Directory

Sterling Williams-Ceci is a PhD Student in Information Science focusing on the intersection of human-computer interaction and social psychology. She researches how cognitive biases impact people's perceptions of trustworthiness in modern and unfamiliar information-seeking contexts. Prior to the PhD, Sterling graduated as a Merrill Presidential Scholar from Cornell University with a B.A. in Psychology and a B.A. in the Robert S. Harrison College Scholar Program for interdisciplinary research.

Talia Wise is a PhD student focusing on human-centered AI and augmented cognition. She studies how interactions with information systems affect higher-level cognition, and how a deeper understanding of these processes can inform the study and design of new systems to assist in cognitive tasks such as creative ideation or writing. Prior to joining Cornell, she did her undergraduate work in Computer Science and Liberal Arts at McGill University in Montreal followed by an MSc from the Technion in Haifa where she researched human-machine co-creativity.

Areas of Interest: Human-Computer Interaction, Creativity support, Augmented Cognition, Human-centered AI, Natural Language Processing

Xinyu Yang is an Information Science PhD student at Cornell University. Her research interest lies in Science of Science, Computational Social Science and AI for the common good. She is also broadly interested in exploring applied cutting-edge machine learning and data science methods. Currently, she focuses on conducting large-scale data analyses using advanced computational and machine-learning techniques. Prior to joining Cornell, Xinyu got her bachelor's degree in Computer Science and Technology from Zhejiang University, China.

Olzhas Yessenbayev is a Ph.D. student in Information Science at Cornell University. His research passion lies at the intersection of cognitive sciences and HCI, with an emphasis on leveraging cognitive and biological affordances to elevate health technology design. In terms of sensing, he is dedicated to understanding the capacity of passively sensed markers to accurately model and predict our cognitive states. In terms of behavior change, he explores ways to modulate these cognitive states by engaging with semi-voluntary physiological mechanisms seamlessly, through creation of subtle interfaces. For instance, he has incorporated feedback into video-watching experiences to subtly guide eating rates, and used peripheral vision as an avenue of sensory input processed almost automatically by another such interface. These methods aim to craft interventions that seamlessly integrate with users' natural behaviors, fostering effective yet unobtrusive behavior modifications. He is currently under the guidance of Professor Rajalkshmi Nandakumar at Cornell.

Areas of Interest: HCI, Mobile Sensing, Health, Cognitive Sciences, Affective Computing