Ahmed Soliman
Graduate Researcher
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About Ahmed Soliman
AI Data Scientist and Researcher specializing in advanced artificial intelligence methodologies. Expertise encompasses machine learning architectures, generative AI, multimodal systems, and natural language processing with a focus on clinical data analysis and medical informatics. Proficient in developing and optimizing large-scale language models for healthcare domains through advanced fine-tuning methodologies and prompt engineering. Dedicated to advancing responsible AI technologies that bridge computational innovation with clinical practice, delivering evidence-based solutions that transform healthcare delivery and improve patient care quality. Committed to pioneering ethical AI solutions that deliver measurable impact and translate cutting-edge research into practical applications with significant societal and commercial value.
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Graduate Researcher
2025 – Current · University of Florida
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AI Data Scientist Researcher
2024 – 2025 · University of Florida, USA
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Data Science & AI Instructor
2024 – 2024 · Ministry of Communication and Information Technology in Egypt
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Machine Learning Instructor
2024 – 2024 · Streamlines Energy for Oil and Gas, Cairo, Egypt
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Machine Learning Engineer and Researcher
2023 – 2023 · Upshift Foundation, USA
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Data Science and Machine Learning Instructor
2022 – 2023 · Udacity
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Teaching Assistant
2021 – 2024 · Galala University in Egypt Powered by Arizona State University in the USA
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Teaching Assistant
2019 – 2024 · Faculty of Engineering, Al-Azhar University, Egypt
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Machine Learning Engineer & System Architect
2019 – 2023 · RoboEye Tec, Egypt
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Teaching Assistant
2016 – 2018 · Egyptian Academy for Engineering & Advanced Technology, Egypt
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Software Engineer
2014 – 2016 · Information Systems and Computing Center (ISCC), Egypt
Teaching Profile
Teaching Philosophy
My approach includes a mix of interactive lectures, hands-on activities, and practical applications to cater to diverse learning styles.
Research Profile
My research advances Machine Learning (ML), Generative AI, and Natural Language Processing (NLP), focusing on Agentic AI systems, LLM optimization, and multimodal applications. I develop and fine-tune AI models for real-world challenges, including code generation, EHR-based suicide risk identification, and healthcare innovation. Leveraging techniques like prompt engineering, LangChain, and Retrieval-Augmented Generation (RAG), I aim to bridge research and practical implementation. My work drives innovation in AI, emphasizing scalable solutions and knowledge sharing to address complex societal and industrial problems.
Areas of Interest
- Artificial Intelligence
- Biomedical informatics
- Deep Learning
- Generative AI
- Information Retrieval
- Machine learning and applications
- Multimodal
- Natural Language Processing (NLP)
- Prompt Engineering
- data science
Publications
Academic Articles
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Natural Language Processing to Identify Substance Use in Electronic Health Records: A Scoping Review.
- Journal
- Substance use & addiction journal.
- Volume/Issue
- 47(4):1273-1287
- [DOI]
- 10.1177/29767342261463377.
- [PMID]
- 42481076.
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Efficacy and safety of upadacitinib in adults and adolescents for treatment of non-segmental vitiligo (Viti-Up): results of two phase 3 randomised controlled studies.
- Journal
- Lancet (London, England).
- Volume/Issue
- 408(10555):636-648
- [DOI]
- 10.1016/S0140-6736(26)00896-2.
- [PMID]
- 42594914.
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Beyond metrics to methods: a scoping review of transformers and large language models for detection of social drivers of health in clinical notes.
- Journal
- Journal of the American Medical Informatics Association : JAMIA.
- Volume/Issue
- 33(3):754-769
- [DOI]
- 10.1093/jamia/ocaf201.
- [PMID]
- 41691647.
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Integrating Machine Learning Models for Enhancing Power Transformer Health Assessment Based on the Insulating Paper State
- Journal
- Measurement.
- Volume/Issue
- 256
- [DOI]
- 10.1016/j.measurement.2025.118222.
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Beyond Metrics to Methods: A Scoping Review of Large Language Models for Detection of Social Drivers of Health in Clinical Notes
- Journal
- medRxiv.
- [DOI]
- 10.1101/2025.07.04.25330866.
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Leveraging pre-trained language models for code generation
- Journal
- Complex & Intelligent Systems.
- Volume/Issue
- 10(3):3955-3980
- [DOI]
- 10.1007/s40747-024-01373-8.
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MarianCG: a code generation transformer model inspired by machine translation
- Journal
- Journal of Engineering and Applied Science.
- Volume/Issue
- 69(1)
- [DOI]
- 10.1186/s44147-022-00159-4.
Education
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PhD in Biomedical Informatics & Data Science
University of Florida
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MSc in Computer Engineering
Faculty of Engineering, Cairo University, Egypt
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BSc in Computer Engineering
Faculty of Engineering, Al-Azhar University, Egypt
Contact Details
- Business:
- (689) 243-5534
- Business:
- ahmed.soliman@ufl.edu
- Business Mailing:
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1889 MUSEUM RD STE 7000
GAINESVILLE FL 32611 - Business Street:
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1889 MUSEUM RD STE 7000
GAINESVILLE FL 32611