Daniela Bolaños Garcia

- Product owner (and ownership) of computational pipeline and Desktop app for helping clinicians and researchers to process ultrasound data and perform data analysis for different datasets and different systems. Work presented at: https://www.eventclass.it/emim2026/scientific/online-program/poster-session?s=PW-10#e755

• Conducted bioinformatics enzyme research at Roche, utilizing wet and dry lab techniques for data analysis and protein engineering. • Applied validation technology and statistics in enzymology analysis for drug discovery and diagnosis purposes. • Plugin development in Geneious Software to improve time processing of enzyme candidates to further downstream processing analysis.

• Conduct exploratory data analysis on MRI datasets, applying statistical methods and dataset balancing techniques. • Develop statistical models and machine learning techniques to enhance segmentation accuracy and predictive performance. • Research and present innovative MRI techniques to the team, contributing to workflow improvements. • Implement automated biomarker data processing pipelines in Python and Linux. • Perform data annotation and labeling to generate high‑quality training datasets for AI‑drive

• Conduct biomarker-driven statistical analysis of longitudinal neuroimaging data, focusing on cerebral blood flow. • Develop and maintain a scientific database and automated Python, MATLAB and Bash pipelines. • Compare brain features and collaborate with scientists and clinicians. Publication: https://www.researchgate.net/publication/385349347_Cerebral_perfusion_Magnetic_Resonance_Imaging_reveals_significantly_lower_cerebral_blood_flow_in_very_preterm_compared_to_term-born_adults

• Focus: Biomedical Data Analysis, Computational Modeling, AI in Medical Imaging & Biomarker Research • Thesis: Study of Brain Perfusion and Metabolism Impairments in Very Preterm Born Adults Using Magnetic Resonance Imaging (Accepted at ESMRMB 2024, Spain) • Key Skills: Statistical Analysis, ML for Biomarker Discovery, Data Processing Pipelines (Python, R, MATLAB) • Relevant Courses: Biostatistics, Advanced AI in Medicine, Computational Biology, MRI courses, Theranostics, Radioactivity, Medical Augmented R

Physics department.

• Developed and validated analytical methods for pharmaceutical products using HPLC and GC, ensuring precise and accurate results critical for regulatory compliance and quality assurance. • Authored comprehensive protocols and reports for method validation and analytical transfer, facilitating seamless handover to the Quality Control department. • Collaborated with cross‑functional teams, including formulation scientists and regulatory affairs, to optimize product development and ensure compliance with indu

• Designed and executed HPLC and GC experiments to improve the formulation of pharma, nutrition, and oral care products, ensuring high efficacy and consumer safety. • Led the development and optimization of disinfection and oral health products, focusing on antibacterial and antiviral efficacy, including solutions relevant to the COVID‑19 pandemic. • Validated analytical methods for new product formulations, utilizing advanced techniques to achieve high‑quality and reproducible results. • Worked closely wit

• Conducted rigorous quality control testing of raw materials, in‑process samples, and finished products, using validated analytical methods to maintain product integrity. • Standardized and prepared solutions for routine analysis, ensuring consistent and reliable results for the quality assurance process (INVIMA regulations). • Managed documentation and compliance with regulatory requirements, contributing to the company’s adherence to Good Manufacturing Practices (GMP). • Participated in the investigation