プロフィール詳細

プロジェクトを作成

★★★★★

☆☆☆☆☆

★★★★★

☆☆☆☆☆

Dr. Aiman G.に依頼

Netherlands

Applied ML Researcher | Time-Series Forecasting, Digital Twins & Python Data Apps, Networks, and NLP

プロフィール概要

I am an applied machine learning researcher and Python developer with strong experience in time-series forecasting, digital twins, interpretable AI, and custom data applications. I completed my PhD at USTC and later worked as a postdoctoral researcher at Eindhoven University of Technology, where I developed global forecasting and clustering methods for large LED degradation datasets as part of the ECSEL AI-Twilight digital twin project. I am the first author of an ACM TIST publication on global forecasting for LED lumen degradation. In addition to research, I build practical tools that help people use data effectively. I have developed Streamlit apps, Python analysis pipelines, and desktop GUI tools for exploratory analysis, explainable AI, and interactive visualization. My projects include end-to-end applications for semantic mapping, network analysis, and rule extraction, and I enjoy turning complex datasets into usable systems for researchers, engineers, and decision-makers. I can help with forecasting, data cleaning, exploratory analysis, interpretable ML, dashboard development, and research-oriented Python solutions. My background also includes network analytics and NLP model development, which gives me flexibility across scientific and technical projects.

専門分野

• ☆ Electrical Engineering
• ☆ Wireless Sensor Networks
• ☆ Network Engineering
• ☆ Data Analysis
• ☆ Machine Learning
• ☆ Neural Networks
• ☆ Telecommunications
• ☆ Computer Networks & Networking
• ☆ Multilingualism
• ☆ Computer Science Education

サービス

• Writing
• Research
• Consulting
• Data & AI

Writing Technical Writing, Creative Writing

Research Scientific and Technical Research

Consulting Digital Strategy Consulting, Scientific and Technical Consulting

Data & AI Predictive Modeling, Image Analysis, Algorithm Design-Non ML, Algorithm Design-ML, Data Visualization, Text Mining & Analytics, Data Processing, Data Insights

職務経験

Independent Researcher

Independent Researcher

1月 2026 - 現在

Eindhoven University of Technology

- 5月 2024

Visiting Scholar

University of Science and technology of China

7月 2021 - 7月 2022

Network engineering

MIPc

11月 2010 - 8月 2013

学歴

doctor of engineering in computer science

University of Science and Technology of China

9月 2017 - 5月 2021

Master of engineering in Computer Science

University of Science and Technology of China

9月 2014 - 6月 2017

認定資格

• Ph.D

  University of Science and Technology of China

  1月 2026 - 現在

• Masters

  University of Science and Technology of China

  1月 2026 - 現在

出版物

JOURNAL ARTICLE

Aiman Ghannami (2026). Global Forecasting Model for LED Lumen Degradation: An Optimal Cluster Estimation Method . ACM Transactions on Intelligent Systems and Technology.

Potential of Satellite-Airborne Sensing Technologies for Agriculture 4.0 and Climate-Resilient @article{e9c20e02820442a2b6f9d6da5a1987ee, title = "Potential of Satellite-Airborne Sensing Technologies for Agriculture 4.0 and Climate-Resilient: A Review", abstract = "Agriculture 4.0 offers the potential to revolutionize the agriculture sector through improved productivity and efficiency. However, adopting Agriculture 4.0 requires a period of transition and effort. Satellite-airborne sensing technologies may become an opening enabler technology of this new paradigm due to its fast deployment process and flexible infrastructure. This article provides an overview of the technology, trends, challenges, and opportunities in agriculture and climate-resilient sensing technologies. The research covers critical enabling technologies such as low-altitude platforms (LAPs) (i.e., drones and tethered balloons), high-altitude platforms (HAPs) (i.e., airships, HAPs balloons, and aircraft), and satellites, as well as recent advancements in data processing and digital twins (DT), with some examples from agricultural research projects. Furthermore, this article explores some challenges in agriculture and the technological deployment of satellite-airborne sensing technologies. Finally, this article provides some potential opportunities for satellite-airborne sensing technologies for agricultural purposes. This article may become a guide for adopting Industry 4.0 by leveraging satellite-airborne network technologies.", keywords = "Agriculture 4.0, airborne network (AN), high-altitude platforms (HAPs), satellite, smart farming, unmanned aerial vehicles (UAVs)", author = "Hazmy, \{Asa Ibnu\} and Ammar Hawbani and Xingfu Wang and Ahmed Al-Dubai and Aiman Ghannami and Yahya, \{Ali Abdullah\} and Liang Zhao and Alsamhi, \{Saeed Hamood\}", year = "2024", month = feb, day = "15", doi = "10.1109/JSEN.2023.3343428", language = "English", volume = "24", pages = "4161--4180", journal = "IEEE Sensors Journal", issn = "1530-437X", publisher = "Institute of Electrical and Electronics Engineers", number = "4", } . IEEE Sensors Journal.

Ghannami, A., Li, J., Hawbani, A., Alhusaini, N.(2021). Diversity metrics for direct-coded variable-length chromosome shortest path problem evolutionary algorithms . Computing. 103. (2). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 313-332.

Ghannami, A., Li, J., Hawbani, A., Al-Dubai, A.(2021). Stratified opposition-based initialization for variable-length chromosome shortest path problem evolutionary algorithms . Expert Systems with Applications. 170.

Hawbani, A., Wang, X., Kuhlani, H., Ghannami, A., Farooq, M.U., Al-sharabi, Y.(2019). Extracting the overlapped sub-regions in wireless sensor networks . Wireless Networks. 25. (8). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 4705-4726.

Hawbani, A., Wang, X., Sharabi, Y., Ghannami, A., Kuhlani, H., Karmoshi, S.(2019). LORA: Load-Balanced Opportunistic Routing for Asynchronous Duty-Cycled WSN . IEEE Transactions on Mobile Computing. 18. (7). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 1601-1615.

Hawbani, A., Wang, X., Abudukelimu, A., Kuhlani, H., Sharabi, Y., Qarariyah, A., Ghannami, A.(2019). Zone Probabilistic Routing for Wireless Sensor Networks . IEEE Transactions on Mobile Computing. 18. (3). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 728-741.

Hawbani, A., Wang, X., Karmoshi, S., Kuhlani, H., Ghannami, A., Abudukelimu, A., Ghoul, R.(2017). GLT: Grouping based location tracking for object tracking sensor networks . Wireless Communications and Mobile Computing. 2017.

CONFERENCE PAPER

Ghannami, A., Shao, C.(2017). Efficient fast recovery mechanism in Software-Defined Networks: Multipath routing approach . 2016 11th International Conference for Internet Technology and Secured Transactions, ICITST 2016. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 432-435.

Ghannami, A., Shao, C.(2017). Experience-based learning for identifying sub-regions in Wireless Sensor Networks . 2016 11th International Conference for Internet Technology and Secured Transactions, ICITST 2016. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 326-327.

Karmoshi, S., Hawbani, A., Ghannami, A., Mohammed, S., Zhu, M.(2017). VNE-Greedy: Virtual Network Embedding Algorithm Based on OpenStack Cloud Computing Platform . Proceedings - 2016 International Conference on Digital Home, ICDH 2016. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 143-149.