Art exhibit highlighting creative the creative talent of UConn Health Employees from across the organization.

"Expressions in Multimedia" by Martha G. Trask "Secondary Effects" by Jeff Ostergren Join us for a reception Thursday, May 22, from 4 to 6 p.m. in the Celeste LeWitt Gallery. (north side of the food court)Martha G. Trask is an expressive mixed media artist who happens to work in our library.Jeff Ostergren infuses his paint with actual medications to tell stories about the intertwined histories of pharmaceuticals and color.

For the full class schedule, descriptions, and to register, please visit the UConn Recreation website (https://recreation.uconn.edu/group-fitness-schedule/).

For new students only

ABSTRACT Guided by insights from fundamental cause, stress process, and critical race theories, the proposed three-paper dissertation aims to examine two understudied systems of stratification—structural xenophobia and digital divisions—and their roles in population health. Research has identified structural xenophobia, often operationalized as immigration policy climate, as a social determinant of poorer public health. Paper one advances literature on social stratification, immigration, and recently developed measures of structural systems to offer a novel multidimensional measure of structural xenophobia. Paper one extracts data from multiple sources (e.g., American Community Survey, Google, and governmental reports) spanning cultural, socioeconomic, medical, legal, and political spheres to generate a more comprehensive measure of state-level structural xenophobia from 2012 to 2019 based on approaches including factor analysis and latent class modeling. Preliminary results focusing on 2019 data produce one measure of structural xenophobia defined by six variables (i.e., immigrant poverty rate, immigrant labor force participation rate, and immigrant insurance coverage rate, anti-immigration policy climate, political representation of immigrants, Google search of anti-immigrant slurs) and shows the index has a marginally acceptable reliability of .61. Informed by fundamental cause and stress process frameworks, Paper two examines whether the newly developed measure of structural xenophobia is associated with state-level birth outcomes and mortality rates. Namely, Paper two expects that people in states with higher xenophobia will have poorer health outcomes, and even more so for racially marginalized populations, reflecting their greater exposure to stressors and reduced access to resources. Preliminary results, based on data from the Kaiser Family Foundation and the Centers for Disease Control and Prevention, indicate that high-levels of xenophobia in one year are associated with higher rates of low birthweight births three years later among Black and White populations, and to a larger degree for the former. Using data from the Federal Communications Commission, County Health Rankings & Roadmaps, and the National Health Interview Survey, Paper three proposes to examine how county-level digital divisions—operationalized as unequal access to quality internet—structures county-level preventative cancer screening, prior to, during, and after the increased digitalization induced by Covid-19. Specifically, this study identifies how shifting social environments shape dependency on digital tools and moderate the association between internet access and rates of mammogram screening. Furthermore, Paper three will employ individual-level data to examine possible mediating effects of information acquisition and provide empirical insights into intervention strategies to enhance information dissemination, and ultimately, increase cancer screening.

To learn more and register, please visit the link below. https://event.on24.com/wcc/r/4960035/7DF87930DE6A92EDBBCA84C896F3B8A7 (https://event.on24.com/wcc/r/4960035/7DF87930DE6A92EDBBCA84C896F3B8A7)

For the full class schedule, descriptions, and to register, please visit the UConn Recreation website (https://recreation.uconn.edu/group-fitness-schedule/).

Join staff from ISSS, Global Affairs, HR and Labor Relations and the UConn Health Center for a discussion on recent immigration updates for the university community. We will cover Travel Bans, Delays in Visa Processing, Social Media Vetting, and recent comments made by the Secretary of State regarding Visa Revocations and additional Visa Processing Scrutiny for certain students from mainland China and Hong Kong SAR.  

For the full class schedule, descriptions, and to register, please visit the UConn Recreation website (https://recreation.uconn.edu/group-fitness-schedule/).

For the full class schedule, descriptions, and to register, please visit the UConn Recreation website (https://recreation.uconn.edu/group-fitness-schedule/).

Let's Talk: Mental Health Office HoursWhat is it? The Let's Talk: Mental Health Office Hours program provides informal, confidential consultation with therapists from SHaW. Services are free of charge and offered on a first come, first served basis and are about 15-20 minutes. More info like dates, time and location can be found below. Clinicians provide support, coaching, and connect students to other campus resources as needed. Although therapists provide this service, it is not a substitute for formal counseling. The Let's Talk: Mental Health Office Hours program is also not suited to treat mental health emergencies; students who are experiencing a mental health crisis should see Crisis Support or Immediate Support Resources.Who is it for? Students who may benefit from attending a Let's Talk: Mental Health Office Hours session include: Students who want help connecting to resources but are unsure where to begin Students who are looking for advice on a non-clinical issue Students who are unsure about therapy and are curious about what it is like to talk to a therapist Students who may have concerns about the mental health of a friend and seek advice on how to support their friend If a student is not an imminent risk, and is refusing your support in contacting our office, you may also consider contacting the UConn Student CARE Team (https://studentcareteam.uconn.edu/). How is this program beneficial? Let's Talk: Mental Health Office Hours creates space for students to seek immediate support for non-crisis concerns. By doing so, we support students in need before they reach the level of crisis. Furthermore, Let's Talk contributes to our social justice mission by reducing barriers to mental health services for student populations who are less likely to seek formal mental health treatment. Provider:Fumi Sowah, LCSW (https://studenthealth.uconn.edu/person/olufumilayo-sowah/)

