to his field and his institution.โ€‹

Conclusion:

Professor Ma Xinbo’s academic journey and research endeavors underscore his pivotal role in advancing geotechnical engineering, particularly in the realm of mining safety. His innovative approaches to fracture detection and his commitment to scholarly excellence make him a valuable asset to the academic community and a strong candidate for the “Best Researcher Award.”

Prof. Pinghui Wu | Technology | Best Researcher Award

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Prof. Pinghui Wu | Technology | Best Researcher Award

Prof. Pinghui Wu | Technology – Division Chief of Scientific Research at Quanzhou Normal University, China

Prof. Wu Pinghui, a distinguished academic from Quanzhou Normal University, has made remarkable contributions to the fields of advanced optics, materials science, and thermal engineering. With a robust portfolio of research, Wuโ€™s work reflects a passion for innovation and scientific exploration, particularly in areas like metamaterials and solar energy technologies. Known for a collaborative approach, Wu has worked with numerous international researchers, driving forward impactful studies that influence both theoretical and applied sciences.

Profile:

Orcid | Scopus | Google Scholar

Education:

Prof. Wu Pinghui pursued advanced studies in materials science and optical engineering, laying a strong foundation for a career marked by academic excellence and groundbreaking research. The educational journey involved rigorous training in both theoretical principles and practical applications, fostering expertise in cutting-edge technologies. This academic background has been pivotal in shaping Wuโ€™s approach to complex scientific challenges and interdisciplinary collaborations. ๐ŸŽ“

Experience:

With years of dedicated academic service, Wu has held prominent research and teaching positions at Quanzhou Normal University. This experience includes mentoring graduate students, leading research projects, and contributing to curriculum development in scientific disciplines. Wuโ€™s role extends beyond academia, with active participation in international conferences and collaborative research initiatives that span across institutions and countries. ๐ŸŒ

Research Interests:

Wuโ€™s research interests are diverse, encompassing optical materials, thermal energy systems, and metamaterial-based devices. Key areas include the development of ultra-broadband solar absorbers, terahertz smart devices, and advanced optical reinforcement materials. Wuโ€™s work is characterized by a focus on sustainability, energy efficiency, and the application of novel materials to solve real-world technological problems. ๐Ÿ”ฌ

Awards:

While specific awards are not detailed, Wuโ€™s academic achievements, high citation count, and influential publications underscore a career recognized for excellence. The impact of Wuโ€™s research is reflected in the widespread adoption of scientific findings and contributions to the academic community. ๐Ÿ†

Selected Publications:

  1. “Highly Localized Linear Array of Optical Rings with Multiple Tunable Degrees of Freedom” (2025) – Optics Communications โœจ
  2. “Highly Efficient Color Tuning of Lithium Niobate Nanostructures on Flexible Substrate” (2025) – Materials ๐ŸŒˆ
  3. “Ultra-Broadband Solar Absorber and Near-Perfect Thermal Emitter Based on Columnar Titanium Micro-Structure” (2025) – Applied Thermal Engineering โ˜€๏ธ
  4. “Bi-Directional Metamaterial Perfect Absorber Based on Gold Grating and TiOโ‚‚-InAs Normal Hexagonal Pattern Film” (2025) – Solar Energy Materials and Solar Cells โšก
  5. “Thermal Radiation Analysis of a Broadband Solar Energy-Capturing Absorber Using Ti and GaAs” (2025) – Dalton Transactions ๐ŸŒž
  6. “Ultra-Broadband Absorber and Near-Perfect Thermal Emitter Based on Multi-Layered Grating Structure Design” (2025) – Energy ๐Ÿ”ฅ
  7. “Terahertz Smart Devices Based on Phase Change Material VOโ‚‚ and Metamaterial Graphene” (2025) – Optics and Laser Technology ๐ŸŒ

Cited By: Over 6,610 citations, reflecting the widespread influence and recognition of these works. ๐Ÿ“š

Conclusion:

