BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Biomedical Mathematics Group - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Biomedical Mathematics Group
X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20200101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20211021T110000
DTEND;TZID=Asia/Seoul:20211021T120000
DTSTAMP:20260410T001223
CREATED:20211103T170000Z
LAST-MODIFIED:20210930T040222Z
UID:4787-1634814000-1634817600@www.ibs.re.kr
SUMMARY:Scaling in development
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234)\n\nAbstract: \n Within a given species\, fluctuations in egg or embryo size is unavoidable. Despite this\, the gene expression pattern and hence the embryonic structure often scale in proportion with the body length. This scaling phenomenon is very common in development and regeneration and has long fascinated scientists. I will first discuss a generic theoretical framework to show how scaling gene expression pattern can emerge from non-scaling morphogen gradients. I will then demonstrate that the Drosophila gap gene system achieves scaling in a way that is entirely consistent with our theory. Remarkably\, a parameter-free model based on the theory quantitatively accounts for the gap gene expression pattern in nearly all morphogen mutants. Furthermore\, the regulation logic and the coding/decoding strategy of the gap gene system can be revealed. Our work provides a general theoretical framework on a large class of problems where scaling output is induced by non-scaling input\, as well as a unified understanding of scaling\, mutants’ behavior and regulation in the Drosophila gap gene and related systems.
URL:https://www.ibs.re.kr/bimag/event/2021-10-21/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/07/resize.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20211007T110000
DTEND;TZID=Asia/Seoul:20211007T120000
DTSTAMP:20260410T001223
CREATED:20211006T170000Z
LAST-MODIFIED:20211230T031435Z
UID:4850-1633604400-1633608000@www.ibs.re.kr
SUMMARY:A temporal signaling code to specify immune responses
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nAbstract: \nImmune sentinel cells must initiate the appropriate immune response upon sensing the presence of diverse pathogens or immune stimuli. To generate stimulus-specific gene expression responses\, immune sentinel cells have evolved a temporal code in the dynamics of stimulus responsive transcription factors. I will present recent works 1) using an information theoretic approach to identify the codewords\, termed “signaling codons”\, 2) using a machine learning approach to characterize their reliability and points of confusion\, and 3) dynamical systems modeling to characterize the molecular circuits that allow for their encoding. I will present progress on how the temporal code may be decoded to specify immune responses.  Further\, I will discuss to what extent such a code may be harnessed to achieve greater pharmacological specificity when therapeutically targeting pleiotropic signaling hubs. \nNFκB Signaling: information theory\, signaling codons \nAdelaja\, A.\, Taylor\, B.\, Sheu\, K.M.\, Liu\, Y.\, Luecke\, S.\, Hoffmann\, A. 2021 Six distinct NFκB signaling codons convey discrete information to distinguish stimuli and enable appropriate macrophage responses. Immunity\, 54\, pp.916-930. e7. PMID: 33979588 \nTang\, Y.\, Adelaja\, A.\, Ye\, X\, Deeds\, E.\, Wollman\, R.\, Hoffmann\, A. 2021. Quantifying information accumulation encoded in the dynamics of biochemical signaling. Nature Communications 12\, pp.1-10 \nDecoding signaling codons to specify immune responses \nSen S.\, Cheng\, Z.\, Sheu\, K.\, Chen\, E.Y.H.\, Hoffmann\, A. 2020 Gene Regulatory Strategies that Decode the Duration of NFkB Dynamics Contribute to LPS- versus TNF-Specific Gene Expression. Cell Systems\, 10\, pp.1-14. PMID:31972132\, PMC7047529 \nCheng\, Q.J.\, Ohta\, S.\, Sheu\, K.M.\, Spreafico\, R.\, Adelaja\, A.\, Taylor\, B.\, Hoffmann\, A.  2021 NFκB dynamics determine the stimulus-specificity of epigenomic reprogramming in macrophages. Science\, 372\, pp.1349-1353; PMID: 34140389. \nPharmacologic manipulation of the code \nBehar\, M.\, Barken\, D.\, Werner\, S.L.\, Hoffmann\, A. 2013  The Dynamics of Signaling as a Pharmacological Target.  Cell\, 155\, pp.448-461. PMID: 24120141\, PMC3856316
URL:https://www.ibs.re.kr/bimag/event/2021-10-07/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/10/AlexanderHoffmann_profile_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210916T110000
DTEND;TZID=Asia/Seoul:20210916T120000
DTSTAMP:20260410T001223
CREATED:20210915T170000Z
LAST-MODIFIED:20211230T030915Z
UID:4529-1631790000-1631793600@www.ibs.re.kr
SUMMARY:Stochastic processes as scientific instruments: efficient inference based on stochastic dynamical systems
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234)\n\nAbstract: 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.
