I am a data scientist with a PhD in Electrical Engineering and expertise in machine/deep learning, statistical analysis, and probabilistic modeling. My current research focuses on developing predictive models for medical applications, such as cardiac motion modeling and reconstruction of 3D+t CT volumes from 2D+t X-ray projections acquired during radiotherapy. I have experience analyzing large-scale population datasets and utilizing various data analytics techniques to extract insights from complex data.
I am an enthusiastic learner and always open to exploring new technologies and approaches. In addition to my expertise in Python programming (with PyTorch, Keras, NumPy, Pandas, ...), I also have experience with MATLAB and Simulink.
- Software development within Python and MATLAB
- Object-oriented programming
- Machine learning (Scikit-learn, PyTorch, Keras)
- Natural Language Processing (NLP) (SpaCy)
- Data cleaning, transformation, and manipulation (NumPy, Pandas)
- Data visualization (Matplotlib, Seaborn)
- Computer vision (OpenCV)
- Source version control (Git)
I am passionate about using my skills to solve real-world problems and always looking for opportunities to collaborate with others in the field. Feel free to reach out to me for any data science-related inquiries or collaborations.