Prof. Wu Pinghuiโ€™s academic journey exemplifies a commitment to scientific excellence and innovation. The combination of extensive research output, impactful publications, and interdisciplinary collaborations highlights a career dedicated to advancing knowledge and technology. Wuโ€™s contributions not only enrich the academic community but also inspire future generations of researchers. This nomination for the Best Researcher Award is a testament to the profound impact Wu has made in the scientific world. ๐ŸŒŸ

Mr. Mohammad Mahdi Badami | Data Analysis | Young Scientist Award

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Mr. Mohammad Mahdi Badami | Data Analysis | Young Scientist Award

Mr. Mohammad Mahdi Badami | University of Southern California | United States

Mehdi Badami is a dedicated Ph.D. candidate in Environmental Engineering at the University of Southern California (USC) under Prof. Constantinos Sioutas. His expertise lies in air quality improvement, with hands-on experience in air pollution monitoring using advanced instrumentation such as SMPS-CPC, OPS, and Aethalometer 51. He specializes in data-driven environmental assessments, employing Python for pollution source apportionment and emission trend analysis. His research contributes to community-centric environmental policies and sustainable air quality solutions. Passionate about environmental justice, he aims to bridge scientific research with real-world policy implementation. ๐ŸŒฑ๐Ÿ”ฌ

Professional Profile:

Google Scholar

Suitability for the Young Scientist Award

Mehdi Badami is a strong candidate for the Young Scientist Award due to his significant contributions to environmental engineering, particularly in air quality improvement. As a Ph.D. candidate at the University of Southern California (USC), his research focuses on air pollution monitoring and data-driven environmental assessments. His expertise in advanced instrumentation (e.g., SMPS-CPC, OPS, Aethalometer 51) and Python-based pollution source apportionment makes him a valuable asset to the field.

Education & Experience ๐Ÿข๐ŸŽ“

  • Ph.D. Candidate in Environmental Engineering (2022-Present) โ€“ USC, Los Angeles, USA ๐Ÿ‡บ๐Ÿ‡ธ

    • GPA: 3.95/4
    • Advisor: Prof. Constantinos Sioutas

  • M.Sc. in Mechanical Engineering (Fluid Mechanics) (2017-2020) โ€“ University of Tehran, Iran ๐Ÿ‡ฎ๐Ÿ‡ท

    • GPA: 3.77/4
    • Supervisors: Dr. Alireza Riasi, Prof. Kayvan Sadeghy

  • B.Sc. in Mechanical Engineering (2012-2016) โ€“ K. N. Toosi University of Technology, Iran ๐Ÿ‡ฎ๐Ÿ‡ท

  • Research Assistant โ€“ USC Aerosol Lab (2023โ€“Present) ๐Ÿญ๐ŸŒซ๏ธ

    • Conducted air pollution measurements using state-of-the-art monitoring systems
    • Developed Python programs for data automation and pollution trend analysis
    • Led collaborations with institutions like Harvard, UCLA, and Dresden University
    • Mentored Ph.D. students on environmental research projects

  • Research Assistant โ€“ Hydro-kinetic Energy Lab, University of Tehran (2017โ€“2022) ๐Ÿ”ฌ๐Ÿ’ง

    • Investigated fluid mechanics phenomena related to blood hammer effects in arteries

  • Teaching Assistant โ€“ USC & University of Tehran (2018โ€“2024) ๐Ÿ“š๐Ÿ‘จโ€๐Ÿซ

    • Assisted in courses on climate change, air quality, fluid mechanics, and thermodynamics

Professional Development ๐Ÿš€

Mehdi Badami has actively contributed to the field of environmental engineering through cutting-edge research on air pollution, sustainability, and emission control. His extensive knowledge of aerosol science, atmospheric chemistry, and data analysis allows him to assess air quality trends with precision. He has developed innovative models for pollution source apportionment, worked on real-time monitoring systems, and collaborated with leading institutions to improve urban air quality. His passion for environmental justice drives his work towards creating actionable solutions that ensure healthier air for communities. His dedication extends beyond academia, as he actively engages in outreach and policy-driven initiatives. ๐ŸŒฟ๐Ÿ“Š

Research Focus ๐Ÿ”

Mehdiโ€™s research centers on air pollution control, environmental monitoring, and sustainable urban development. His work involves identifying and mitigating pollution sources through field measurements and computational models. He specializes in:

