Mir Pias

Algebra, Geometry and Computer Algebra group (AGAG). Tech Stack: Python 3, Django, PostgreSQL Developed a web interface for querying the number fields database to look up polynomials, used internally in the department. Also built a Postgres database from the JSON files in GenericDecMats.jl, and a prototype web interface for querying the database to look up matrices.

Dept. of Social Science, Tech Stack: Matlab, Python, Pandas, MS Excel, MS Powerpoint. Pre-processed and visualized data collected from perception experiments conducted with participants. Created stimuli for use in conducting experiments. General IT maintenance.

Tech stack: Python, Pandas, Scikit-learn, Matplotlib. Pre-processed, visualized, and analyzed time-series data from a production line in a factory to determine if a relationship exists between different types of alarm occurrences. Analysis methods: Hierarchical clustering, Pearson correlation, conditional probability analysis.

Tech Stack: Matlab Conducted a comparison of cascade learning and deep learning performance for detecting number plates from a dataset of vehicle images. Together with my supervisors, I authored a paper summarizing our findings, which we subsequently published at the CBMI 2017 conference.

Specialising in Intelligent Systems