URL:https://www.ibs.re.kr/bimag/event/2021-09-16/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/09/imagev2.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210908T170000
DTEND;TZID=Asia/Seoul:20210908T180000
DTSTAMP:20260410T001223
CREATED:20210907T230000Z
LAST-MODIFIED:20210907T103108Z
UID:4648-1631120400-1631124000@www.ibs.re.kr
SUMMARY:[CANCELED] Approaches to understanding tumour-immune interactions
DESCRIPTION:CANCELED due to unexpected circumstances\nThis talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nAbstract: 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.
URL:https://www.ibs.re.kr/bimag/event/2021-09-08/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/06/Helen-Byrne_Photo_crop2.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210902T100000
DTEND;TZID=Asia/Seoul:20210902T110000
DTSTAMP:20260410T001223
CREATED:20210901T160000Z
LAST-MODIFIED:20211230T030825Z
UID:4540-1630576800-1630580400@www.ibs.re.kr
SUMMARY:Exploiting evolution to design better cancer therapies
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234)\n\nAbstract: 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.
URL:https://www.ibs.re.kr/bimag/event/2021-09-02/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/09/AndersonAlexander2.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210728T170000
DTEND;TZID=Asia/Seoul:20210728T180000
DTSTAMP:20260410T001223
CREATED:20210407T040301Z
LAST-MODIFIED:20210717T235315Z
UID:4383-1627491600-1627495200@www.ibs.re.kr
SUMMARY:Theory and design of molecular integral feedback controllers
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234)\nAbstract: \nHomeostasis is a recurring theme in biology that ensures that regulated variables robustly adapt to environmental perturbations. This robust perfect adaptation feature is achieved in natural circuits by using integral control\, a negative feedback strategy that performs mathematical integration to achieve structurally robust regulation. Despite its benefits\, the synthetic realization of integral feedback in living cells has remained elusive owing to the complexity of the required biological computations. In this talk I will show that there is a single fundamental biomolecular controller topology that realizes integral feedback and achieves robust perfect adaptation in arbitrary intracellular networks with noisy dynamics. This adaptation property is guaranteed both for the population-average and for the time-average of single cells. On the basis of this concept\, I will describe a genetically engineered synthetic integral feedback controller in living cells and demonstrate its tunability and adaptation properties. A growth-rate control application in Escherichia coli shows the intrinsic capacity of our integral controller to deliver robustness and highlights its potential use as a versatile controller for regulation of biological variables in uncertain networks. These results provide conceptual and practical tools in the area of cybergenetics\, for engineering synthetic controllers that steer the dynamics of living systems.