  • Air Quality Assessment ๐ŸŒซ๏ธ๐Ÿ“Š โ€“ Studying PM2.5 and ultrafine particle pollution in urban environments
  • Pollution Source Apportionment ๐Ÿญโš–๏ธ โ€“ Analyzing emissions from vehicles, industries, and natural sources
  • Aerosol Science ๐ŸŒช๏ธ๐Ÿ’จ โ€“ Investigating the toxicity and health impacts of airborne particles
  • Machine Learning in Environmental Studies ๐Ÿค–๐Ÿ“‰ โ€“ Utilizing data science to model pollution trends
  • Climate and Environmental Justice ๐ŸŒŽโš–๏ธ โ€“ Advocating for equitable air quality policies in urban communities

Awards & Honors ๐Ÿ†

  • Outstanding Research Assistant Award โ€“ USC, Sonny Astani Department of Civil and Environmental Engineering (2024) ๐Ÿ…
  • Fellowship Award โ€“ USC (2022-2023) ๐ŸŽ“๐Ÿ’ฐ (Recognized for academic excellence in Environmental Engineering)
  • National Fellowship for Masterโ€™s Studies โ€“ University of Tehran (2017) ๐Ÿ“–๐Ÿ†
  • Top 0.15% Rank in National Entrance Exam โ€“ Iran (Competitive ranking in Mechanical Engineering)

Publication Top Notes:

๐Ÿ“„ Design, optimization, and evaluation of a wet electrostatic precipitator (ESP) for aerosol collection โ€“ Atmospheric Environment (2023) โ€“ ๐Ÿ“‘ Cited by: 11
๐Ÿ“„ Size-segregated source identification of water-soluble and water-insoluble metals and trace elements of coarse and fine PM in central Los Angeles โ€“ Atmospheric Environment (2023) โ€“ ๐Ÿ“‘ Cited by: 7
๐Ÿ“„ Numerical study of blood hammer phenomenon considering blood viscoelastic effects โ€“ European Journal of Mechanics-B/Fluids (2022) โ€“ ๐Ÿ“‘ Cited by: 7
๐Ÿ“„ Development and performance evaluation of online monitors for near real-time measurement of total and water-soluble organic carbon in fine and coarse ambient PM โ€“ Atmospheric Environment (2024) โ€“ ๐Ÿ“‘ Cited by: 4
๐Ÿ“„ Numerical analysis of laminar viscoelastic fluid hammer phenomenon in an axisymmetric pipe โ€“ Journal of the Brazilian Society of Mechanical Sciences and Engineering (2021) โ€“ ๐Ÿ“‘ Cited by: 3
๐Ÿ“„ Urban emissions of fine and ultrafine particulate matter in Los Angeles: Sources and variations in lung-deposited surface area โ€“ Environmental Pollution (2025) โ€“ ๐Ÿ“‘ Cited by: 1

 

 

 

Assoc. Prof. Dr. Kincsล‘ Decsi | Data in Brief | Best Researcher Award

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Assoc. Prof. Dr. Kincsล‘ Decsi | Data in Brief | Best Researcher Award

Assoc. Prof. Dr. Kincsล‘ Decsi, Hungarian University of Agricultural and Life Sciences, Institute of Agronomy, Hungary

Assoc. Prof. Dr. Kincsล‘ Decsi is a renowned academic in the field of plant physiology and plant ecology, currently serving as an associate professor at the Hungarian University of Agriculture and Life Sciences, Georgikon Campus. She has an extensive academic career, having previously held assistant professor roles at the same institution and at Pannon University. Dr. Decsi earned her Ph.D. in Agricultural and Horticultural Sciences in 2005, summa cum laude, with a dissertation on abiotic stress effects in maize. Her research and teaching focus on plant biotic and abiotic stress physiology, plant growth, and development. She has taught a wide range of courses at the BSc, MSc, and PhD levels, in both Hungarian and English. Dr. Decsiโ€™s research contributions, particularly in plant genetics, bioinformatics, and environmental stress physiology, have significantly advanced our understanding of plant resilience and adaptation. ๐ŸŒฑ๐Ÿ“š๐ŸŒ

