Graduate Research Assistant,
Computer Science,
Marquette University
Computer Science,
Marquette University
ABOUT ME
Hello! I am Fayika Farhat Nova, a 5th-year graduate research assistant at Marquette University, Milwaukee, Wisconsin. I have completed my Master’s in Computing and am currently a Ph.D. candidate at Computer Science.
My research interest falls largely at the intersection of HCI and social computing where I analyze the objectives and motivations that drive individual's risky behaviors and victimization online, particularly for marginalized and at-risk populations. I specifically look at online harassment, sexual solicitation, and the mental health of gender and sexually minor (GSM) communities, teenagers, and young adults through mixed method approaches. Using computational methods (e.g. Machine Learning, Topic Modeling) and qualitative assessment (e.g. inductive and deductive thematic analysis) of rich data, I produce holistic understandings on human characteristics and behaviors during risky self-presentation and online interactions. Through my research, I also aim to develop actionable recommendations to improve the ways these understandings can be operationalized and propagated within the existing system design.
Currently, I am expanding my research to the healthcare domain to investigate how these online risky behaviors/lifestyles impact patient-related health services and assessment protocols in clinical settings. Specifically, analyzing data from patients' EHRs, I plan to connect digital signals about harassment to clinical assessment for better patient service and outcomes. My resesrch have been published/accepted in major conference venues including CHI, CSCW, GROUP and ICTD.
Currently, I am looking for potential 2022 internships as well as job opportunities where I will be able to incorporate my expertise in computational and qualitative data analysis and will be able to learn and grow professionally.
My research interest falls largely at the intersection of HCI and social computing where I analyze the objectives and motivations that drive individual's risky behaviors and victimization online, particularly for marginalized and at-risk populations. I specifically look at online harassment, sexual solicitation, and the mental health of gender and sexually minor (GSM) communities, teenagers, and young adults through mixed method approaches. Using computational methods (e.g. Machine Learning, Topic Modeling) and qualitative assessment (e.g. inductive and deductive thematic analysis) of rich data, I produce holistic understandings on human characteristics and behaviors during risky self-presentation and online interactions. Through my research, I also aim to develop actionable recommendations to improve the ways these understandings can be operationalized and propagated within the existing system design.
Currently, I am expanding my research to the healthcare domain to investigate how these online risky behaviors/lifestyles impact patient-related health services and assessment protocols in clinical settings. Specifically, analyzing data from patients' EHRs, I plan to connect digital signals about harassment to clinical assessment for better patient service and outcomes. My resesrch have been published/accepted in major conference venues including CHI, CSCW, GROUP and ICTD.
Currently, I am looking for potential 2022 internships as well as job opportunities where I will be able to incorporate my expertise in computational and qualitative data analysis and will be able to learn and grow professionally.
