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

Master Algebra with us! Join our Algebra Workshop Series this fall at CASE (Room 260) from 3:30–4:30 P.M. Each session will break down key algebra concepts to help you build confidence and sharpen your skills. 📅 Upcoming Sessions: Quadratic Equations – Wed. Nov 19 📍 CASE (Room 260) Don't miss the chance to level up your math game!

The Critical Language Scholarship (CLS) Program provides immersive summer programs for U.S. undergraduate and graduate students to learn languages of strategic importance to the United States' national security and economic prosperity. Through intensive language instruction and structured cultural activities, participants receive the equivalent of one year of language study in just eight weeks. Join CLS Program Officers and alumni ambassadors in this webinar to learn about CLS Chinese, Japanese, and Korean offerings.

Tejal A. Desai is currently the Sorensen Family Dean of Engineering at Brown University. An accomplished biomedical engineer and academic leader, Desai's research spans multiple disciplines including materials engineering, cell biology, tissue engineering, and pharmacological delivery systems to develop new therapeutic interventions for disease. She seeks to design new platforms, enabled by advances in micro and nanotechnology, to overcome challenges in therapeutic delivery. With more than 275 peer-reviewed articles and patents, Desai's research has earned her numerous recognitions including Technology Review's "Top 100 Young Innovators," Popular Science's "Brilliant 10" and the Dawson Biotechnology Award. She served as president of the American Institute for Medical and Biological Engineering from 2020 to 2022 and is a fellow of AIMBE, IAMBE, CRS, and BMES. She was elected to the National Academy of Medicine in 2015, the National Academy of Inventors in 2019, and to the National Academy of Engineering in 2024. Desai was also awarded the 2023 Robert A. Pritzker Distinguished Lecture Award at the Biomedical Engineering Society Annual Meeting — the highest honor the organization can bestow upon an individual who has demonstrated impactful leadership and accomplishments in biomedical engineering science and practice. Prior to coming to Brown, she was the Deborah Cowan Endowed Professor of the Department of Bioengineering & Therapeutic Sciences at University of California, San Francisco (UCSF); and Professor in Residence, Department of Bioengineering, UC Berkeley (UCB). She served as director of the NIH training grant for the Joint UCSF/UCB Graduate Program in Bioengineering for over 15 years, and founding director of the UCSF/UCB Masters Program in Translational Medicine. She was also the Ernest L. Prien Chair of the Department of Bioengineering and Therapeutic Sciences at UCSF from 2014-2021 and the Inaugural Director of the UCSF Engineering and Applied Sciences Initiative known as HIVE (Health Innovation Via Engineering). She currently sit on the National Advisory Council for the NIH National Institute for Biomedical imaging and Bioengineering. A vocal advocate for education and outreach to historically underrepresented groups in STEM, Desai's work to break down institutional barriers to equity and cultivate a climate of inclusion has earned numerous honors and awards, including the AWIS Judith Poole Award in Mentorship, the 2021 UCSF Chancellors Award for the Advancement of Women, and the 2022 Controlled Release Woman in Science Award. As president of AIMBE (2020-2022), she led advocacy efforts for increased scientific funding and addressing workforce disparities in science/engineering. To foster the next generation of scientists, she has been involved in the SF Science Education partnership and has worked with outreach organizations such as the Lawrence Hall of Science, PBS, and the UN Women's council to develop hand-on exhibits and videos related to nanotechnology and women in engineering. Education & Training • PhD UCSF and UC Berkeley • B.S. Brown University

Interpersonal Group for Undergraduate Students Undergraduate 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. To join this group therapy session, please call SHaW at 860-486-4700 (tel:860-486-4705). This session is held by Maritza Lugo-Stalker, (https://studenthealth.uconn.edu/person/maritza-lugo-stalker/) 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 Student Health and Wellness (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.

In September 1984, Frederick Wiseman undertook the Deaf and Blind series, a four-part documentary about the Alabama Institute for Deaf and Blind in Talladega. At the time, Wiseman was already a veteran of public television: he had made more than a dozen documentaries for PBS, establishing a reputation as an auteurwho achieved accessinside myriad American institutions. The Deaf and Blind series was broadcast on PBS in 1988, two years before the passing of the Americans with Disabilities Act. Several decades later, this four-part documentary remains a marginalized media object in Wiseman's archive of American life. This talk reconsiders the Deaf and Blind series through the lens of overlooked histories and perspectives, including issues of access and mainstreaming debates that harken back to the 19th century.  Jennifer Cazenave is Associate Professor of French and Cinema & Media Studies at Boston University. She is currently a Visiting Residential Fellow at UCHI. Her research interests include documentary cinema, disability studies, archive and memory studies, Holocaust and genocide studies, and gender studies. She is the author of An Archive of the Catastrophe: The Unused Footage of Claude Lanzmann's "Shoah." Her work has also appeared in edited volumes, journals, and magazines including SubStance, Cinema Journal, and Los Angeles Review of Books.