Professional Profile

Orcid

Suitability for Award

Assoc. Prof. Dr. Kincsล‘ Decsi is an exceptional candidate for the Research for Best Researcher Award due to her significant contributions to plant physiology, environmental stress, and plant genetics. Her extensive teaching experience at both undergraduate and postgraduate levels, coupled with her research on plant adaptation to biotic and abiotic stresses, has earned her recognition in academia. Dr. Decsiโ€™s work in bioinformatics and transcriptomics has enhanced the understanding of plant responses to environmental challenges, which is vital for sustainable agriculture. Her leadership in the scientific community, especially in plant physiology and molecular biology, makes her a suitable candidate for this prestigious award. Dr. Decsiโ€™s ability to bridge research and teaching, coupled with her impact on both local and international scientific communities, reflects her dedication to advancing agricultural sciences. ๐ŸŒพ๐Ÿ”ฌ๐Ÿ…

Education

Assoc. Prof. Dr. Kincsล‘ Decsi has an extensive academic background in agricultural sciences. She earned her Ph.D. in Agricultural and Horticultural Sciences from the Hungarian University of Agriculture and Life Sciences in 2005, with summa cum laude honors. Her doctoral research focused on examining the effects of various abiotic stresses on maize. Dr. Decsiโ€™s educational journey began with a Certified Agricultural Engineer qualification from the University of Veszprรฉm, where she also studied plant genetics and plant breeding. Additionally, she completed a Certified Chemistry Teacher qualification at Pannon University in 2023. Dr. Decsiโ€™s early academic experiences were enriched by scholarships such as the Martonvรกsรกr and Pioneer Hi-Bred Rt. scholarships, which allowed her to deepen her expertise in plant science. Her education has laid the foundation for her ongoing research and teaching in plant physiology, molecular biology, and bioinformatics. ๐ŸŽ“๐ŸŒพ๐Ÿ“–

Experienceย 

Assoc. Prof. Dr. Kincsล‘ Decsi has over two decades of experience in both research and teaching. She currently holds the position of associate professor at the Hungarian University of Agriculture and Life Sciences, Georgikon Campus, where she has taught various plant physiology and molecular biology courses at the BSc, MSc, and PhD levels. Her research experience spans from genetic mapping of potato blight resistance genes to the study of abiotic stress effects in plants. Dr. Decsi has also been involved in bioinformatics research, particularly in transcriptomic studies, enhancing her expertise in plant adaptation and resilience. Her role as a scientific associate at the Festetics Gyรถrgy Bioinnovation Research Center further strengthened her research portfolio, contributing to projects on plant genetic mapping and resistance genes. Dr. Decsiโ€™s experience is a blend of practical research, teaching, and leadership in the scientific community. ๐ŸŒฟ๐Ÿ’ผ๐Ÿ”ฌ

Awards and Honors

Assoc. Prof. Dr. Kincsล‘ Decsi has been recognized for her academic excellence through various scholarships and awards. She received the Pioneer Hi-Bred Rt. Scientific Scholarship and the Martonvรกsรกr Scientific Scholarship in the late 1990s and early 2000s, which supported her early academic development. Dr. Decsi was also honored with the Georgikon Outstanding Scholarship for her exceptional performance during her studies. Additionally, she was awarded the Lรกszlรณffy Woldemรกr Diploma Thesis Application special fee in recognition of her outstanding academic achievements. Her participation in international language courses, such as the Sommerakademie in Neubrandenburg and Wiener Internationale Hochschulkurse, further enriched her academic journey. These awards and honors reflect Dr. Decsiโ€™s dedication to her field and her commitment to advancing plant science research. ๐Ÿ†๐ŸŽ“๐ŸŒ

