09/10/2022 updated


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Bioengineer - Bioinformatician | Entry Level AI Engineer | Entry Level Web Developer
Turkey
Turkey
BSc in Bioengineering (English)HTMLJavaScriptArtificial IntelligenceData AnalysisBiomechanicsMedical ImagingCascading Style Sheets (CSS)Computer ProgrammingDatabasesData VisualizationWeb DevelopmentFood ChemistryImage ProcessingPython (Programming Language)MATLAB
Background and knowledge in computer programming languages and frameworks including MATLAB, Python, HTML, CSS, JavaScript, React and React Native.
Skilled in working with FEBio (Finite Elements for Biomechanics) software tool
I designed a project in Molecular Modeling of Protein Interactions (Molecular Docking) and Bioinformatics during my graduation thesis.
I gained skills and competencies in Molecular Design with Deep Learning during my internships.
The knowledge, skills and competencies acquired that I worked on during my internships and work experiences:
β’ Bioinformatic and cheminformatic analysis of the nutraceutical database was conducted and the results of the research were published as a paper.
Kaya, I. and Colmenarejo, G. βAnalysis of Nuisance Substructures and Aggregators in a Comprehensive Database of Food Chemical Compounds,β Journal of Agricultural and Food Chemistry, vol. 68, no. 33, pp. 8812β8824, Aug. 2020, doi: 10.1021/acs.jafc.0c02521.
β’ Deeper knowledge of Python libraries for data analysis and data visualization and chemoinformatic toolkits especially Pandas, NumPy, Matplotlib
β’ Deeper knowledge of Python libraries for chemoinformatic toolkits: RDKit
β’ Familiarization with Python Machine Learning and Deep Learning libraries: TensorFlow, Keras, Scikit-Learn
β’ Gaining a deeper knowledge of Python libraries for working medical imaging datasets: pydicom, SimpleITK
β’ Gaining a deeper knowledge of Python libraries for preprocessing of the data and image processing: scikit-image, OpenCV
β’ Gaining knowledge of Python Deep Learning libraries: PyTorch, PyTorch Lightning
ββββββββ’ Working on medical image segmentation studies with CNN-based methods
ββββββββ’ Professional usage of Git
Skilled in working with FEBio (Finite Elements for Biomechanics) software tool
I designed a project in Molecular Modeling of Protein Interactions (Molecular Docking) and Bioinformatics during my graduation thesis.
I gained skills and competencies in Molecular Design with Deep Learning during my internships.
The knowledge, skills and competencies acquired that I worked on during my internships and work experiences:
β’ Bioinformatic and cheminformatic analysis of the nutraceutical database was conducted and the results of the research were published as a paper.
Kaya, I. and Colmenarejo, G. βAnalysis of Nuisance Substructures and Aggregators in a Comprehensive Database of Food Chemical Compounds,β Journal of Agricultural and Food Chemistry, vol. 68, no. 33, pp. 8812β8824, Aug. 2020, doi: 10.1021/acs.jafc.0c02521.
β’ Deeper knowledge of Python libraries for data analysis and data visualization and chemoinformatic toolkits especially Pandas, NumPy, Matplotlib
β’ Deeper knowledge of Python libraries for chemoinformatic toolkits: RDKit
β’ Familiarization with Python Machine Learning and Deep Learning libraries: TensorFlow, Keras, Scikit-Learn
β’ Gaining a deeper knowledge of Python libraries for working medical imaging datasets: pydicom, SimpleITK
β’ Gaining a deeper knowledge of Python libraries for preprocessing of the data and image processing: scikit-image, OpenCV
β’ Gaining knowledge of Python Deep Learning libraries: PyTorch, PyTorch Lightning
ββββββββ’ Working on medical image segmentation studies with CNN-based methods
ββββββββ’ Professional usage of Git
Languages
EnglishFluentFrenchBasic knowledgeSpanishGoodTurkishNative speaker
Project history
- Gaining knowledge of Python Deep Learning libraries: PyTorch, PyTorch Lightning
- Gaining a deeper knowledge of Python libraries for preprocessing of the data and image processing: scikit-image, OpenCV
- Working on medical image segmentation studies with CNN-based methods
- Working on lung disease diagnosis studies with Deep Learning
- Professional usage of Git
- Company project reporting
- Gaining a deeper knowledge of biomedical imaging datasets and their properties
- Gaining a deeper knowledge of Python libraries for working medical imaging datasets: pydicom, SimpleITK
- Working on medical image segmentation studies with traditional methods
- Working on lung disease diagnosis studies with Deep Learning