プロフィール詳細

プロジェクトを作成

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Flora O.に依頼

Nigeria

AI Engineer & Researcher | 5 years experience in Data science & Analytics. Award winner at ICLR 2025 Conference

プロフィール概要

I am an AI Engineer and independent AI Researcher with experience showcasing work at leading conferences such as NeurIPS, ICLR, and Deep Learning Indaba. My recent paper, “How Effective Are AI Models in Translating English Scientific Texts to Nigerian Pidgin: A Low-Resource Language?”, received the Didactic Paper Award at the ICLR 2025 Workshop in Singapore. I specialize in developing AI systems and conducting end-to-end research problem identification, data sourcing, model training and evaluation, and academic writing. Alongside my AI expertise, I am proficient in data analytics and data science, with hands-on experience in data collection, preprocessing, analysis, and visualization to generate actionable insights for stakeholders. With a degree in Biotechnology and a research publication in that field, I am also equipped to contribute to bioinformatics, ecology, and genetics research. My technical toolkit spans Python, Excel, Matplotlib, Scikit-learn, TensorFlow, PyTorch, Power BI, Tableau, Langraph, Hugging Face, and LLMs enabling me to handle diverse tasks across AI, analytics, and research.

専門分野

• ☆ Computational Biology
• ☆ Evolutionary Biology
• ☆ Biostatistics
• ☆ Molecular Biology
• ☆ Biomarkers
• ☆ Genetics
• ☆ Microarrays
• ☆ Cell Biology
• ☆ Cytogenetics
• ☆ Cell Signaling Pathways
• ☆ Membrane Biology
• ☆ Gene Regulation
• ☆ Stem Cell Research
• ☆ Data Analysis
• ☆ Image Processing
• ☆ Algorithm Design
• ☆ Predictive Modeling & Analytics
• ☆ Data Processing
• ☆ Data Exploration
• ☆ Cluster Analysis
• ☆ Data Visualization
• ☆ Big Data Analytics
• ☆ Data Collection
• ☆ Data Management
• ☆ Data Manipulation
• ☆ Machine Learning
• ☆ Text Mining & Analytics
• ☆ Data Mining
• ☆ Data Cleaning
• ☆ Natural Language Processing
• ☆ Neural Networks
• ☆ Pattern Recognition
• ☆ Artificial Intelligence
• ☆ Deep Learning
• ☆ Business Analytics
• ☆ Cell Culture
• ☆ Primary Cells
• ☆ Cell Banking
• ☆ Cell Line Engineering
• ☆ Large Scale Cell Culture
• ☆ Knowledge Management
• ☆ Taxonomy/Classification
• ☆ Data Archaeology
• ☆ Decision Science
• ☆ Cell Aging
• ☆ Information & Knowledge Management
• ☆ Data Storage
• ☆ Python
• ☆ SPSS
• ☆ SQL
• ☆ Excel
• ☆ Tensorflow
• ☆ LaTex
• ☆ R
• ☆ Tableau
• ☆ Scikit-learn
• ☆ Markup Languages

サービス

• Writing
• Research
• Data & AI
• Product Development

Writing Technical Writing

Research Technology Scouting, Gray Literature Search, Scientific and Technical Research, Systematic Literature Review, Secondary Data Collection

Data & AI Predictive Modeling, Statistical Analysis, Image Analysis, Data Visualization, Big Data Analytics, Data Cleaning, Data Processing, Data Insights

Product Development Formulation, Stability/Shelf Life Testing, Prototyping

職務経験

AI Engineer

Tolaram Groups

3月 2025 - 現在

AI Researcher

Data Science Nigeria

8月 2023 - 3月 2025

学歴

Biotechnology

Federal University of Technology Akure

1月 2017 - 10月 2023

B.Tech (Biotechnology)

Federal University of Technology

1月 2017 - 10月 2023

認定資格

• Microsoft Certified: Azure AI Engineer Associate

  Microsoft

  https://learn.microsoft.com/en-us/users/floraoladipupo/credentials/7012412979117aff

  5月 2025 - 現在

• Microsoft Certified: Azure Data Scientist Associate

  Microsoft

  https://learn.microsoft.com/api/credentials/share/en-us/FloraOladipupo/5A4B9A1CC27C3C41?sharingId=FED71F1FC5487F8A

  6月 2024 - 現在

出版物

CONFERENCE PAPER

Flora Oladipupo, Ife Adebara, Ife Adebara, Ife Adebara, Olubayo Adekanmbi, Olubayo Adekanmbi, et al.(2025). How Effective Are AI Models in Translating English Scientific Texts to Nigerian Pidgin: A Low-resource Language . The International Conference on Learning Representations (ICLR).

JOURNAL ARTICLE

Flora Oladipupo, Zion Oluwasegun, Ugwu Paschal, Ogunleye Adewale(2024). Bioinformatics Jobs 2024: Trends, Top Locations and In-Demand Skills . HackBio. HackBio

Alabi, O.A., Afelumo, O.M., Oladipupo, F.O. et al. Safety assessment of three common food additives: the reproductive, oxidative and enzymatic perspective. Discov Toxicol 1, 8 (2024). https://doi.org/10.1007/s44339-024-00007-5 .