
Cognitive science is the study of how intelligent beings (including people, animals, and machines) perceive, act, know, and think.
Cog Sci explores the process and content of thought as observed in individuals, distributed through communities, manifested in the structure and meaning of language, modeled by algorithms, and contemplated by philosophies of mind.
Cogs Sci draws from many disciplines, including psychology, linguistics, logic, computer science, anthropology, and philosophy. Models are tested using evidence from psychological experiments, clinical studies, field studies, computer simulations, and neurophysiological observation.
About the UCONN Cognitive Science Program
The Cognitive Science Program’s mission is to provide interdisciplinary, high-quality training to undergraduate and graduate students in the science of the human mind. We aim to be a hub for Cognitive Science education at the University of Connecticut by serving as the point of intersection for the diverse approaches and perspectives from the fields of psychology, linguistics, philosophy, neuroscience, anthropology, computer science, and speech and hearing sciences. Academic preparation includes theoretical and experimental foundations of cognitive science, and the opportunity for laboratory and field research. Our mission aligns with the institution and college missions of fostering innovative scholarship, diversity, and facilitating faculty-student interactions outside the classroom.
We support an undergraduate degree program (BA, BS, minor), a doctoral certificate program (open to non-degree students), and a colloquium series. The goal of the Colloquia is to create a forum for common intellectual exchange between students and faculty affiliates on a diverse range of topics within the field of Cognitive Sciences.
Announcement: The Cognitive Science Graduate Certificate is now open to UConn students and continuing education students. Please see the Graduate Certificate webpage for more information.
Upcoming Events
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Sep
26
MCB Seminar Series: Dr. Tara McAllister 3:30pm
MCB Seminar Series: Dr. Tara McAllister
Tuesday, September 26th, 2023
03:30 PM - 04:30 PM
BPB 130
Dr. Tara McAllister, Research Fellow, Victoria University of Wellington, Wellington, New Zealand
Host: Dr. Kat Milligan-McClellan
“Formidable Phormidium: toxic cyanobacteria in New Zealand rivers”
Summary: In this seminar, Dr McAllister will explore the physicochemical factors that lead to toxic benthic cyanobacterial blooms in New Zealand rivers. She will present the findings of two experiments that collectively aimed to understand the effects of nutrients and velocity on Phormidium growth
Bio: Dr Tara McAllister (Te Aitanga a Māhaki) is an Indigenous scientist, interdisciplinary scholar and a mother. She is currently a Research Fellow at the School for Science in Society at Te Herenga Waka — Victoria University of Wellington in New Zealand. She holds a PhD in Water Resource Management from the University of Canterbury and has expertise spanning freshwater ecology and racism in higher education.
Publication: The rise of toxic benthic Phormidium proliferations: a review of their taxonomy, distribution, toxin content and factors regulating prevelance and increased severity. -
Sep
26
Pet Therapy 5:00pm
Pet Therapy
Tuesday, September 26th, 2023
05:00 PM - 07:00 PM
Cordial Storrs House
SHaW is hosting Pet Therapy every Tuesday from 5pm - 7pm at the Cordial Storrs House.
Stop by for some pet therapy love!We’ve also partnered with the The Benton to host Pet Therapy every first Thursday of the month!
Join us in The Benton from 4:30 – 6:30 p.m.Please note that Pet Therapy is provided on a volunteer basis. We cannot guarantee that dogs will be present the entire time.
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Sep
27
Social Psychology Speaker Series 2:00pm
Social Psychology Speaker Series
Wednesday, September 27th, 2023
02:00 PM - 03:15 PM
Bousfield Building
Dr. Flora Oswald, University of Connecticut
Social perceptions and experiences among marginalized group members: Implications for intergroup disparities
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Sep
27
STAT Colloquium, Prof. Sujit K. Ghosh 4:00pm
STAT Colloquium, Prof. Sujit K. Ghosh
Wednesday, September 27th, 2023
04:00 PM - 05:00 PM
Austin Building
Professor Sujit K. Ghosh, Ph.D.
Department of Statistics
North Carolina State UniversityRecipient of the 2023 UConn Statistics Department
Distinguished Alumnus AwardNonparametric Estimation of Multivariate Copula using Empirical Bayes Method
In the field of finance, insurance, and system reliability, etc., it is often of interest to measure the dependence among variables by modeling a multivariate distribution using a copula. The copula models with parametric assumptions are easy to estimate but can be highly biased when such assumptions are false, while the empirical copulas are non-smooth and often not genuine copula, making the inference about dependence challenging in practice. As a compromise, the empirical Bernstein copula provides a smooth estimator, but the estimation of tuning parameters remains elusive. In this paper, by using the so-called empirical checkerboard copula, we build a hierarchical empirical Bayes model that enables the estimation of a smooth copula function for arbitrary dimensions. The proposed estimator based on the multivariate Bernstein polynomials is itself a genuine copula, and the selection of its dimension-varying degrees is data-dependent. We also show that the proposed copula estimator provides a more accurate estimate of several multivariate dependence measures, which can be obtained in closed form. We investigate the asymptotic and finite-sample performance of the proposed estimator and compare it with some nonparametric estimators through simulation studies. An application to portfolio risk management is presented, along with a quantification of estimation uncertainty. [This presentation is based on a joint work with my former student Dr. Lu Lu]
DATE: Wednesday, September 27, 2023
TIME: 4:00 pm
PLACE: AUST 110
WebEx: https://uconn-cmr.webex.com/uconn-cmr/j.php?MTID=m44f5da414545274b83c84dec11d638d5
Coffee will be served 3:30-4:00 in the Noether Lounge (AUST 326)