Prabhleen’s Ph.D. research focuses on applying statistical network analysis methods on animal GPS radio-telemetry data to understand the causes and consequences of social interactions amongst the animal community. In addition, Prabhleen is utilising agent-based modelling techniques for simulating animal movements. Her research has given her a deep understanding of network statistics and data science applications on large data sets. Furthermore, her work involved exposure and extensive work with programming languages such as R, Python, and C++. Prabhleen’s passion for conveying mathematics/statistics to a broader audience has motivated her to develop an R software package, aniSNA. aniSNA serves as a ready-made toolkit for ecologists, allowing them to apply the novel methods described in her research to their respective animal social network studies. Prabhleen desires to continue on this path and leverage her mathematical-statistical analysis skills acquired through her double Masters and Ph.D. experience to solve technical challenges.

Areas of Interest: Network analysis, Natural language processing, Applications of data science in ecology, education and business intelligence.

Thesis Title: Statistical network analysis of animal societies

12 week training placement: Analysis of customer accessibility feedback through knowledge graph embeddings, Microsoft.

I got an amazing opportunity to work with the data science team led by Principal data scientist Cathal O’Connor at Microsoft, Ireland. The aim of the project was to build a modern graph-based pipeline and models to better understand the inclusion technology needs of people in the area of vision, hearing, neurodiversity, learning, mobility and mental health. Based on the latest academic research, the solution solved natural language processing tasks using multilingual knowledge graph embedding based techniques and detected market specific anomalous clusters across markets and languages including trends and shifts.
Deliverables – Documented Code (GitHub), Interactive dashboard (Using Plotly, Dash in Python)

International Placement: Agent based modelling to simulate animal movements.
I completed a three month research placement at the University of Zurich, Switzerland working in the lab of Dr. Damien Farine. I collaborated with a team of ecologists in order to gain a better understanding of animal behaviour and approach things from an ecological perspective which empowered me to build statistical models for agent based simulations.

Professional Links:
LinkedIn: linkedin.com/in/prabhleen-kaur-963b8a197
GitHub: https://github.com/PrabhleenKaur19
Preprint : https://www.biorxiv.org/content/10.1101/2023.03.30.534779v1