R&D | Bioinformatics & AI Healthcare
Passionate about applying technology to healthcare and education through innovative machine learning solutions and data-driven approaches.
I'm a bioinformatics researcher with a passion for applying technology to healthcare and education. I hold a Bachelor's in Computer Science and a Master's in Bioinformatics, with experience in analyzing complex biological datasets and building machine learning models.
I specialize in bioinformatics, machine learning, and data-driven solutions, working on projects such as multi-omics biomarker identification, breast cancer classification, and tumor detection. My research combines rigorous data analysis with practical applications, bridging biology, statistics, and computational techniques.
At Learnify Health, I contributed to both technical development and marketing:
I am proficient in Python, machine learning,SQL and bioinformatics tools, and I enjoy creating projects that combine technical rigor, creativity, and real-world impact.
Multi-omics analysis, biomarker identification, and biological data interpretation using computational methods.
Development of predictive models for cancer classification, tumor detection, and healthcare applications.
Building robust pipelines, interactive applications, educational tools, and data analysis solutions for healthcare technology.
Developed machine learning models to identify predictive biomarkers using integrated genomic, transcriptomic, and proteomic data for improved disease diagnosis.
Built predictive models for breast cancer classification using advanced machine learning algorithms and feature selection techniques.
Developed interactive virtual patient scenarios and optimized pipelines for healthcare education, contributing to both technical development and marketing.
Designed and implemented automated workflows for processing large-scale genomic datasets, reducing processing time by 60% and improving data quality.
Developed a machine learning platform for drug discovery using molecular docking simulations and predictive modeling, achieving 85% accuracy in binding affinity prediction.
Built an interactive dashboard for clinical data visualization and analysis, enabling healthcare professionals to make data-driven decisions with real-time insights.
I'm always interested in new opportunities and collaborations in bioinformatics, machine learning, and healthcare technology.