URL:https://www.ibs.re.kr/bimag/event/2021-07-28/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/04/MustafaKhammash_profile-e1617768310550.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210714T170000
DTEND;TZID=Asia/Seoul:20210714T180000
DTSTAMP:20260410T001223
CREATED:20210406T074701Z
LAST-MODIFIED:20210420T215116Z
UID:4368-1626282000-1626285600@www.ibs.re.kr
SUMMARY:Inference for Circadian Pacemaking
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nAbstract: Organisms have evolved an internal biological clock which allows them to temporally regulate and organize their physiological and behavioral responses to cope in an optimal way with the fundamentally periodic nature of the environment. It is now well established that the molecular genetics of such rhythms within the cell consist of interwoven transcriptional-translational feedback loops involving about 15 clock genes\, which generate circa 24-h oscillations in many cellular functions at cell population or whole organism levels. We will present statistical methods and modelling approaches that address newly emerging large circadian data sets\, namely spatio-temporal gene expression in SCN neurons and rest-activity actigraph data obtained from non-invasive e-monitoring\, both of which provide unique opportunities for furthering progress in understanding the synchronicity of circadian pacemaking and address implications for monitoring patients in chronotherapeutic healthcare.
URL:https://www.ibs.re.kr/bimag/event/2021-07-14/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/04/barbel_finkenstadt_rand_crop-e1617768405446.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210610T110000
DTEND;TZID=Asia/Seoul:20210610T120000
DTSTAMP:20260410T001223
CREATED:20210406T074242Z
LAST-MODIFIED:20210607T080017Z
UID:4364-1623322800-1623326400@www.ibs.re.kr
SUMMARY:Towards individualized predictions of human sleep and circadian timing
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nAbstract: Accurate assessment of circadian timing is critical to many applications\, including timing of drug delivery\, prediction of neurobehavioral performance\, and optimized scheduling of sleep. Current methods for measuring circadian timing are onerous and do not produce results in real time. Mathematical models have been developed for predicting circadian timing from an individual’s light exposure patterns\, which can be applied to passively collected data. These models are now well validated in the field at the group-average level\, but tend to perform poorly at the individual level. One potential solution to this problem is the estimation of model parameters at an individual level. We explored whether this approach could be applied to parameters relating to an individual’s light sensitivity. We found that these parameters can account for inter-individual and intra-individual variation in circadian timing. These findings demonstrate that model parametrization based on physiological measurements of light sensitivity could lead to more accurate individual-level circadian phase prediction.
URL:https://www.ibs.re.kr/bimag/event/2021-06-10/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/04/AndrewPhillips_profile_crop-e1617768455279.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210526T170000
DTEND;TZID=Asia/Seoul:20210526T180000
DTSTAMP:20260410T001223
CREATED:20210311T114629Z
LAST-MODIFIED:20210407T040940Z
UID:4248-1622048400-1622052000@www.ibs.re.kr
SUMMARY:Neural network aided approximation and parameter inference of stochastic models of gene expression
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nAbstract: Non-Markov models of stochastic biochemical kinetics often incorporate explicit time delays to effectively model large numbers of intermediate biochemical processes. Analysis and simulation of these models\, as well as the inference of their parameters from data\, are fraught with difficulties because the dynamics depends on the system’s history. Here we use an artificial neural network to approximate the time-dependent distributions of non-Markov models by the solutions of much simpler time-inhomogeneous Markov models; the approximation does not increase the dimensionality of the model and simultaneously leads to inference of the kinetic parameters. The training of the neural network uses a relatively small set of noisy measurements generated by experimental data or stochastic simulations of the non-Markov model. We show using a variety of models\, where the delays stem from transcriptional processes and feedback control\, that the Markov models learnt by the neural network accurately reflect the stochastic dynamics across parameter space.