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

Abstract: We study continuous-time mean-variance portfolio selection in markets where stock prices are diffusion processes driven by observable factors that are also diffusion processes, yet the coefficients of these processes are unknown. Based on the recently developed reinforcement learning (RL) theory for diffusion processes, we present a general data-driven RL algorithm that learns the pre-committed investment strategy directly without attempting to learn or estimate the market coefficients. For multi-stock Black-Scholes markets without factors, we further devise a baseline algorithm and prove its performance guarantee by deriving a sublinear regret bound in terms of Sharpe ratio. For performance enhancement and practical implementation, we modify the baseline algorithm and carry out an extensive empirical study to compare their performance, in terms of a host of common metrics, with a large number of widely used portfolio allocation strategies on S&P 500 constituents. The results demonstrate that the proposed continuous-time RL strategy is consistently among the best especially in a volatile bear market, and decisively outperforms the model-based continuous-time counterparts by significant margins. This is joint work with Prof. Yanwei Jia (CUHK) and Prof. Xunyu Zhou (Columbia U). Speaker's short bio: Yilie is a Postdoctoral Research Scientist in the Department of Industrial Engineering and Operations Research at Columbia University, supervised by Professor Xun Yu Zhou (https://www.engineering.columbia.edu/faculty-staff/directory/xunyu-zhou). He earned his PhD in Industrial Engineering and Operations Research at Columbia University in 2024. He also holds an M.S. in Operations Research from Columbia University (2018) and a B.S. in Mathematics and Applied Mathematics from Zhejiang University (2017). His research lies at the intersection of reinforcement learning (RL), diffusion models for GenAI, stochastic control, and financial engineering, with a focus on developing and analyzing continuous-time RL algorithms to optimize financial and control systems under uncertainty. For more information, please visit https://yiliehuang.github.io/

Abstract: We study continuous-time mean-variance portfolio selection in markets where stock prices are diffusion processes driven by observable factors that are also diffusion processes, yet the coefficients of these processes are unknown. Based on the recently developed reinforcement learning (RL) theory for diffusion processes, we present a general data-driven RL algorithm that learns the pre-committed investment strategy directly without attempting to learn or estimate the market coefficients. For multi-stock Black-Scholes markets without factors, we further devise a baseline algorithm and prove its performance guarantee by deriving a sublinear regret bound in terms of Sharpe ratio. For performance enhancement and practical implementation, we modify the baseline algorithm and carry out an extensive empirical study to compare their performance, in terms of a host of common metrics, with a large number of widely used portfolio allocation strategies on S&P 500 constituents. The results demonstrate that the proposed continuous-time RL strategy is consistently among the best especially in a volatile bear market, and decisively outperforms the model-based continuous-time counterparts by significant margins. This is joint work with Prof. Yanwei Jia (CUHK) and Prof. Xunyu Zhou (Columbia U). Speaker's short bio: Yilie is a Postdoctoral Research Scientist in the Department of Industrial Engineering and Operations Research at Columbia University, supervised by Professor Xun Yu Zhou (https://www.engineering.columbia.edu/faculty-staff/directory/xunyu-zhou). He earned his PhD in Industrial Engineering and Operations Research at Columbia University in 2024. He also holds an M.S. in Operations Research from Columbia University (2018) and a B.S. in Mathematics and Applied Mathematics from Zhejiang University (2017). His research lies at the intersection of reinforcement learning (RL), diffusion models for GenAI, stochastic control, and financial engineering, with a focus on developing and analyzing continuous-time RL algorithms to optimize financial and control systems under uncertainty. For more information, please visit https://yiliehuang.github.io/

English workshops are available for 10-weeks in the Fall and Spring semesters. These workshops can be used to improve the communication skills needed to meet the university's English requirement for teaching undergraduate students (TA's) These workshops will help participants develop the speaking skills needed to convey their ideas clearly when presenting in front of an audience. Students will practice presenting information relevant to their field of study and be actively involved in self-assessment and peer assessment. Content will be adapted to suit the group's needs. Conversation partners will join the last hour of class to provide opportunities for practice, feedback, and questions. Registration for the workshop series is highly recommended to guarantee a seat. Who can register? UConn undergraduates, graduates, J1 scholars, J2, F2, exchange students (EGL).https://ita.uconn.edu/english-support/ (https://ita.uconn.edu/english-support/) 

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/).

