I'm a Data Scientist with a PhD in Bioinformatics and over 7 years of experience applying machine learning and genomics technologies to advance life-science research. My work spans high-content image analysis, genomics data, and developing AI/ML models for biological systems. I love tackling complex problems in bioinformatics and collaborating across diverse teams to drive innovation in data science and structural biology.
- 🧬 Current Role: Postdoctoral Fellow at Johnson & Johnson, working on AI/ML models for drug-induced liver injury (DILI) using high-content image and omics data.
- 📊 Skills:
- Programming: Python, R
- Data: PostgreSQL, data mining, manipulation & visualization
- Machine Learning, Genomics, Bioinformatics, Image Analysis
- Version Control: Git
- Structural Biology, Project Management, Scientific Publishing
- 👯 I’m interested in collaborating on:
- Bioinformatics, data science, and genomics research
- AI/ML projects, especially related to healthcare and drug discovery
- 🌱 Currently honing my skills in advanced AI and omics.
- High-dimensional phenotypic profile analysis using machine learning (Cell-Painting, transcriptomics data)
- Building scalable data pipelines for clinical and epidemiological data integration
- AI/ML applications in metabolic engineering and drug discovery
- RNA-seq data analysis for cancer research, including discovery of long intergenic non-coding RNAs (lincRNAs)
- Flux prediction using artificial neural network (ANN) for glycolysis optimization PLoS ONE 2019
- Machine learning for enzyme concentration optimization in metabolic pathways Catalysts 2020