Announcements
Northeast Workshop in Geometric Analysis, 5–6 November 2022
Mathematics Continued, 22 October 2022
2022 Research Experience for Undergraduates (REU) Programs
News & Achievements
Equity in Math Education: Joint Policy Statement for Connecticut
Prof. Cardetti Part of Team Winning $3M for Graduate Program
Revenge of the Data Scientists
Former UConn Postdoc Receives NSF CAREER Award
Prof. Valdez Awarded 2022 Mehr Award
Prof. Malmendier Receives OVPR SFF Award
Professor Andreas Malmendier has received an OVPR Scholarship Facilitation Fund for his project “Developing Best Practices for Inclusive Graduate Mentoring in Mathematics”. Developing best practices for inclusive mentoring in Mathematics is key for enhancing the diversity in UConn’s mathematical sciences graduate program. The goal of this Scholarship Facilitation Fund is to cultivate knowledge about how […]
[Read More]Upcoming Events

Oct
3
Actuarial Science Seminar
Risk Allocation Through Shapley Decompositions with Applications to Variable Annuities
Frederic Godin (Concordia University)11:00amActuarial Science Seminar
Risk Allocation Through Shapley Decompositions with Applications to Variable Annuities
Frederic Godin (Concordia University)Monday, October 3rd, 2022
11:00 AM  12:00 PM
Other
OnlinePlease join the Webex virtual seminar using the following link:
https://uconncmr.webex.com/uconncmr/j.php?MTID=mcff3996e1bfb542702cef27de6fba0e6
(Meeting number: 2620 464 0564
Password: tpW8pD7KZx6)
Abstract: We introduce a flexible risk decomposition method for life insurance contracts associated with exposure to several risk factors. Hedging can be naturally included in the framework. Although the method is applied to variable annuities in this work, it is also applicable in general to other insurance or financial contracts. The approach relies on applying an allocation principle to components of a Shapley decomposition of the gain and loss. The implementation of the allocation method requires a stochastic on stochastic algorithm.
Numerical examples studying the relative impact of equity, interest rate and mortality risk for guaranteed minimal maturity benefit (GMMB) policies are also presented. (Joint work with Emmanuel Hamel, Patrice Gaillardetz and Edwin HonMan Ng)
Speaker's short bio: Frederic is an associate professor in the Department of Mathematics and Statistics at Concordia University (Canada). He obtained his PhD from HEC Montreal in 2014. His research interests include Mathematical and Computational Finance, Actuarial Science, Risk Management, Dynamic Programming, and Statistics. For more information on his research, please visit https://www.researchgate.net/profile/FredericGodin.Contact Information: Bin Zou, bin.zou@uconn.edu
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Oct
3
Control and Optimization Seminar
Analysis of a Finite State Many Player Game Using its Master Equation
Asaf Cohen (University of Michigan)2:00pmControl and Optimization Seminar
Analysis of a Finite State Many Player Game Using its Master Equation
Asaf Cohen (University of Michigan)Monday, October 3rd, 2022
02:00 PM  03:00 PM
Storrs Campus
OnlinePlease join the Webex virtual seminar using the following link:
https://uconncmr.webex.com/uconncmr/j.php?MTID=m4843051786397a32038771f6b19eafdb
(Meeting number: 2623 958 5994
Password: 33sWs6ZJAp2)
Abstract: We consider an nplayer symmetric stochastic game with weak interaction between the players. Time is continuous and the horizon and the number of states are finite. We show that the value function of each of the players under Nash equilibrium can be approximated by the solution of a partial differential equation called the master equation. For this, we prove the regularity of the master equation. (Based on joint work with Erhan Bayraktar and Ethan Zell).
