학과 세미나 및 콜로퀴엄




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구글 Calendar나 iPhone 등에서 구독하면 세미나 시작 전에 알림을 받을 수 있습니다.

I will explain how to put certain natural geometric structures on Tate-Shafarevich groups and other related groups attached to abelian varieties over function fields. We can refine arithmetic duality theorems by taking these geometric structures into account. This has applications to Weil-etale cohomology, the Birch-Swinnerton-Dyer conjecture and Iwasawa theory. Partially based on joint work with Geisser and with Lai, Longhi, Tan and Trihan.
Please contact Wansu Kim at for Zoom meeting info and any inquiry.
Host: Wansu Kim     영어     2021-09-13 17:36:08
(KAIX Distinguished Lectures Series)
1st talk 10:00-11:00 short break and Q&A 11:00-11:15 2nd talk 11:15-12:15 Q&A 12:15-12:30
Host: 권순식     영어     2021-09-23 16:53:35
This is joint work with Kenjiro Ishizuka (Kyoto). We study global behavior of solutions to the nonlinear Klein-Gordon equation with a damping and a focusing nonlinearity on the Euclidean space. Recently, Cote, Martel and Yuan proved the soliton resolution conjecture completely in the one-dimensional case: every global solution in the energy space is asymptotic to a superposition of solitons getting away from each other as time tends to infinity. The next question is to see which initial data evolve into each of the asymptotic forms. The asymptotic decomposition is very sensitive to initial perturbation because all the solitons are unstable. We consider the simplest non-trivial setting in general space dimensions: the global behavior of solutions starting near a superposition of two ground states. Cote, Martel, Yuan and Zhao proved that the solutions asymptotic to 2-solitons form a codimension-2 manifold in the energy space. Our question is what happens for the other initial data in the neighborhood. As an answer, we give a complete classification of those solutions into 5 types of global behavior. Two of them are asymptotic to the positive ground state and the negative one respectively. They form two codimension-1 manifolds that are joined at their boundary by the Cote-Martel-Yuan-Zhao manifold of 2-solitons. The connected union of those three manifolds separates the remainder of the neighborhood into the open set of global decaying solutions and that of blow-up. The main difficulty to prove it is in controlling the direction of instability in two dimensions attached to the two soliton components, because the soliton interactions are not integrable in time, breaking the simple superposition of the linearized approximation around each soliton. It is resolved by showing that the non-integrable interactions do not essentially affect the direction of instability, using the reflection symmetry of the equation and the 2-solitons. I will also explain the difficulty for the 3-solitons due to a more dramatic phenomenon, which may be called soliton merger.
Host: Moon-Jin Kang     미정     2021-09-06 10:34:30
The cohomology of Shimura varieties have rich structures and have been studied for many years. Some new vanishing theorems were proved in the last few years and especially the one by Caraiani-Scholze is crucial in arithmetic applications. I will survey these results, and discuss further development.
(Please contact Wansu Kim at for Zoom meeting info and any inquiry.)
Host: Wansu Kim     미정     2021-09-13 17:51:27
In his famous 1900 presentation, Hilbert proposed so-called the Hilbert’s 6thproblem, namely “Mathematical Treatment of the Axioms of Physics”. He mentioned that “Boltzmann's work on the principles of mechanics suggests the problem of developing mathematically the limiting processes, there merely indicated, which lead from the atomistic view to the laws of motion of continua.” In this lecture, we present some recent development of the Hilbert’s 6th problem in the Boltzmann theory when the various fluid models have natural “singularities” such as unbounded vorticity and formation of boundary layers.
Host: 배명진     Contact: Kyushik Kim (042-350-2702, qskim1)     미정     2021-08-27 23:49:54
The temporal credit assignment, the problem of determining which actions in the past are responsible for the current outcome (long-term cause and effect), is difficult to solve because one needs to backpropagate the error signal through space and time. Despite its computational challenges, humans are very good at solving this problem. Our lab uses reinforcement learning theory and algorithms to explore the nature of computations underlying the brain’s ability to solve the temporal credit assignment. I will outline two-fold approaches to this issue: (1) training a computational model from human behavioral data without underfitting and overfitting (Brain → AI) and (2) using the trained model to manipulate the way the human brain solves the temporal credit assignment problem (AI → brain).
Education/employments PhD, KAIST (2009)Postdoc, MIT (2010-2011), Caltech (2011-2015)Faculty, KAIST (2015-now) Honors/awards IBM Academic Research Award (2021)Google Faculty Research Award (2017)Della-Martin Fellowship (2014) KAIST Breakthroughs (2020)KAIST Songam Distinguished Research Award (2019)KAIST Top 10 Technologies (2019)KAIST Institute Faculty Award (2019) KIIS Young Investigator Award (2016)ICROS Young Investigator Award (2016)
Anyons are quasiparticles in two dimensions. They do not belong to the two classes of elementary particles, bosons and fermions. Instead, they obey Abelian or non-Abelian fractional statistics. Their quantum mechanical states are determined by fusion or braiding, to which braid groups and conformal field theories are naturally applied. Some of non-Abelian anyons are central in realization of topological qubits and topological quantum computing. I will introduce the basic properties of anyons and their recent experimental signatures observed in systems of topological order such as fractional quantum Hall systems and topological superconductors.
