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Professor Suil O Selected as Recipient of NRF-NSFC Core Cooperation Prgram
Professor Suil O has been selected as a recipient of the NRF-NSFC core cooperation program (National Research Foundation of Korea and National Natural Science Foundation of China), funded by the Ministry of Science and ICT. He will serve as the Co-Principal Investigator for the research project “Algebraic and structural problems of graphs on surfaces” for 3 years (2021.12.01~2024.11.30).
Author
Administrator
Registration Date
2021-11-12
Hits
261
[Seminar] Representation Learning for Complex Data and My Experience after Math Major at...
Speaker: Dr. Irene Kim Place: Online via Zoom, Zoom ID: 997 6634 3524 / Passcode: 556273 Time: Thu, 10/28/2021 - 11:00 About the speaker Dr. Irene Kim graduated from the University of California at Davis with Ph.D. in Statistics and graduated from Stony Brook University with Bachelor’s degree in Mathematics. Her research interests are in Machine Learning, deep learning, representation learning, and uncertainty quantification Abstract This talk will be divided into two parts where the first part will be on my current research, and the second part will be focused on sharing my experience at Stony Brook University and studying Math/Applied Math as an undergraduate degree. PART 1: In this talk, I will take an oil reservoir modeling and a history matching problem as an example to address the challenges of modern data analysis. As modern data become more complex and higher dimensional, finding a way to represent the data in a concise and useful form is an important problem. An auto-encoder can be used to find a low dimensional representation for an oil reservoir data and used for history matching problem. PART 2: Experience at Stony Brook University as a math major, life after graduation, job interview etc.
Author
Applied Mathematics & Statistics
Registration Date
2021-10-28
Hits
251
Welcome from SBU AMS Department!
A warm welcome from SBU AMS Department for SUNY Korea students!
Author
Administrator
Registration Date
2021-09-30
Hits
259
Professor Suil O Selected as Recipient of NRF-NSFC Joint Grant
Professor Suil O has been selected as a recipient of the NRF-NSFC Joint Grant (National Research Foundation of Korea and National Natural Science Foundation of China), funded by the Ministry of Science and ICT. He will serve as the principal investigator for the research project “Spectral Radii of Saturated Graphs” for 2 years (2021.09.01~2023.08.31).
Author
Administrator
Registration Date
2021-09-06
Hits
249
Hyerin Choi selected as 2021 NIMS-Industrial Mathematics Undergraduate Trainee
Hyerin Choi who is double majoring in AMS has been selected to National Institute for Mathematical Sciences as the Industrial Mathematics Undergraduate Trainee for Summer 2021. Hyerin will get the opportunity to practice solving industrial mathematics problems and experience industrial mathematics culture proliferation activities.
Author
Administrator
Registration Date
2021-07-09
Hits
220
Summer 2021 Math Boot Camp - Prof. Young-Seon Lee
We are pleased to announce that Professor Young-Seon Lee from the AMS Department will offer Summer 2021 Math Boot Camp! This camp can be beneficial to students who want to improve their math skills and math placement scores prior to the Math Placement Exam. This camp also provides a brief review of mathematical concepts, which is useful to prepare for SBU math courses. It is a first-come-first-serve basis. Do not miss this great opportunity! Please find the details about the Math Boot Camp from the poster, and if you are interested in registering for the Math Boot Camp this Summer, please feel free to contact YounJu Baek via younju.baek@sunykorea.ac.kr.
Author
Administrator
Registration Date
2021-07-08
Hits
219
Two Professors of AMS SUNY Korea received NRF Grant
Professor Young-Seon Lee has been selected as a recipient of the National Research Foundation research grant funded by the Ministry of Science and ICT. He will serve as a principal investigator for the research project entitled “Assessing and minimizing parameter uncertainty in mathematical models of cardiac cells” for two years and nine months (2021.06.01 ~ 2024.02.29) Professor Ky Tran has been selected as a recipient of the National Research Foundation research grant funded by the Ministry of Science and ICT. He will serve as a principal investigator for the research project entitled “Asymptotic behaviors, control, and applications of stochastic hybrid systems” for two years and nine months (2021.06.01 ~ 2024.02.29).
Author
Administrator
Registration Date
2021-06-02
Hits
215
[Seminar] Using Machine Learning to Advance Disparities Research in Access to Opioid Tre...
