Jon.Landrigan@gmail.com CV

Currently I am a fellow at Insight Data Science a program that helps individuals transition from academia to data science. While at Insight I worked with the company Sown To Grow to develop Teacher's Aid: A NLP tool to help teachers evaluate student work (for a brief post about this project click here).

While in graduate school at Drexel University I worked under the mentorship of Dr. Daniel Mirman and Dr. Zoe Zhang. During this time I gained a vast amount of experience using both quantitative and qualitative methods. For example I worked with varying types of data including but not limited to neuroimaging data, pscychological assessments, surveys and text data. I also used a number of different techniques to garner insights from this data including the use of clustering algorithms (e.g. community detection analysis) and predictive models such as random forest classifiers and neural networks. Further I also developed a number of behavioral experiments examining varying aspects of cognition.

My dissertation "Exploring Aphasia Using Community Detection Analysis and Machine Learning" combined a number of these techniques in order to re-examine the traditional aphasic diagnoses. I first used community detection analysis on a large dataset to cluster patients and then not only compared the lesion maps associated with patients in these clusters but also predicted patient cluster membership and/or deficits based solely on their lesion data.