Host: 변재형     Contact: 김규식 (042-350-2702, qskim1)     영어     2021-08-28 00:48:51
The purpose of this talk is to mathematically investigate the formation of a plasma sheath, and to analyze the Bohm criterions which are required for the formation. Bohm derived originally the (hydrodynamic) Bohm criterion from the Euler–Poisson system. Boyd and Thompson proposed the (kinetic) Bohm criterion from kinetic point of view, and then Riemann derived it from the Vlasov–Poisson system. We study the solvability of boundary value problems of the Vlasov–Poisson system. On the process, we see that the kinetic Bohm criterion is a necessary condition for the solvability. The argument gives a simpler derivation of the criterion. Furthermore, the hydrodynamic criterion can be derived from the kinetic criterion. It is of great interest to find the relation between the solutions of the Vlasov–Poisson and Euler–Poisson systems. To clarify the relation, we also investigate the hydrodynamic limit of solutions of the Vlasov–Poisson system.
Host: 강문진     미정     2021-09-15 13:19:52
In hyperbolic 3 manifolds, by Marden, Thurston and Bonahon, every immersed surface of which the fundamental group is invectively embedded in the 3-manifold group is quasi-fuchsian or doubly degenerated. Surface subgroups of 3-manifold groups play an important rule in 3-manifold theory. For instance, some collection of immersed surfaces give a rise to a CAT(0) cube complex. Especially, in the usual construction of the CAT(0) cube complex, each immersed surface composing the collection is quasi-fuchsian. In this talk, I introduce the work by Cooper, Long and Reid. In hyperbolic mapping tori, the work gives a criterion to determine whether the given immersed surface is quasi-fuchsian or not. The criterion is given in terms of laminations induced in immersed surfaces.
Host: 백형렬     미정     2021-09-13 17:30:55
Questions about the mechanistic operation of biological systems are naturally formulated as stochastic processes, but confronting such models with data can be challenging. In this talk, I describe the essence of the difficulty, highlighting both the technical issues and the importance of the “plug-and-play property”. I then illustrate some effective approaches to efficient inference based on such models. I conclude by sketching promising new developments and describing some open problems.
Zoom link: 709 120 4849 (pw: 1234)
The objective of the study is to evaluate neural circuitry supporting a cognitive control task, and associated practice-related changes via acquisition of blood oxygenation level dependent (BOLD) signal collected using functional magnetic resonance imaging (fMRI). FMR images are acquired from participants engaged in antisaccade (generating a glance away from a cue) performance at two scanning sessions: 1) pre-practice before any exposure to the task, and 2) post-practice, after one week of daily practice on antisaccades, prosaccades (glancing towards a target) or fixation (maintaining gaze on a target). The three practice groups are compared across the two sessions, and analyses are conducted via the application of a model-free clustering technique based on wavelet analysis. This series of procedures is developed to address analysis problems inherent in fMRI data and is composed of several steps: data aggregation, no trend test, decorrelation, principal component analysis and K-means clustering. Also, we develop a semiparametric approach under shape invariance to quantify and test the differences in sessions and groups using the property that brain signals from a task-related experiment may exhibit a similar pattern in regions of interest across participants. We estimate the common function with local polynomial regression and estimate the shape invariance model parameters using evolutionary optimization methods. Using the proposed approach, we compare BOLD signals in multiple regions of interest for the three practice groups at the two sessions and quantify the effects of task practice in these groups.
I will talk about data science and Big Data, and how I view statistics in the data science and Big Data era. Next, I will briefly introduce my research areas in statistics. Finally, I will present some of my interdisciplinary research on functional magnetic resonance imaging data analysis.
Direct ZOOM link
While the presence of immune cells within solid tumours was initially viewed positively, as the host fighting to rid itself of a foreign body, we now know that the tumour can manipulate immune cells so that they promote, rather than inhibit, tumour growth. Immunotherapy aims to correct for this by boosting and/or restoring the normal function of the immune system. Immunotherapy has delivered some extremely promising results. However, the complexity of the tumour-immune interactions means that it can be difficult to understand why one patient responds well to immunotherapy while another does not. In this talk, we will show how mathematical, statistical and topological methods can contribute to resolving this issue and present recent results which illustrate the complementary insight that different approaches can deliver.
Zoom link: 709 120 4849 (pw: 1234)
Our current approach to cancer treatment has been largely driven by finding molecular targets, those patients fortunate enough to have a targetable mutation will receive a fixed treatment schedule designed to deliver the maximum tolerated dose (MTD). These therapies generally achieve impressive short-term responses, that unfortunately give way to treatment resistance and tumor relapse. The importance of evolution during both tumor progression, metastasis and treatment response is becoming more widely accepted. However, MTD treatment strategies continue to dominate the precision oncology landscape and ignore the fact that treatments drive the evolution of resistance. Here we present an integrated theoretical/experimental/clinical approach to develop treatment strategies that specifically embrace cancer evolution. We will consider the importance of using treatment response as a critical driver of subsequent treatment decisions, rather than fixed strategies that ignore it. We will also consider using mathematical models to drive treatment decisions based on limited clinical data. Through the integrated application of mathematical and experimental models as well as clinical data we will illustrate that, evolutionary therapy can drive either tumor control or extinction using a combination of drug treatments and drug holidays. Our results strongly indicate that the future of precision medicine shouldn’t be in the development of new drugs but rather in the smarter evolutionary, and model informed, application of preexisting ones.