Ph.D. in Cellular & Molecular Biology | Biomedical Scientist | B.Sc. Information Systems
I am a biomedical scientist and university professor with a Ph.D. in Cellular & Molecular Biology, currently in the first year of a Bachelor's degree in Information Systems.
My work sits at the intersection of biomedical science and software engineering, combining extensive experience in experimental research with formal training in computer science, programming, and information systems.
I am particularly interested in developing software and computational workflows for scientific research, biomedical data, laboratory automation, and reproducible analysis.
Languages & Data
Scientific Computing
Development & Infrastructure
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Scientific Computing & Automation Developing Python-based tools and workflows for experimental data processing, scientific analysis, and research automation.
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Biomedical Software Applying software engineering principles to problems in biomedical research, laboratory workflows, and scientific data management.
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Database Engineering Designing normalized relational databases with emphasis on data integrity, consistency, and efficient querying.
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Reproducible Research Building structured computational environments and version-controlled workflows using Linux, Docker, and Git.
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Software Engineering Exploring object-oriented programming, software architecture, testing, error handling, and maintainable application design.
A reproducible Python-based pipeline for molecular docking, virtual screening, GROMACS molecular dynamics, trajectory analysis, MM-PBSA calculations, and automated reporting.
The project focuses on automating and structuring multi-stage molecular simulation workflows, with target-specific data isolation, validation of computational artifacts, and modular execution of computationally intensive stages.
Stack: Python · GROMACS · Linux · Docker · uv · Git
A Python-based CLI tool designed to streamline cytogenetic assays and micronucleus analysis, replacing manual counting workflows with a keyboard-driven data acquisition system.
The application provides dedicated counting modes for nuclear classification and genotoxicity markers, automated protocol limits, real-time statistics, and persistent data storage to reduce transcription errors and data loss during microscopy-based analysis.
Stack: Python · CLI · CSV · Data Validation · uv · Git
An interactive educational platform for molecular biology and genetics, developed to transform fundamental biological concepts into practical computational tools and visual learning experiences.
The application combines sequence analysis, DNA/RNA transcription and translation, ORF detection, mutation simulation, Mendelian genetics, Punnett squares, and NCBI BLAST integration within a modular Streamlit architecture.
Stack: Python · Streamlit · Biopython · NCBI BLAST · uv · Git
- Ph.D. in Cellular & Molecular Biology
- M.Sc. in Genetics and Applied Toxicology
- Biomedical Scientist
- University Professor
- B.Sc. Information Systems — currently enrolled
