Charlotte Pietrasiak

Analyzed large-scale transcriptomic datasets (60,000 genes/ sample) to model skin responses to perfumery active ingredients Designed Python/ R pipelines, integrating statistical modelling and machine learning ( classification/ regression) for molecular signature discovery Built interactive dashboards for data visualization and secure biological data management Software:R,Python,Pytorch,pandas,Matplotlib,Openai

Built a DIA-MS proteomics pipeline to analyze skin samples from atopic dermatitis patients Performed Limma differential expression analysis to identify proteins regulated after dermatological treatment Applied unsupervised ML (PCA, clustering) to uncover molecular patterns of skin barrier recovery and predictive biomarkers of therapeutic response Software:R,Python,pandas,Scikit-learn,R-shiny,

Hackathon (3rdPrize)

Built an AI-driven lab access management app(Gemini) for automated visitor authentication and security Developed an AI-guided virtual lab tour controlled navigation in restricted research areas Software:Appsheet,Gemini,GoogleMapsAPI