Data Science | Machine Learning Engineer | PhD in Bioinformatics
Transforming complex data into clear, actionable insights through machine learning solutions and intelligent visualization.
13+ years of experience in research and industry. My academic background in computer science and statistics provides me with a solid foundation to transform complex data into clear, compelling narratives. I am highly proficient in Python, data visualization, and machine learning, with extensive experience in integrating and analyzing large-scale datasets.
Transformed complex datasets into actionable insights using statistical analysis and visualization techniques. Experience with large-scale data processing and analysis in both research and industry settings.
Built robust, scalable applications using modern software engineering practices. Proficient in multiple programming languages and frameworks.
Designed and implemented end-to-end ML solutions for various domains, from genomics to climate prediction. Experience in PyTorch, TensorFlow, and modern MLOps practices for scalable deployments.
Led cross-functional teams and managed complex projects from conception to delivery in international environments.
Led groundbreaking research in genomics, proteomics and 3D modeling of macromolecules, resulting in high-impact publications. Developed novel algorithms for spatial data analysis and contributed to international collaborations.
Passionate about knowledge sharing and mentoring. Experience in teaching advanced concepts in bioinformatics, machine learning, and programming to diverse audiences.
Key Achievements:
My passion lies in solving complex challenges through technology and innovation. I'm always eager to learn and apply new approaches to meaningful problems. I'm particularly interested in projects that can make a positive impact, especially in sustainability. I thrive in collaborative environments where continuous learning and open feedback are part of the culture.
Core Technologies:
ML/AI:
MLOps: