Master Calendar

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/).

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/).

Panelists will center their traditions' shared ground and offer insights for the general academic community and public. While many participants will have strong political positions, the goal of this meeting is not ideological. Its focus is co-learning and productive discussion of their research in Advanced Black Jewish Studies. Please RSVP by April 22ndConvenersLewis R. Gordon and Adane Zawdu Gebyanesh ParticipantsDr. Fekade Abebe, Postdoctoral Fellow, Germany Dr. Danny Admasu, Hebrew University Dr. Gil Rothschild Elyassi, Haifa University Itzik Itzhak Dessie, Bar-Ilan University Dr. Bruce D. Haynes, UC-Davis Dr. Remy Ilona, Olaudah Equiano Institute Rabbi Dr. Walter Isaac, University of Tennessee Dr. Dréa Key, Claflin University Shahanna McKinney-Baldon, University of Wisconsin Dr. Shula Mola, Hebrew University Dr. Bryan Roby, University of Michigan Dr. Engdau Shelly, University of Haifa Moriya Tadela, University of Haifa Efrat Yerday, Tel Aviv University  Resident artist for the meetingJessica Valoris, Mandel Artist Fellow   Thank you to our co-sponsorsAfrican American Cultural Center Africana Studies Institute Center for Judaic Studies and Contemporary Jewish Life College of Liberal Arts and Sciences Department of Literature, Culture, and Languages Department of Sociology Dodd Impact Programs Global Affairs Human Rights Institute Schedule Day 1 Morning Sessions8:45 AM: Breakfast 9:15 AM: Opening remarks 9:30 AM – 11:00 AM: Presentation 11:15 AM – 12:30 PM: Presentation Break12:30 PM – 2:00 PM Afternoon Sessions2:00 PM – 3:30 PM: Presentation 3:45 PM – 5:30 PM: Presentation 5:30 PM – 6:30 PM: Networking Day 2 Morning Sessions8:45 AM: Breakfast 9:15 AM: Opening remarks 9:30 AM – 11:00 AM: Presentation 11:15 AM – 12:30 PM: Presentation Break12:30 PM – 2:00 PM Afternoon Sessions2:00 PM – 3:30 PM: Presentation 3:45 PM – 5:30 PM: Presentation 5:30 PM – 6:30 PM: Reception

This training is not only for people who are thinking about starting a practice, but also for those who have an existing practice. It's never too late to make some adjustments to your practice that will help it grow more effectively. This training relates to direct practice as it aims to help the clinician build a practice that will benefit the clients it serves and ensure their practice adheres to the strictest of ethical principles. Participants will learn how to build a private practice that meet the needs of the clients they serve and strengthens both the client's treatment experience and the profession as a whole. This training is split into 3 consecutive Thursday webinars. Participants must attend all 3 sessions to earn CECs. DAY 1 covers the top mistakes people make in private practice, and begins to layout the framework for building a better one. We will explore the nuts and bolts of who, why, where, and when to open a private practice. Then we will dive into how to set up your practice with your own policies and procedures.

Learn more about the Master's in Early Childhood for Infants and Children with Autism here. (https://uconnucedd.org/masters-degree-early-childhood-for-infants-and-children-with-autism/)

Stop by DTWN 219 from April 28 to May 2nd, 9AM-3PM to grab your de-stress finals care packages filled with hot chocolate packets, fidget toys, playdough, and snacks! An Honors GPS member or staff will also be there and available to answer any questions about your honors journey. 

Join us for virtual office hours! Drop in with your questions—we're here to support you in the most convenient way possible.Register today! (https://connect.grad.uconn.edu/register/stem-virtual-250429)

Join us for an engaging, hands-on experience that brings genetics education to life through the power of virtual reality and community engagement. This unique event combines cutting-edge technology with student-driven learning and local professional interaction to deepen understanding of how genetics solves real-world human problems. Students will explore key concepts in genetics and gene editing through an immersive VR experience and showcase their takeaways in a reverse career fair-style poster presentation. Attendees—including professionals from the Greater Hartford area—are invited to circulate, connect with students, and provide real-time feedback and career insights. Whether you're a student curious about science careers or a local professional passionate about mentoring the next generation, this event offers a collaborative space for exploration, reflection, and dialogue.

