Richmond Upon Thames, England, United Kingdom
Senior Data Scientist at bp. PhD in Theory and Simulation of Materials (Computational Physics).
An intensive two-week course which covered a range of machine learning tools and methods including: • pandas, seaborn, scikit-learn, xgboost, and pytorch • data preprocessing • dimensionality reduction • classification, regression, and clustering • decision trees, random forests, boosting, (recurrent) neural networks, and reinforcement learning
• Developed (Recurrent) Neural Networks with PyTorch for text analysis. • Utilised clustering algorithms (Gaussian mixture models and k-means) in combination with Deep Learning to gain insights into customer comments.
• Supervised a 5-week-long MATLAB/Python project for 20 second year undergraduate students. - Prepared and scheduled weekly meetings with students. - Taught basic principles of procedural programming. - Supported the students by monitoring their progress, advising them on project planning and management and providing regular individual feedback. • Assisted undergraduate students during practical exercises in the first and second year MATLAB course. - Explained basic coding concepts and MATLAB functionalities. • Tutored 24 first year students in their Mathematics and Computing course. - Planned and conducted hour-long tutorials for four groups of six students. - Marked homework and gave individual written and oral feedback. - Identified and revised the mathematical concepts the students struggled with. • Marked weekly coursework assignments of eight MSc students and planned and delivered hour-long feedback sessions to discuss their answers.