Research Focusย 

Assoc. Prof. Dr. Kincsล‘ Decsiโ€™s research focuses on plant physiology, particularly the effects of biotic and abiotic stresses on plant growth and development. Her work explores how plants respond to environmental challenges such as drought, salinity, and pathogen attacks, which are critical for improving agricultural resilience. Dr. Decsi has contributed significantly to the field of plant genetics, including the genetic mapping of resistance genes for potato blight and PVY virus resistance. Her research also delves into bioinformatics, particularly in transcriptomic studies, to understand gene expression under stress conditions. Dr. Decsiโ€™s work aims to enhance the sustainability of agricultural practices by improving plant stress tolerance, which is essential for food security in the face of climate change. Her contributions to molecular plant biology, biotechnology, and environmental stress physiology are pivotal in advancing our understanding of plant adaptation mechanisms. ๐ŸŒฑ๐Ÿ”ฌ๐ŸŒฟ

Publication Top Notes

  • Title: RNA-seq Datasets of Field Rapeseed (Brassica napus) Cultures Conditioned by Elice16Indures (R) Biostimulator
    • Year: 2022
  • Title: RNA-seq Datasets of Field Soybean Cultures Conditioned by Elice16Indures (R) Biostimulator
    • Year: 2022
  • Title: Time-course Gene Expression Profiling Data of Triticum Aestivum Treated by Supercritical CO2 Garlic Extract Encapsulated in Nanoscale Liposomes
    • Year: 2022
  • Title: Transcriptome Datasets of Beta-Aminobutyric Acid (BABA)-Primed Mono- and Dicotyledonous Plants, Hordeum Vulgare and Arabidopsis Thaliana
    • Year: 2022
  • Title: Transcriptome Profiling Dataset of Different Developmental Stage Flowers of Soybean (Glycine Max)
    • Year: 2022

 

 

Prof. Dr. Lei Geng | Data Analysis | Best Researcher Award

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Prof. Dr. Lei Geng | Data Analysis | Best Researcher Award

Prof. Dr. Lei Geng, Tiangong University, China

Prof. Dr. Lei Geng is a distinguished professor at the School of Life Sciences, Tiangong University, with a focus on computer vision, machine learning, and measurement technology. He received his Ph.D. in 2012 from Tianjin University and has since made significant contributions to the fields of AI, machine vision, and medical technology. With over 80 published papers, Dr. Geng has played a pivotal role in the development of advanced imaging and measurement technologies for industrial and medical applications. His research includes applications in image analysis, 3D dimensional measurement, and hemostatic medical equipment. As a leader in his field, he has led more than 10 national and provincial-level projects and received numerous awards for his technological innovations. ๐Ÿš€

Professional Profile:

Scopus
Orcid

Suitability for the Award

Prof. Dr. Lei Geng is highly suitable for the Best Researcher Award due to his groundbreaking work in AI, machine vision, and medical technology. His research has led to the development of advanced image analysis techniques and high-precision measurement tools, with far-reaching implications for both industrial and healthcare applications. Dr. Gengโ€™s leadership in national and provincial projects, combined with his three provincial-level awards, highlights his ability to drive technological advancements that have a direct impact on society. His contributions to AI-based diagnostics, particularly in otolaryngology, underscore his dedication to improving healthcare through cutting-edge technologies. Prof. Gengโ€™s consistent excellence in research, innovation, and application makes him an ideal candidate for this prestigious award. ๐Ÿ…

Education

๐ŸŽ“ Dr. Lei Geng earned his Ph.D. in 2012 from Tianjin University, specializing in areas at the intersection of computer vision, machine learning, and measurement technology. His academic journey laid the foundation for his extensive contributions to these fields, including the development of cutting-edge applications in industrial and medical sectors. Dr. Gengโ€™s deep understanding of both theoretical and practical aspects of machine vision and artificial intelligence has made him an expert in creating innovative solutions across multiple industries. His education has fueled his ongoing research and contributions to advancements in AI-driven healthcare and precision measurement technologies. ๐Ÿ“˜

Experience

๐Ÿง‘โ€๐Ÿซ Prof. Dr. Lei Geng has extensive teaching and research experience, currently serving as a professor at the School of Life Sciences at Tiangong University. He has been involved in both undergraduate and postgraduate education, teaching courses such as Machine Vision and Deep Learning. Over his career, Dr. Geng has undertaken more than 10 national, provincial, and ministerial-level projects, focusing on industrial and medical applications of machine vision and AI. His experience includes pioneering work in hemostatic medical equipment and high-precision 2D/3D measurement systems. This broad range of expertise positions Dr. Geng as a leader in his field, particularly in the integration of AI technologies with practical, real-world applications. ๐ŸŒ