Electrical and Computer Engineering Department Title: Learning-Based Optimization and Control of Active Distribution Systems: Voltage Security, Cybersecurity, and Outage Mitigation   Abstract: Active Distribution Networks (ADNs) with high penetrations of inverter-interfaced Distributed Energy Resources require coordinated voltage control, outage resilience, and cyber-physical security. In this thesis the operational challenge is formulated as a constrained decision process whose state combines nodal voltages, power injections, load forecasts, and threat indicators, while the action space unifies inverter set-points, network-switch commands, and protection settings. Within this unified framework a distributed Volt–VAR optimizer—implemented with the actor–learner architecture on Ray RLlib—is trained across Monte-Carlo solar- and load-scenarios to sustain ±5% voltage compliance with sub-second convergence. The same decision-process formulation is extended with probabilistic storm forecasts, enabling a hybrid model-predictive/deep-reinforcement learning strategy that pre-positions storage and schedules switch operations, thereby reducing expected customer downtime by more than 60% in hurricane simulations. Building directly on the Volt–VAR control security, a two-stage cyber-defense pipeline safeguards the controller against data manipulation. First, a ResNet classifier augmented by explainable-AI examines streaming phasor measurements and large-language analysis of control logs to flag stealthy perturbations of inverter Volt–VAR curves in real time. Second, a Bayesian-optimized Stackelberg formulation leverages the same decision variables to prescribe counteractions and topology adjustments that restore voltage bounds under worst-case false-data injections, thus closing the loop between detection and mitigative control. The resulting secure and resilient framework is finally extended to islanded operation. Reduced-order dynamic models of grid-forming inverters, combined with safe deep-reinforcement learning, map admissible proportional–integral gains and co-optimize real and reactive power commands under explicit voltage, frequency, and power-sharing constraints. This agent admits only safe actions, enabling reliable black-start of multiple microgrids across uncertain load-pickup profiles and completing an end-to-end control architecture for tomorrow's inverter-dominated distribution systems.

Electrical and Computer Engineering Department Title: Learning-Based Optimization and Control of Active Distribution Systems: Voltage Security, Cybersecurity, and Outage Mitigation   Abstract: Active Distribution Networks (ADNs) with high penetrations of inverter-interfaced Distributed Energy Resources require coordinated voltage control, outage resilience, and cyber-physical security. In this thesis the operational challenge is formulated as a constrained decision process whose state combines nodal voltages, power injections, load forecasts, and threat indicators, while the action space unifies inverter set-points, network-switch commands, and protection settings. Within this unified framework a distributed Volt–VAR optimizer—implemented with the actor–learner architecture on Ray RLlib—is trained across Monte-Carlo solar- and load-scenarios to sustain ±5% voltage compliance with sub-second convergence. The same decision-process formulation is extended with probabilistic storm forecasts, enabling a hybrid model-predictive/deep-reinforcement learning strategy that pre-positions storage and schedules switch operations, thereby reducing expected customer downtime by more than 60% in hurricane simulations. Building directly on the Volt–VAR control security, a two-stage cyber-defense pipeline safeguards the controller against data manipulation. First, a ResNet classifier augmented by explainable-AI examines streaming phasor measurements and large-language analysis of control logs to flag stealthy perturbations of inverter Volt–VAR curves in real time. Second, a Bayesian-optimized Stackelberg formulation leverages the same decision variables to prescribe counteractions and topology adjustments that restore voltage bounds under worst-case false-data injections, thus closing the loop between detection and mitigative control. The resulting secure and resilient framework is finally extended to islanded operation. Reduced-order dynamic models of grid-forming inverters, combined with safe deep-reinforcement learning, map admissible proportional–integral gains and co-optimize real and reactive power commands under explicit voltage, frequency, and power-sharing constraints. This agent admits only safe actions, enabling reliable black-start of multiple microgrids across uncertain load-pickup profiles and completing an end-to-end control architecture for tomorrow's inverter-dominated distribution systems.

This initiative is part of our ongoing commitment to supporting students' sexual health and wellness throughout the summer. No appointment is necessary.Please note: The office will be closed on Tuesday, June 10.

For the full class schedule, descriptions, and to register, please visit the UConn Recreation website (https://recreation.uconn.edu/group-fitness-schedule/).

Graduate Students Interpersonal Groups focuses on promoting emotional wellbeing as you balance academics, relationships, family, and personal responsibilities. Groups offer a supportive confidential space to share your concerns, practice skills and get feedback. Provider: Carlos Gonzalez-Martinez, LCSW

For the full class schedule, descriptions, and to register, please visit the UConn Recreation website (https://recreation.uconn.edu/group-fitness-schedule/).

For the full class schedule, descriptions, and to register, please visit the UConn Recreation website (https://recreation.uconn.edu/group-fitness-schedule/).