URL:https://www.ibs.re.kr/bimag/event/2021-05-26/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/03/DjvWsbfJ-e1617756286824.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210421T170000
DTEND;TZID=Asia/Seoul:20210421T183000
DTSTAMP:20260410T001223
CREATED:20210324T050549Z
LAST-MODIFIED:20210421T074343Z
UID:4307-1619024400-1619029800@www.ibs.re.kr
SUMMARY:Advice to my younger self
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nFacebook live streaming: https://www.facebook.com/10226475900150025/videos/10226475902790091 \nAge brings the benefit of experience and looking back at my job as a professor\, there are a couple of things that fall into the category “I wish someone had told me that earlier”. In this seminar\, I would like to share some of the things I learned and which\, I hope\, will be useful for younger scientists. \nThe questions I will touch upon include \n\n\n\nWhat is productivity\, for a scientist?\nWhat are qualities of successful people?\nHow can one create motivation and success?\nHow to organize myself? (project management; getting things done)\nHow to communicate effectively?\nSeeking fulfillment\n\n\n\nThe seminar is targeted at PhD students\, postdocs\, and junior group leaders. \n \n 
URL:https://www.ibs.re.kr/bimag/event/2021-04-21/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/03/olaf-wolkenhauer-e1617756681631.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210415T110000
DTEND;TZID=Asia/Seoul:20210415T120000
DTSTAMP:20260410T001223
CREATED:20210314T044747Z
LAST-MODIFIED:20210412T021311Z
UID:4258-1618484400-1618488000@www.ibs.re.kr
SUMMARY:Dynamics-based data science in biology
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nAbstract: Life science has been a prosperous subject for a long time\, and is still developing with high speed now. One of its major aims is to study the mechanisms of various biological processes on the basis of biological big-data. Many statistics-based methods have been proposed to catch the essence by mining those data\, including the popular category classification\, variables regression\, group clustering\, statistical comparison\, dimensionality reduction\, and component analysis\, which\, however\, mainly elucidate static features or steady behavior of living organisms due to lack of temporal data. But\, a biological system is inherently dynamic\, and with increasingly accumulated time-series data\, dynamics-based approaches based on physical and biological laws are demanded to reveal dynamic features or complex behavior of biological systems. In this talk\, I will present a new concept “dynamics-based data science” and the approaches for studying dynamical bio-processes\, including dynamical network biomarkers (DNB)\, autoreservoir neural networks (ARNN) and partical cross-mapping. These methods are all data-driven or model-free approaches but based on the theoretical frameworks of nonlinear dynamics. We show the principles and advantages of dynamics-based data-driven approaches as explicable\, quantifiable\, and generalizable. In particular\, dynamics-based data science approaches exploit the essential features of dynamical systems in terms of data\, e.g. strong fluctuations near a bifurcation point\, low-dimensionality of a center manifold or an attractor\, and phase-space reconstruction from a single variable by delay embedding theorem\, and thus are able to provide different or additional information to the traditional approaches\, i.e. statistics-based data science approaches. The dynamical-based data science approaches will further play an important role in the systematical research of biology and medicine in future.
URL:https://www.ibs.re.kr/bimag/event/2021-04-15/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/03/LC_profile2.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210325T110000
DTEND;TZID=Asia/Seoul:20210325T120000
DTSTAMP:20260410T001224
CREATED:20210301T013812Z
LAST-MODIFIED:20210406T075105Z
UID:4167-1616670000-1616673600@www.ibs.re.kr
SUMMARY:Daniel Forger\, The mathematics of the wearables with applications to circadian rhythms and sleep
DESCRIPTION:This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) \nAbstract: Millions of individuals track their steps\, heart rate\, and other physiological signals through wearables. This data scale is unprecedented; I will describe several of our apps and ongoing studies\, each of which collects wearable and mobile data from thousands of users\, even in > 100 countries. This data is so noisy that it often seems unusable and in desperate need of new mathematical techniques to extract key signals used in the (ode) mathematical modeling typically done in mathematical biology. I will describe several techniques we have developed to analyze this data and simulate models\, including gap orthogonalized least squares\, a new ansatz for coupled oscillators\, which is similar to the popular ansatz by Ott and Antonsen\, but which gives better fits to biological data and a new level-set Kalman Filter that can be used to simulate population densities. My focus applications will be determining the phase of circadian rhythms\, the scoring of sleep and the detection of COVID with wearables.
URL:https://www.ibs.re.kr/bimag/event/2021-03-25/
LOCATION:ZOOM ID: 709 120 4849 (ibsbimag)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium,Seminar
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2021/03/dannyg.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
END:VCALENDAR