Abstract: Machine learning (ML) has shown great promise in a variety of applications. One particular space where ML applications are desired is the analysis of scientific data. Many of these applications differ from the more discussed applications of ML in that data are more difficult to acquire. A wealth of written works, photographs, and data on topics such as browsing habits exist and have resulted in many of the most powerful ML models ever created. In many scientific applications, data collected from a particular technique are scarcer. Analyzing these data may require years of expertise and hours of work to analyze a single datum. ML solutions are therefore highly desirable, but difficult to achieve. Here I present several works to create domain specific ML applications under these limitations. The first application is a hierarchical classifier for small angle scattering curves to identify the structures of nanoparticles. To do this, a hierarchical model creates an interpretable series of decision boundaries that align with physical differences. Creating this hierarchical model involves both selecting the optimal tree structure and tuning each decision along the hierarchical model. Each decision in this hierarchical model is independently trained as a standalone binary classifier. We propose and justify a rebalancing of k-fold cross validation to tune models which generalize better and minimize the risk of overfitting model selection, by using more data for validation than training at each fold. A second project is symbolic regression for implicit equations. In many scientific applications, it can be more informative to learn an actual description of a relationship between two quantities, rather than a tool for mapping input to output. Symbolic regression is an ML technique that learns an actual symbolic expression of relationships between data. Implicit expressions, however, are a uniquely challenging problem, due to only possessing a single label, and often non-invertible relationships between variables. We create a probabilistic featurization of implicit equations utilizing importance sampling. This allows many tools for symbolic regression to generalize to implicit equations and discovering conserved quantities in series of differential equations. Symbolic regression is, in essence, a special case of model selection. We utilize other tools including weighted bootstrap sampling and complexity-focused checkpoints to find the symbolic expression with the fewest operators, while carefully avoiding false answers such as trivial models. By utilizing careful model selection and careful construction of features and models we can create ML tools using small amounts of data.

Get your Graduation and Mother's Day cards and gifts here! 20% off cards, a large assortment of jewelry, museum t-shirts, art umbrellas and other art themed items, scarves, games, accessories, UConn cards and postcards, and other gifts. (30% for Paid Museum Members) Become a museum supporter and save! CT Art Trail Passports are here. Get your passport here and visit 30 world-class museums, nature centers and historic sites, created to promote Connecticut's rich cultural assets as part of a travel experience, for just $35.

UConn Sexpert Peer Support Drop-In Hours are a free service offered by peer health educators, the UConn Sexperts, on the UConn Storrs campus!Peer Support Drop-In Hours are a great option for students who have questions about sex and sexual health, are looking for a non-judgmental, laid-back environment to discuss a sex related concern or issue, or are interested in improving their sexual health and personal well-being. Our UConn Sexperts are trained to provide education, support, and connection to resources on and off-campus on a wide variety of topics pertaining to sex, sexual health, and relationships.Mondays: 10am-1pm Tuesdays: 10am-12pm Wednesdays: 9am-6pm Thursdays: 9am-6pm Fridays: 2pm-5pm UConn Sexperts (and supervising staff) are designated confidential employees under UConn's Title IX Reporting Obligations. Peer support sessions are for educational and support purposes only. Peer support visits are not on-call or emergency services, and are not for individualized medical advice, nor are they counseling or therapy. For more information, visit: studenthealth.uconn.edu/sexperts (https://studenthealth.uconn.edu/sexperts/) 

More info about SHaW's Group Sessions. (https://studenthealth.uconn.edu/mental-health/group-therapy/)Mind and BodySupport Group: support and empowerment for students with chronic health conditions. This weekly group is for students adjusting to coping with chronic health conditions in a university setting. This is a safe space for students to share their experiences and support each other in managing their health while also managing the challenges of college life. This group is a joint effort between medical and mental health services to ensure that students are cared for in a complete and holistic manner.' This session is held by Jennifer Fox, PhD (https://studenthealth.uconn.edu/person/jennifer-fox/) & Ryan Grade BSN, RN (https://studenthealth.uconn.edu/person/ryan-grade/) For many concerns that students face- like overwhelming stress, anxiety, difficult relationships, depression, academic difficulties, and more – group therapy is the best option for support and healing. Facilitated by SHaW counselors, our therapy groups encourage peer support, promote emotional wellbeing, and increase a felt sense of connection. Participants often find that they feel less alone in their struggles and walk away with newfound support and ideas for coping.

We are pleased to offer online accessible technology workshops as part of an ongoing workshop series. These workshops are intended to enhance the knowledge and skills of University employees and organizations in the use of accessible technology.

FIND OUT: • How to save for the retirement you want • How to take advantage of your plan features • How to choose investments that meet your needs • If you're on track to meet your goals (and what to do if not)

Tabling to raise awareness of Denim Day for Sexual Assault Awareness Month

SHaW's Substance Use Risk Reduction Peer Educators are here to offer a safe and non-judgmental space for students to talk about anything related to alcohol, cannabis, or other substance use- whether it's for yourself or someone you care about. Our peer heath educators are students just like you, trained to provide education, support, and connection to resources on and off-campus on a wide variety of substance use topics.Monday: 11:15 am to 1:15 pm Tuesday: 11:30 am to 1:30 pm Wednesday: 10 am to 12 pm & 5 pm to 7 pm Thursday: 2:30 pm to 4:30 pm Student Health and Wellness peer educators are designated confidential employees under UConn's Title IX Reporting Obligations. Peer Support sessions are for educational and support purposes only. Peer support visits are not on-call or emergency services, and are not for individualized medical advice, nor are they counseling or therapy.