Awards and Honors

๐Ÿ… Dr. Lei Gengโ€™s excellence in research and technological innovation has been recognized through several prestigious awards. He has received three provincial-level awards, including the Tianjin Second Prize for Technological Invention and the Special Prize of the National Award for Business Science and Technology Progress. These accolades are a testament to his significant contributions to the fields of AI, computer vision, and medical technology. Dr. Gengโ€™s ability to bridge the gap between advanced scientific research and practical applications in industries such as healthcare and manufacturing has made him a highly respected figure in the scientific community. ๐ŸŒŸ

Research Focus

๐Ÿ”ฌ Dr. Lei Gengโ€™s research focuses on four key areas:

  1. Image Analysis & Understanding: Developing AI-based systems for image classification, object detection, and segmentation for industrial and medical applications.
  2. Dimensional Measurement: Applying machine vision and 3D scanning technology for high-precision industrial measurement and target positioning.
  3. Hemostatic Medical Equipment: Innovating in extracorporeal compression and intravascular interventional devices for medical bleeding control.
  4. AI in Otorhinolaryngology: Applying deep learning for disease diagnosis in ear, nose, and throat (ENT) medicine.

His work in these areas aims to integrate AI and machine vision to solve real-world problems, particularly in medical diagnostics and industrial automation. ๐Ÿ’ก

Publication Top Notes:

  • Direct May Not Be the Best: An Incremental Evolution View of Pose Generation
    • Year: 2024
    • Citations: 1
  • Multi-parametric investigations on the effects of vascular disrupting agents based on a platform of chorioallantoic membrane of chick embryos
    • Year: 2024
  • Label-Aware Dual Graph Neural Networks for Multi-Label Fundus Image Classification
    • Year: 2024
  • Cross-scale contrastive triplet networks for graph representation learning
    • Year: 2024
    • Citations: 4
  • Objective rating method for fabric pilling based on LSNet network
    • Year: 2024
    • Citations: 3

Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

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Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

Dr. Satish Mahadevan Srinivasan, Penn State Great Valley , United States.

Dr. Satish Mahadevan Srinivasan is a Tenured Associate Professor of Information Science at Penn State Great Valley, with expertise spanning data mining, machine learning, cybersecurity, and bioinformatics. With a Ph.D. in Information Technology from the University of Nebraska, his research contributions include class-specific motif discovery in protein classification and tools for metagenomic analysis. Dr. Srinivasan’s work merges cutting-edge technologies with practical applications, contributing to bioinformatics, distributed computing, and artificial intelligence. He has a rich academic and professional journey, publishing impactful research and developing transformative software tools.ย ๐ŸŒ๐Ÿ“Š๐Ÿ”ฌ

Publication Profiles

Googlescholar

Education and Experience

Education

  • ๐ŸŽ“ย Ph.D. in Information Technology, University of Nebraska, 2010
  • ๐ŸŽ“ย M.S. in Industrial Engineering & Management, IIT Kharagpur, 2005
  • ๐ŸŽ“ย B.E. in Information Technology, Bharathidasan University, 2001

Experience

  • ๐Ÿ“šย Tenured Associate Professor, Penn State Great Valley (2019โ€“Present)
  • ๐Ÿ“šย Assistant Professor, Penn State Great Valley (2013โ€“2019)
  • ๐Ÿ”ฌย Postdoctoral Researcher, Computational Bioinformatics, UNMC (2011โ€“2013)
  • ๐Ÿ’ปย Postdoctoral Research Assistant, Computer Science, University of Nebraska (2010โ€“2011)
  • ๐Ÿ› ๏ธย Project Assistant, IIT Kharagpur (2001โ€“2005)

Suitability For The Award

Dr. Satish Mahadevan Srinivasan, a Tenured Associate Professor at Penn State, excels in interdisciplinary research spanning data mining, bioinformatics, machine learning, and cybersecurity. His groundbreaking tools like MetaID and Monarch have advanced microbial analysis and software engineering. With impactful publications, innovative solutions, and practical applications, Dr. Srinivasan exemplifies research excellence, making him highly deserving of the Best Researcher Award.

