Does the style of language you hear help persuade you? Does texting with friends influence whether you vote or not? Will it be
These are the types of questions that interest Dhanya Sridhar, a new assistant professor in the Department of Computer Science and Operations Research at the University of Montreal.
Experts in causality and machine learning, researchers at the Mira-Québec Institute for Artificial Intelligence have always had a keen interest in the underlying patterns of human behavior.
“I have always been very interested in understanding why complex behaviors and systems emerge, and learning about what motivates people to do what they do.
Such scientific questions require reasoning about cause and effect, but it is not always possible to determine causality. In her work, Sridhar uses large-scale data and machine learning to uncover possible causal variables and analyzes these data using causal mathematical tools.
In doing so, her goal is to understand, not just predict, the scientific phenomena that govern our lives.
“I am excited about the possibilities of using machine learning and big data to answer and study more causal questions that affect people’s lives and health,” she said. “This is a long-term project, but it would be great if we could demonstrate that these methods can provide solutions to pressing problems.”
Her current research at UdeM and Mila focuses on fundamental research to combine causality and machine learning to build artificial intelligence that is more robust and useful for discovering scientific knowledge.
Postdoctoral and doctoral studies (Columbia University and University of Southern California, Santa Cruz) focused primarily on the application of computational social sciences to language and speech.
american in montreal
Having always enjoyed languages, she is now able to apply this knowledge to her own life.
Since moving to Montreal from New York City for a new job, Sridhar, an American citizen, has been learning French and enjoys the opportunities to speak and write in it in everyday life in the city.
While teaching students and graduate students, Sridhar seeks to foster independent thinking. She prefers an approach of teaching techniques that her students can develop on their own, rather than repeating formulas that must be learned by rote rote.
“I want my students to feel as creative and independent as possible,” she said. “Research and graduate school are never easy environments, but if you have a deep understanding of the field and the ability to make connections, I think you will be able to acquire the ability to deal with setbacks in the future.”
Professors are always striving to better understand what they are teaching and, whether in courses, lectures or scientific publications, they try to explain concepts as simply as possible.
“Experience has shown me that the deeper I understand a subject, the clearer I can explain it. It is important.”