More Steps in Coding: Reliable, Reusable, Understandable Code

Description

Convenor: Lidea Shahidi (CDH Methods Fellow)

Code in research helps to automate the collection, analysis or visualisation of data. Although the code may fulfil your research objective, you might have wondered how to improve it, code more efficiently, or make it ready for collaboration and sharing. Perhaps you have experienced challenges with debugging or understanding it.

In this intermediate workshop, we will introduce several coding design principles and practices that ensure code is reliable, reusable and understandable, enabling participants to take their code to the next level.

The workshop will begin by introducing the key concepts using ample examples. Participants will then work in groups to apply the concepts either to code provided by the convenor or to their existing projects, with guidance from the convenor. Participants will also have the opportunity to discuss their project goals with the convenor to demonstrate how the best practices can be implemented during the coding process.

This workshop is for individuals who have some prior experience with Python and who, ideally, have a coding project that they wish to work on. Participants are encouraged to arrive with a specific objective or desired output for their coding project. For example, you might wish to pre-process your data, add a specific analysis to your project, or make your code publicly available.

If you are interested in attending this course, please sign up and fill in the pre-course questionnaire to confirm your place. Places will be prioritised for students and staff in Arts & Humanities, Humanities & Social Sciences, libraries and museums. If you study or work in a STEM department (e.g. Geography) and use humanities or social sciences approaches you are also welcome to join.

About the convenor: Lidea Shahidi is a postdoctoral research associate based at the MRC Cognition and Brain Sciences Unit.  She studied for her PhD in the Applied Machine Learning Lab in the Electrical and Computer Engineering department at Duke University, where she developed speech enhancement strategies to mitigate the impact of reverberation on speech intelligibility outcomes for cochlear implant recipients. Prior to her PhD, she studied cell and molecular biology at the University of North Carolina at Chapel Hill, where she earned a Bachelor of Science degree in Biology.

Lidea’s current research investigates novel cochlear implant speech coding strategies, with the aim of improving clinical outcomes for cochlear implant recipients. This work involves computational analyses and behavioural experiments to measure speech perception and psychoacoustic phenomena, with the aim of understanding the mechanisms by which coding strategies may improve the transmission of speech information to the auditory nerve. Outside of cochlear implant research, her research interests include auditory scene analysis, speech enhancement, and speech processing. She has taught several lectures and workshops on programming, command line tools, psychoacoustics, and signal processing.