DEVDEEPTA BOSE, Postdoc
Devdeepta Bose is a Postdoctoral Scholar in Economics and Psychology in the Camerer Team. He holds a PhD in Economics from the University of Arizona, an MS in Applied Economics from the University of Michigan, and a B.Eng in Electrical Engineering from Nanyang Technological University, Singapore. Devdeepta uses a combination of eye-tracking, machine learning, laboratory and field experiments to study how people make sub-optimal choices in different economic decision-making environments, ranging from consumer purchases in the supermarket to asset purchases in financial markets. He is interested in how social preferences inform equilibrium selection in infinitely repeated games, and how adaptive design can be used to infer social preferences in representative populations.
TANAZ MOLAPOUR, Postdoc
Tanaz Molapour is a Postdoctoral Scholar in Computational Affective Science in Colin Camerer and Dean Mobbs’s labs. She holds a PhD in Clinical Neuroscience from Karolinska Institutet in Stockholm. Tanaz has a background in neurocognitive mechanisms of emotional learning in social situations. She uses a combination of brain imaging, psychophysiological and behavioral measures to investigate how people perceive threats in social interactions and how it influences behavior. Currently she is interested in understanding how social networks are formed, and how behaviors (e.g., punishments) are spread within the network.
BOWEN J FUNG, Postdoc
Bowen J Fung is a Postdoctoral Scholar in Computational Affective Science, working both in the Camerer Lab and in Dean Mobbs Lab. He holds a PhD in Cognitive Science from the University of Melbourne. Bowen has a broad background, with expertise in neuroeconomic decision-making processes (e.g. temporal discounting), psychophysiology, behavioural ecology (e.g. foraging), and time perception. He is currently interested in how affective states (e.g. frustration) can be reconciled with models of reinforcement learning, and uses a range of state-of-the-art techniques to address this question.
XIAOMIN LI, PhD Student
Xiaomin Li is a fifth year PhD student in the Social and Decision Neuroscience program at Caltech. She holds a M.A. in Economics from NYU, and a B.S. in Finance from Shanghai University of Finance and Economics. Currently, she is trying to understand strategic decision making through various methods: behavioral data, eye-tracking, or brain recordings. She is also interested in single choice decision making broadly related to economics and is open to any relevant future projects.
ANASTASIA BUYALSKAYA, PhD Student
Anastasia Buyalskaya is a third year PhD student in the Social and Decision Neuroscience program at Caltech and a Chen Graduate Fellow. She holds an MSc in Economics and Stategy for Business from Imperail College London, and a BA in Economics and Interdisciplinary Studies from Hunter College in New York City. Anastasia studies the neural and physiological mechanisms which underpin economics decision making. Her current research includes an empirical analysis of habit formation and an experimental analysis of optimal mechanisms to reduce cheating behavior.
MARCOS GALLO, PhD Student
Marcos Gallo is a second-year Ph.D. student in the Social and Decision Neuroscience program and a Chen Graduate Fellow. He has a background in Economics, including an MSc from Shanghai Jiao Tong University. Marcos’s motivation to research the neuroscience of poverty and discrimination directly stems from his experiences growing up in a disadvantaged neighborhood in Brazil. When he started his studying at Brigham Young University, he became determined to dedicate his career to helping inform and create effective policies to lift those in poverty. Marcos is fluent in Portuguese, Spanish, English, and Mandarin Chinese. When he is not working in the lab, he sings in a gospel choir, experiments with cooking, learns contemporary dance, and weightlifts.
VIRGINIA FEDRIGO, Research Assistant
Virginia Fedrigo is a research assistant with the Camerer Team. She graduated with an M.Sc. in Neuroeconomics from Maastricht University, The Netherlands. Previously, she double majored in Cognitive Science and Molecular Biology at the University of California, San Diego. She is broadly interested in exploring how economic models and behavioral insights (gained from both laboratory and field experiments) can be applied to deepen our understanding of behavior traditionally perceived as irrational.
Irene Chang is an intern with the Camerer group studying CS and BEM at Caltech, in the class of 2022. She is also involved in student government at Caltech, a peer advocate, and social media manager for the Caltech Y. With diverse skills and interests, she helps in a variety of ongoing projects within the lab–such as building this website, researching habit formation and healthy eating, and emotional profile in regards to horse race betting.
Tads Ciecierski-Holmes Holmes is a CamSURF student. He is entering the final year of the B.A. in Economics at St John’s College, University of Cambridge, UK. During his time at Cambridge, he contributed to various charities and student societies focused on charity fundraising and international development, including working on health education interventions in Tanzania with the Cambridge Development Initiative. He is interested in exploring the applications of behavioural economics and datascience in Health Economics. His 2019 SURF project is revisiting the intertemporal choice problem in the context of exercise habits. Namely, finding ‘irrational’ behaviours in gym membership data and investigating possible explanations for these behaviours. He is also helping to draft a new medication adherence intervention using an arsenal of targeted behavioural and information based interventions.
Tony Kukavica is a Rose Hills Foundation SURF Fellow. He is a rising third-year undergraduate double-majoring in mathematics and economics at Caltech. He is also the concertmaster of the Caltech Symphony, a first violinist in the American Youth Symphony, President of the Caltech Chess Club, and a National Chess Master. His SURF project concerns the use of reinforcement learning algorithms to investigate whether habit-based “model-free” actions can be statistically predicted by a carefully selected range of state variables.
Yanrong Xu received the Degree of Bachelor of Science with a joint major in Mathematics and Economics from University of California, San Diego. He is interested in the neuroscientific foundations that could affect people’s behavior and economic decisions.
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