Speaker's short bio: Dr. Cohen is an assistant professor in the Department of Mathematics at the University of Michigan at Ann Arbor. He obtained his PhD in 2014 from TelAviv University, Israel, and was an assistant professor at the University of Haifa. His research interests are applied probability and control theory and their applications to meanfield games, mathematical finance, and stochastic networks. Please visit his website for more information: https://sites.google.com/site/asafcohentau/homeContact Information: Bin Zou, bin.zou@uconn.edu
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Oct
5
Algebra Seminar
Cluster algebras and knot theory
Ralf Schiffler (University of Connecticut)11:15amAlgebra Seminar
Cluster algebras and knot theory
Ralf Schiffler (University of Connecticut)Wednesday, October 5th, 2022
11:15 AM  12:05 PM
Storrs Campus
Monteith 313This talk is based on joint work with Véronique BazierMatte in which we found a relation between cluster algebras and knot theory. To every knot diagram (or link diagram), we associate a cluster algebra by constructing a quiver with potential. The rank of the cluster algebra is \(2n\), where \(n\) is the number of crossing points in the knot diagram. We then construct \(2n\) indecomposable modules \(T(i)\) over the Jacobian algebra of the quiver with potential. For each \(T(i)\), we show that the submodule lattice of \(T(i)\) is isomorphic to the corresponding lattice of Kauffman states of the knot. Furthermore, the Alexander polynomial of the knot is a specialization of the \(F\)polynomial of \(T(i)\), for every \(i\).Contact Information: mihai.fulger@uconn.edu
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Oct
5
Math Club
Computationally Hard Problems and Their Uses in Cryptography
Asimina Hamakiotes (UConn)5:30pmMath Club
Computationally Hard Problems and Their Uses in Cryptography
Asimina Hamakiotes (UConn)Wednesday, October 5th, 2022
05:30 PM  06:30 PM
Storrs Campus
Monteith 214Cryptography is the practice and study of techniques used for secure communication in the presence of adverse third parties. Although cryptography is of interest to computer scientists, there is a lot of mathematics being done behind the scenes. In this talk, we will explain the difference between private key cryptography and public key cryptography. We will also talk about some computationally hard math problems that are used in public key cryptography.
Note: Free refreshments. The talk starts at 5:40.Contact Information: Keith Conrad (kconrad@math.uconn.edu)
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Oct
7
Logic Colloquium: Zoe Ashton (OSU)11:15am
Logic Colloquium: Zoe Ashton (OSU)
Friday, October 7th, 2022
11:15 AM  12:45 PM
Storrs Campus
Hybrid: ITE 336 & ZoomJoin us in the Logic Colloquium!
Zoe Ashton (OSU)
"How the Standard View of Rigor and the Standard Practice of Mathematics Clash"
Mathematical proofs are rigorous – it’s part of what distinguishes proofs from other argument types. But the quality of rigor, relatively simple for the trained mathematician to spot, is difficult to explicate. The most common view, often referred to as the standard view of rigor, is that “a mathematical proof is rigorous iff it can be converted into a formal derivation” (Burgess & De Toffoli (2022)). Each proponent of the standard view interprets “conversion” differently. For some, like Hamami (2022), conversion means algorithmic translation while others, like Burgess (2015), interpret it as just revealing enough steps of the formal derivation.
In this talk, I aim to present an overarching concern for the standard view. I’ll argue that no extant version of the standard view makes sense of how mathematicians make rigor judgments. Both Hamami (2022) and TattonBrown (2021) have both attempted to account for mathematicians’ rigor judgments using the standard view. I’ll argue that both still fail to adequately account for mathematical practice by positing that mathematicians engage in either algorithmic proof search and/or extensive training in formal rigor.
We seem to be left with two options: continue trying to amend the standard view or introduce a new account of rigor which is practicefocused. I’ll argue that issues with the two accounts are general issues that will likely occur for future formulations of the standard view. Thus, we should aim to introduce a new account of informal, mathematical rigor. I’ll close by sketching a new account of rigor related to the audiencebased view of proof introduced in Ashton (2021).
https://logic.uconn.edu/calendar/Contact Information: logic@uconn.edu
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