2022-2023 Cohort

Rosa Bermejo
Rosa.bermejo@stonybrook.edu
Psychology, Social & Health
Dr. Bonita London

Rosa is a graduate student in the Social and Health Psychology department at Stony Brook University. She received her BA in psychology from Hunter College, CUNY. Her research interests involve discrimination experiences and the wellbeing of racial minorities. Specifically, she is interested in how different racial discrimination experiences affect the academic and psychological wellbeing of Black and Latinx students. 

Karin Hasegawa
karin.hasegawa@stonybrook.edu
Applied Mathematics & Statistics
Dr. Yuefan Deng

Karin is a third-year PhD student in Applied Mathematics and Statistics working with Professor Yuefan Deng. Her research interests lie in the field of high-dimensional statistics with applications to deep learning, and molecular dynamics simulations of viruses.

Pei-Hsun Hsieh
pei-hsun.hsieh@stonybrook.edu
Political Science
Dr. Reuben Kline

Pei-Hsun is a Ph.D. candidate in political science at Stony Brook University. His research interests lie at the boundary of political economy, behavioral economics, and political behavior. His research focuses on how social preferences and beliefs affect collective decision-making, collective actions (e.g., mitigating public health crises and climate change), and redistributive policies. He uses a variety of methods, including experiments, machine learning, and agent-based modeling.

Kalina Kostyszyn
kalina.kostyszyn@stonybrook.edu
Linguistics
Dr. Jeffrey Heinz

Kalina Kostyszyn is a Ph.D. student in the Linguistics department at Stony Brook University, advised by Jeffrey Heinz. She graduated in 2017 from Bryn Mawr College with a B.A. in Computer Science and Linguistics, and was a visiting scholar in Linguistics at the University of Delaware for a year before coming to Stony Brook. Her research is on phonology, morphophonology, and computational modeling of these processes. She also has worked on improving computational literacy with high schoolers, to better prepare them for a world influenced by AI.

James May
james.may@stonybrook.edu
Psychology, Cognitive
Dr. Susan Brennan

James is a first-year PhD student in Psychology. He is interested in how people use language to effectively communicate with one another. He is also interested in learning about ways to ameliorate harmful effects of bias in big data and AI.

John Murzaku
jmurzaku@cs.stonybrook.edu
Computer Science
Dr. Owen Rambow

John is a 2nd year Computer Science Ph.D. student advised by Dr. Owen Rambow. His main research interests are in modeling belief, sentiment, and the respective holder or targets of these beliefs or sentiments. He is also interested in exploring annotation bias in belief/event factuality corpora and bias in large language models fine-tuned on belief/factuality corpora.

Veronica Oelerich
veronica.oelerich@stonybrook.edu
Political Science
Dr. Reuben Kline

Veronica is a PhD student in the Department of Political Science at Stony Brook University. Her research adopts a political psychological approach to studying public opinion regarding the criminal justice system, ranging from racially motivated reasoning about police brutality to public opinion on AI as it is used in predictive policing. 

Sekine Ozturk 
sekine.ozturk@stonybrook.edu
Psychology, Clinical 
Dr. Aprajita Mohanty

Sekine is a third-year student in the clinical psychology Ph.D. program. Her overarching research goal is to elucidate the mechanisms by which emotions impair or facilitate cognitive processing in transdiagnostic populations. She uses neuroimaging, computational modeling, machine learning and behavioral paradigms to answer her research questions. Better understanding the underlying mechanisms of cognitive and emotional processing may inform evidence-based clinical interventions. Her primary research advisor is Dr. Aprajita Mohanty. 

Amie Paige
amie.paige@stonybrook.edu
Psychology, Cognitive
Dr. Susan Brennan

Amie Paige is a cognitive PhD student whose work is focused on using psycholinguistic approaches to examine complex, interactional situations. She graduated with a BA in Psychology in 2013 from Texas A&M University-Commerce before working for a Fortune 50 company as an data analyst. During her time in industry, she developed the technical acumen to analyze trends within big data, presented strategy recommendations to upper leadership, and observed the ways that biases shaped mindsets at all levels within the organization. Such observations inspired her to return to school to earn her MS in Psychology. Her research focused on examining linguistic behaviors within diverse collaborations and using machine learning techniques to study how language influences judgments of others. She left her industry role to pursue a PhD at Stony Brook University where she now studies how language is shaped by the constraints of speaker needs, listener needs, and situations. She hopes to continue to explore the roots of bias and ways of detecting it within language. Passionate about the power of data science, she aspires to use her training as a social scientist to improve educational and industrial spaces.

Medhini Urs
medhini.urs@stonybrook.edu
Psychology, Cognitive
Dr. Christian Luhmann

Medhini is a graduate student in Cognitive Science at Stony Brook University. She received her BS in Psychology from Florida Southern College. Her research interests include investigating the cognitive factors behind economic and social decision-making.

Carl Wiedemann 
carl.wiedemann@stonybrook.edu
Psychology, Social & Health
Dr. Antonio Freitas

Carl Wiedemann is a Ph.D. student in the Social and Health Psychology Doctoral Program at Stony Brook University. In 2019, he graduated from the University at Buffalo with a B.A. with Honors in Psychology, and minors in Philosophy and Counseling. Across separate investigations, Carl has studied bias in political ideologies, bias in information sampling, and bias in self-perceptions. Currently, he works in the Self-Regulation and Cognition Lab under the mentorship of Dr. Antonio Freitas. Carl’s ongoing research projects focus on the relationship between how people consider the future consequences of their actions and the subjective experience of behaving automatically. Automatic responses tend towards stereotyped judgements. Thus, a primary goal of Carl’s research is to identify psychological and contextual factors which can buffer against biased behavioral responses to situational cues. As Carl continues through his doctoral training, he is eager to gain formal education in computer science techniques through the BIAS-NRT program, which will grant him the tools necessary to continue addressing novel questions about the effects of bias on human behavior and perceptions.