歷史紀錄

114 學年度下學期・演講

2026/02/01 – 2026/08/31・共 12 場

2026 年 6 月3 場

202606/23週二 演講 Inspiration and Discovery : Some Math Professors I Met at Princeton University 張德健教授Georgetown University 11:00-12:00 鴻經館M107

Abstract:

In this talk, “Inspiration and Discovery : Some Professors I Met at Princeton University”, the speaker will share his experiences and insights gained from the remarkable mathematics professors at Princeton. These educators not only shaped his academic journey but also inspired a profound appreciation for the beauty and complexity of mathematics.

Through personal anecdotes and stories of innovative research, the speaker will highlight how their unique teaching styles and groundbreaking work influenced his understanding of the subject. From their passion for problem-solving to their dedication to mentoring students, each professor offered a distinct perspective that illuminated the path of discovery in mathematics.

Join the speaker as he explores the intersection of inspiration and discovery in academia, illustrating how the spirit of inquiry and collaboration at Princeton fosters a vibrant intellectual community.Whether you are a student, educator, or simply curious about the world of mathematics, this talk aims to ignite a spark of curiosity and appreciation for the transformative power of education.

 

20260623演講_張德健教授(Georgetown University)

202606/11週四 演講 Dynamics of immersed interface problems in Stokes flow 郭柏均助理教授Purdue University 15:30–17:00 鴻經館M107

Abstract:

Immersed interface problems in Stokes flow arise in fluid–structure interaction,where an internal interface is coupled to a viscous incompressible fluid. One of the simplest of such problems is the 2D Peskin problem, in which a 1D closed elastic structure is immersed in a 2D Stokes fluid. This has been extensively studied computationally and analytically. We extend the 2D Peskin problem into two in two directions:

(1) 2D inextensible interface problem.

(2) 3D Peskin problem.

For the 2D inextensible interface problem, we impose an inextensibility constraint on the interface. Through the boundary integral method, we reformulate the problem as two coupled contour equations, an evolution equation and a tension determination equation. We first study the well-posedness and the regularity of the generalized tension determination problem in Hölder spaces. Next, we use an appropriate time-weighted Hölder space to study the well-posedness and regularity of the full dynamical problem.

We also study the Peskin problem in the 3D case. With the boundary integral

method, the 3D Peskin is reformulated as an evolution equation on a unit sphere for the elastic interface. We use multiple local charts to prove that the problem is well-posed in low-regularity Hölder spaces. Moreover, we prove that the elastic interface becomes smooth instantly in time.

 

20260611演講_郭柏均助理教授(Purdue University)

202606/01週一 演講 Orthogonal polynomials and combinatorics 鄭硯仁助理教授國立屏東大學應用數學系 10:30-12:00 鴻經館M107

Abstract:

Orthogonal polynomials arise in many areas of mathematics, including differential equations, probability theory, and numerical analysis. In this talk, I will present several methods for constructing orthogonal polynomials, and illustrate their rich connections with combinatorial structures, including lattice paths and continued fractions.

 

20260601演講_鄭硯仁助理教授(國立屏東大學應用數學系)

2026 年 5 月5 場

202605/28週四 演講 Reconstruction formulas in Banach Spaces and Related Topics 游步庭博士後研究員University of Oregon 15:30–17:00 鴻經館M107

Abstract:

A countable sequence {x_n} in a separable Banach space X is said to admit a reconstruction formula if every element in the Banach space can be represented as an "infinite linear combination" of x_n, with the convergence of the series in the norm of X. Over the past several decades, the problem of constructing sequences that admit reconstruction formulas with prescribed forms and desirable convergence properties has become a central topic in Banach space theory, approximation theory, and some other related areas.

In this talk, we will provide an introduction to the notion of reconstruction formulas and discuss several related research directions, with particular emphasis on some open problems. The presentation is intended to be introductory in nature, only a basic background in real analysis will be assumed.

 

20260528演講_游步庭博士後研究員(University of Oregon)

202605/26週二 演講 Independence of Weyl-Heisenberg coherent states: the HRT Conjecture Kasso Okoudjou教授Tufts University 10:30-12:00 鴻經館M107
202605/21週四 演講 Profinite Iterated Monodromy Groups of Unicritical Polynomials Trevor Hyde 助理教授Mathematics and Statistics, Vassar College 15:30–17:00 鴻經館M107

Abstract:

Let f be a polynomial with coefficients in a field K and let t be a variable. The Galois group of the extension of K(t) formed by adjoining all iterated f pre-images of t is called the arithmetic profinite iterated monodromy group (pIMG) of f. I'll discuss some recent joint work with Ophelia Adams on the structure of the pIMG of when f is a unicritical polynomial with degree coprime to char(K).