Abstract: We study continuous-time mean-variance portfolio selection in markets where stock prices are diffusion processes driven by observable factors that are also diffusion processes, yet the coefficients of these processes are unknown. Based on the recently developed reinforcement learning (RL) theory for diffusion processes, we present a general data-driven RL algorithm that learns the pre-committed investment strategy directly without attempting to learn or estimate the market coefficients. For multi-stock Black-Scholes markets without factors, we further devise a baseline algorithm and prove its performance guarantee by deriving a sublinear regret bound in terms of Sharpe ratio. For performance enhancement and practical implementation, we modify the baseline algorithm and carry out an extensive empirical study to compare their performance, in terms of a host of common metrics, with a large number of widely used portfolio allocation strategies on S&P 500 constituents. The results demonstrate that the proposed continuous-time RL strategy is consistently among the best especially in a volatile bear market, and decisively outperforms the model-based continuous-time counterparts by significant margins. This is joint work with Prof. Yanwei Jia (CUHK) and Prof. Xunyu Zhou (Columbia U). Speaker's short bio: Yilie is a Postdoctoral Research Scientist in the Department of Industrial Engineering and Operations Research at Columbia University, supervised by Professor Xun Yu Zhou (https://www.engineering.columbia.edu/faculty-staff/directory/xunyu-zhou). He earned his PhD in Industrial Engineering and Operations Research at Columbia University in 2024. He also holds an M.S. in Operations Research from Columbia University (2018) and a B.S. in Mathematics and Applied Mathematics from Zhejiang University (2017). His research lies at the intersection of reinforcement learning (RL), diffusion models for GenAI, stochastic control, and financial engineering, with a focus on developing and analyzing continuous-time RL algorithms to optimize financial and control systems under uncertainty. For more information, please visit https://yiliehuang.github.io/

In celebration of Manufacturing Month, the UConn School of Business Digital Frontiers Initiative (DFI) invites you to the Smart Manufacturing Summit: Turning Data into Decisions—an evening exploring how data, analytics, and innovation are driving the future of Connecticut's manufacturing industry. Join manufacturers, educators, and data professionals for an engaging program featuring two expert panels and a keynote address, followed by a networking reception with complimentary appetizers.  AI & Automation Panel How is artificial intelligence transforming the shop floor? This panel brings together innovators leveraging data-driven automation to enhance production, efficiency, and competitiveness. Learn how manufacturers are integrating smart technologies into real-world operations—and what skills will define the next generation of the manufacturing workforce.Panelists: • Amy Thompson, Connecticut Center for Advanced Technology (CCAT) • Dennis Nash, Control Station • Matthew Krieger, Cober Inc.Moderator:Craig Calvert, University of Connecticut  Economics & Workforce Panel Manufacturing is evolving—and so is the talent it needs. This discussion explores how Connecticut educators, employers, and policy leaders are working together to strengthen the pipeline of skilled workers and address the economic challenges shaping the industry's future. Hear about innovative partnerships, workforce training programs, and the data trends influencing regional development.Panelists: • Mathew Spinelli, CT State Community College – Manchester • Todd Z., Norwich Free Academy • Chris Davis, Connecticut Business & Industry Association (CBIA)Moderator:Jordan Lumpkins, Northeastern CT Council of Governments (NECCOG)Keynote PresentationRevere Staffing Partners"Attracting Top Talent in a Changing Workforce" Co-Founder Joseph Muraski will close the evening with an insightful keynote on the strategies and skills manufacturers need to attract and retain high-performing talent in today's rapidly evolving, technology-driven economy. All students can attend for free! Student registration link: https://nexus.uconn.edu/secure_per/events/event_registration.php?ser=10358&rc=2892870827 If you are not a student, please purchase a ticket here: https://secure.touchnet.com/C21646_ustores/web/product_detail.jsp?PRODUCTID=6205  

Join Avery Point students, faculty, and staff to celebrate writing in our community. Featured writer: Novelist Lara Ehrlich, author of Bind Me Tighter, Still Share your poetry, fiction, essay, song, comedy, or any other work. Unsure about presenting? Send us your work and we'll appoint someone to read it aloud. Register now at https://forms.cloud.microsoft/r/4YC8F4gi4d or at the event.

In the representation theory of Lie groups (or the representation theory of their corresponding Lie algebras), diagrammatic methods have often proven to be very useful for computational purposes. One particularly successful example in this direction is the description of invariant subspaces of \(m{SL}_3\)-representations using certain bipartite planar graphs embedded in the disk called "\(m{SL}_3\)-webs." In the late nineties, Kuperberg introduced webs in order to describe the invariant subspaces of \(m{SL}_3\)-representations and provided a particularly nice family of bases for invariant subspaces using "non-elliptic" \(m{SL}_3\)-webs. These web bases satisfy the additional property of being invariant under rotation of the disk. Despite these rotation-invariant \(m{SL}_3\)-web bases being well-known for nearly 30 years, however, it has until recently been an open problem to provide rotation-invariant web bases for \(m{SL}_4\)-invariants, and this problem is still open for \(m{SL}_r\) with \(r\geq5\). The problem of finding rotation-invariant \(m{SL}_4\)-web bases was solved by Gaetz, Pechenik, Pfannerer, Striker, and Swanson in 2023, building on the work of Patrias in 2017, who described a bijection between non-elliptic \(m{SL}_3\)-webs and combinatorial objects called "generalized oscillating tableaux." Under her bijection, rotation of webs corresponds rather miraculously to the well-studied operation of promotion on tableaux. In this inaugural Graduate Collaboration Seminar, we will present our understanding of this current area of active research in algebraic combinatorics as well as the connections between the underlying combinatorics of webs and tableaux. We intend to focus mainly on the case of \(m{SL}_3\)-webs, but time permitting we may take a visit to the newer \(m{SL}_4\) story.

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/).