Professional Development

Dr. Srinivasan has developed innovative tools and frameworks, including MetaID for metagenomic studies and Monarch for transforming Java programs for embedded systems. His interdisciplinary research bridges machine learning, predictive analytics, and cybersecurity with bioinformatics, aiding microbial classification and software optimization. By integrating artificial intelligence and distributed computing, he has addressed complex challenges in data science, genomics, and engineering. His professional journey reflects a commitment to cutting-edge technology, impactful research, and knowledge dissemination through teaching and mentorship.ย ๐ŸŒŸ๐Ÿ”

Research Focus

Dr. Satish Mahadevan Srinivasan’s research focuses on leveraging advanced technologies to address complex problems in data science, bioinformatics, and cybersecurity. His work inย data miningย andย machine learningย aims to uncover patterns and develop predictive models for diverse applications. Inย bioinformatics, he has designed tools like MetaID for microbial classification and motif discovery in protein sequences, contributing to genomics and medical advancements. His expertise extends toย cybersecurity, where he explores cryptographic techniques to enhance internet security, andย distributed computing, optimizing system performance. Dr. Srinivasan’s interdisciplinary approach bridgesย artificial intelligence,ย predictive analytics, andย software engineeringย to create impactful solutions.ย ๐ŸŒ๐Ÿ”ฌ๐Ÿ“Š

Awards and Honors

  • ๐Ÿ†ย Awarded research grants for innovative bioinformatics tools.
  • ๐Ÿ“œย Recognized for contributions to cybersecurity and internet authentication.
  • ๐ŸŒŸย Acknowledged as a leading researcher in predictive analytics and machine learning.
  • ๐Ÿ“Šย Published in high-impact journals like BMC Bioinformatics and BMC Genomics.

Publication Top Notes

  • Effect of negation in sentences on sentiment analysis and polarity detectionย  โ€“ย Cited by 93, 2021ย ๐Ÿ“Š๐Ÿ“š
  • LocSigDB: A database of protein localization signalsย  โ€“ย Cited by 49, 2015ย ๐Ÿงฌ๐Ÿ“–
  • K-means clustering and principal components analysis of microarray data of L1000 landmark genesโ€“ย Cited by 46, 2020ย ๐Ÿงช๐Ÿ“Š
  • Mining for class-specific motifs in protein sequence classificationย โ€“ย Cited by 29, 2013ย ๐Ÿ”ฌ๐Ÿ“œ
  • Web app security: A comparison and categorization of testing frameworksโ€“ย Cited by 27, 2017ย ๐Ÿ”’๐Ÿ–ฅ๏ธ
  • MetaID: A novel method for identification and quantification of metagenomic samplesย โ€“ย Cited by 23, 2013ย ๐ŸŒ๐Ÿ”
  • Sensation seeking and impulsivity as predictors of high-risk sexual behaviours among international travellersย โ€“ย Cited by 21, 2019ย โœˆ๏ธ๐Ÿง 
  • Cybersecurity for AI systems: A surveyย โ€“ย Cited by 20, 2023ย ๐Ÿค–๐Ÿ”

Abdul-Majeed Al-Izeri | Data Science | Best Scholar Award

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Abdul-Majeed Al-Izeri | Data Science | Best Scholar Award

Dr. Abdul-Majeed Al-Izeri , Clermont Auvergne University, France.