 

20260521演講_Trevor Hyde 助理教授 (Mathematics and Statistics, Vassar College)

202605/14週四 演講 [線上演講]人工智慧式無線通訊 & 什麼是博士班? 周伯衡博士後研究員美國 Virginia Tech 15:30–17:00 鴻經館M107

線上演講連結:

1.https://meet.google.com/hpq-hhwo-xoe

2.開啟 google meet 並輸入下列代碼:hpq-hhwo-xoe

 

Abstract:

未來的 6G 無線網路將在高度動態、高維度且硬體資源受限的環境中運行,傳統的最佳化和短期學習方法已不再適用。本次演講將探討向原生 AI 無線系統轉變的範式,該系統融合了數據驅動的智慧和推理能力。

在物理層,深度學習將取代迭代最佳化和明確通道估計,從而實現可擴展且節能的 RIS 輔助毫米波 MIMO 系統設計。在網路層,我們將引入雙思維世界模型 (DMWM),將快速模式識別與緩慢的邏輯推理相結合,從而支持長期規劃、穩健泛化以及在不確定性下的適應性。

除了技術發展之外,本次演講還將探討攻讀博士學位的更深層意義。正如下一代無線系統從被動優化演進到預測智能一樣,攻讀博士學位的過程也代表著在複雜世界中駕馭不確定性、做出基於價值的決策並不斷重新定義自身方向的過程。

 

20260514線上演講_周伯衡博士後研究員(美國Virginia Tech)

202605/07週四 演講 A Combinatorial Approach in Free Probability 曾培倫助理教授中原大學應用數學系 15:30–17:00 鴻經館M107

Abstract:

Free probability, initiated in the 1980s by Dan Voiculescu, has become a fundamental tool for studying the asymptotic behavior of random matrices. In general, there are two main approaches in free probability: the analytic approach and the combinatorial approach.

 

In this talk, we will first review the random matrix problems that motivate our study. We then demonstrate how the combinatorial approach can be used to address these questions effectively. If time permits, we will also introduce some generalizations of free probability and discuss their connections to random matrix theory.

 

20260507演講_曾培倫助理教授(中原大學應用數學系)

2026 年 4 月2 場

202604/30週四 演講 Newform conjecture for ρ-ADIC SO2n+1 鄭堯副教授淡江大學應用數學與數據科學學系 15:30–17:00 鴻經館M107
202604/23週四 演講 DELIGNE'S CONJECTURE AND THE CROSS-RATIO FORMULA 陳昰宇助理教授國立清華大學數學系 15:30–17:00 鴻經館M107

Abstract:

At the 1977 Corvallis conference, P.Deligne proposed a remarkable conjecture describing the algebraicity of critical L-values in terms of motivic periods. The conjecture has recently been settled for pure motives of rank one. In all other known cases in the literature, proofs typically depend on integral representations of the relevant L-functions. In the framework of the Langlands–Clozel correspondence, we introduce, on the automorphic side, a cross-ratio formula for the critical values of Rankin–Selberg L-functions. This formula provides a new method for addressing Deligne’s conjecture. In this talk, we will introduce Deligne’s conjecture and present the cross-ratio formula. If time permits, we will also outline a proof of Deligne’s conjecture for the symmetric power L-functions of modular forms.

 

20260423演講_陳昰宇助理教授(國立清華大學數學系)

2026 年 3 月2 場

202603/26週四 演講 [線上演講] Scalable Spectral Methods for Manifold Learning with Multi-View Data 葉行遠博士候選人國立台灣大學數學系 15:30–17:00 鴻經館M107

線上演講連結:

  1. https://meet.google.com/hpq-hhwo-xoe
  2. 開啟 google meet 並輸入下列代碼:hpq-hhwo-xoe

 

Abstract:

Manifold learning aims to recover the intrinsic geometry of high-dimensional data through spectral analysis of graph operators. In this talk, I focus on scalable spectral methods for multi-sensor data and large datasets. In particular, I introduce Landmark Alternating Diffusion (LAD), a scalable spectral method for sensor fusion, which builds on the Alternating Diffusion (AD) framework to extract the common manifold structure shared by multiple observations. By approximating the alternating diffusion process using a small set of landmark points, LAD significantly reduces computational cost while preserving the geometry captured by AD. Under standard common manifold assumptions, we establish theoretical guarantees including consistency, convergence, and finite-sample error bounds. We also demonstrate the practical effectiveness of LAD on an EEG sleep stage annotation task using multi-channel signals. Besides, I will also briefly discuss related work on Landmark Vector Diffusion (LA-VDM), which extend the landmark framework to Vector Diffusion Maps in order to capture directional structures and connection information in data. Finally, I will mention current work on sensor fusion using interpolation on the manifold of symmetric positive definite (SPD) matrices.

 

20260326線上演講_葉行遠博士候選人 (國立台灣大學數學系)

202603/19週四 演講 Algebraic and combinatorial aspects of domino tilings 李宜霖博士國立台灣師範大學數學系 15:30–17:00 鴻經館M107

Abstract:

A domino tiling is a covering of a region on the plane using dominoes without gaps or overlaps. I will begin by discussing its background from physics, called the dimer covering, which models how diatomic molecules stick on a crystal surface. This talk focuses on two aspects of domino tilings: in combinatorics, I will review their symmetry classes on the Aztec diamond and present new properties; in algebra, I will establish a connection between specific tiling models and symmetric functions from the viewpoint of Macdonald theory. Finally, I will introduce my recent research in dynamical combinatorics, a vibrant field at the intersection of discrete dynamical systems and combinatorics. This talk does not assume any prior background.

 

20260319演講_李宜霖博士 (國立台灣師範大學數學系)