His research primarily focuses on how language can provide insights into a person’s personality, including their values, experiences, and motives. He has taught several workshops on language analysis, machine learning, and research methods. Ryan is currently a member of several research labs at the University of Texas at Austin and is a data scientist for the ShadowLAB project, as well as Receptiviti. His work has been featured in places such as CNN, the BBC, and NPR, and he is widely recognized as a leading expert in the area of automated psychological language analysis. Ryan is also the developer/designer of several software applications for text analysis, including the Meaning Extraction Helper, LIWC2015, and TAPA, to name a few. His favorite food is pizza, he loves coffee, and he has a dog that is objectively the best dog in the universe.