Publication profile

Googlescholar

Education and Experience

  • 2020-2021: University degree in Data Science, University Clermont Auvergne, France.ย ๐ŸŽ“
  • 2013-2016: PhD in Mathematics (Mathematical analysis of PDEs), University Clermont Auvergne, France.ย ๐Ÿ“œ
  • 2011-2012: Master 2 in Mathematical Modelling (PDEs, calculation, epidemiology), University of Bordeaux, France.ย ๐Ÿ’ป
  • 2010-2011: Master 1 in Mathematics (Modelling, calculation, environment), University of Bordeaux, France.ย ๐Ÿ“
  • 2002-2006: BSc in Mathematics, University of Thamar, Yemen.ย ๐Ÿ“˜
  • October 2021-Present: Assistant Professor, Applied Mathematics, Clermont Auvergne University, France.ย ๐Ÿ‘ฉโ€๐Ÿซ
  • January 2018-July 2021: Postdoctoral Researcher in Epidemiology and PDEs, Clermont Auvergne University, France.ย ๐Ÿ”ฌ
  • 2017: Postdoctoral Project in PDEs Dynamics, Clermont Auvergne University, France.ย ๐Ÿงฎ
  • 2013-2016: Thesis Project in Mathematical Analysis of Population Dynamics, Blaise Pascal University, France.ย ๐Ÿ”
  • 2012: Research Internship, Epidemic Model Study, University of Bordeaux, France.ย ๐Ÿ’ก
  • 2011: Project in Mathematical Modelling for Fishing Resources, University of Bordeaux, France.ย ๐ŸŸ

Suitability For The Award

Dr. Abdul-Majeed Al-Izeri is indeed a highly suitable candidate for the Best Scholar Award based on his extensive academic qualifications, professional experience, and notable contributions to the field of Applied Mathematics and Data Science. His academic background, including a PhD in Mathematics with a specialization in Partial Differential Equations (PDEs), as well as a strong postdoctoral research profile, makes him a valuable asset in both academia and research communities.

Professional Developmentย 

Dr. Al-Izeri has gained comprehensive skills in programming languages like Fortran, Matlab, Python, and R, along with proficiency in parallel computation using MPI. His expertise extends to using Latex and other office software for academic writing and presentations. He has been involved in several international research projects focused on applying mathematical theories to solve real-world problems in epidemiology and population dynamics. Dr. Al-Izeriโ€™s ongoing commitment to improving his mathematical expertise and expanding his knowledge in data science and computational methods keeps him at the forefront of his field.ย ๐Ÿ“Š๐Ÿ’ป๐Ÿ”

Research Focusย 

Awards and Honors

  • 2021: Assistant Professor Appointment, Clermont Auvergne University, France.ย ๐ŸŽ“
  • 2016: PhD Completion, Mathematical Analysis of PDEs, University Clermont Auvergne.ย ๐Ÿ†
  • 2012: Research Internship Excellence Award, University of Bordeaux.ย ๐ŸŒŸ
  • 2011: Best Project in Mathematical Modelling for Resource Management, University of Bordeaux.ย ๐Ÿ…

Publoication Top Notes

  1. On the solutions for a nonlinear boundary value problem modeling a proliferating cell population with inherited cycle lengthย – AM Al-Izeri, K Latrach,ย Nonlinear Analysis: Theory, Methods & Applicationsย 143, 1-18, Cited by 6, 2016ย ๐Ÿ“˜๐Ÿงฌ
  2. Well-posedness of a nonlinear model of proliferating cell populations with inherited cycle lengthย – ALI Abdul-Majeed, K Latrach,ย Acta Mathematica Scientiaย 36 (5), 1225-1244, Cited by 5, 2016ย ๐Ÿ“Š๐Ÿงซ
  3. Nonlinear semigroup approach to transport equations with delayed neutronsย – ALI Abdul-Majeed, K Latrach,ย Acta Mathematica Scientiaย 38 (6), 1637-1654, Cited by 3, 2018ย ๐Ÿ”ฌโณ
  4. A nonlinear age-structured model of population dynamics with inherited propertiesย – AM Al-Izeri, K Latrach,ย Mediterranean Journal of Mathematicsย 13, 1571-1587, Cited by 3, 2016ย ๐ŸŒฑ๐Ÿ”ข
  5. On the asymptotic spectrum of a transport operator with elastic and inelastic collision operatorsย – AM Al-Izeri, K Latrach,ย Acta Mathematica Scientiaย 40, 805-823, Cited by 2, 2020ย ๐Ÿ”๐Ÿ”„
  6. A note on fixed point theory for multivalued mappingsย – AM Al-Izeri, K Latrach,ย Fixed Point Theoryย 24 (1, 2023), 233-240, Cited by 1, 2023ย ๐Ÿ“๐Ÿ“