Speaker: Dr. Yinfei Kong Place: Online via Zoom. Zoom ID: 912 6831 4669, Passcode: 686304 Time: Fri, 05/14/2021 - 11:00 About the speaker Dr. Yinfei Kong is an Associate Professor at the Department of Information Systems and Decision Sciences, College of Business and Economics, California State University, Fullerton. He received his Ph.D. degree from the University of Southern California in 2016. He is particularly interested in deep learning, big data analytics, and applications in business and health care. (Web-page: https://sites.google.com/site/yinfeikong/; Email: yikong@fullerton.edu) Abstract We operationalize an intersectionality conceptual framework using a novel statistical approach and with these efforts improve estimation of disparities in access to treatment beyond race. We analyzed a sample of 941,286 treatment episodes collected in 2015, 2016, and 2017 in the United States from the Treatment Episodes Data Survey (TEDS-A). We also analyzed a subset of TEDS data from California (N=188,637) and Maryland (N=184,276), states with the largest sample of episodes. We conducted a retrospective subgroup analysis using a two-step approach called virtual twins. In step 1, we trained a classification model that gives the probability of waiting (one day or more). In step 2, we identified the subgroups with higher probability difference of waiting due to race. We tested three classification models for step 1 and identified that random forest was the classification model for step 1. Findings suggested that the following factors can define the subgroup more vulnerable to racial disparities: services setting, referral source, living arrangement, prior episodes, medication-assisted opioid treatment, and frequency of using the primary drug.
Author
Applied Mathematics & Statistics
Registration Date
2021-05-14
Hits
107
[Seminar] An Overview of Moreau’s Sweeping Process
Speaker: Prof. Emilio Vilches Place: Online via Zoom. Zoom ID: 518 570 2306 / Passcode: 096577 Time: Fri, 04/16/2021 - 11:00 About the speaker Emilio Vilches, Institute Engineering Sciences, Universidad de O’Higgins Abstract Differentialequations with nonsmooth componentsoccur in various situations. For example, they arise in mechanical systems if the effects of dry friction are included in the model or happen in the case of impacts. They are present in electrical circuits or biological systems if nonsmooth characteristics are used to represent switches. This seminar aims to introduce Moreau’s Sweeping Process, which is a class of nonsmooth dynamical systems involving normal cones to time-dependent moving sets. We review basic results, numerical methods, and practical applications in nonsmooth mechanics and electrical circuits. The current state of research and the main challenges will be discussed. This work has been supported by ANID-Chile under project Fondecyt de Iniciación 11180098.
Author
Applied Mathematics & Statistics
Registration Date
2021-04-16
Hits
121
Professor Hyunwook Koh Selected as Recipient of NRF Research Grant
Professor Hyunwook Koh has been selected as a recipient of the National Research Foundation research grant funded by the Ministry of Science and ICT. He will serve as a principal investigator for the research project entitled "Data-driven adaptive mediation analyses for human microbiome studies" for three years (2021.3 - 2024.2).
Author
Administrator
Registration Date
2021-03-02
Hits
191
[Seminar] Adaptive Statistical Methods for Human Microbiome Studies
Speaker: Hyunwook Koh, AMS SUNY Korea Place: Online via Zoom. Zoom ID: 485 595 6497 / Passcode: 504784 Time: Fri, 11/20/2020 - 16:30 Abstract The human microbiome is the totality of all microbes inhabiting in different organs (e.g., gut, mouth, skin) of the human body. The roles of the microbiome on human health or disease have been increasingly studied by the recent advance in high-throughput sequencing technologies. For example, the microbiome perturbation has been associated with a variety of health or disease status (e.g., obesity, diabetes, cancer, brain disorder), medical interventions (e.g., antibiotic or probiotic use) and behavioral or environmental factors (e.g., diet, residence, smoking, birth mode). However, the high complexity of the microbiome data (e.g., high-dimensionality, compositionality, zero-inflation, phylogenetic correlations) makes the downstream data analysis challenging, and thus there is a strong need for more sophisticated statistical methods. In this seminar, we study the human microbiome from the very beginnings of the subject to recent statistical methods (e.g., a- and b-diversity analysis). Then, we further discuss the potential and promise in statistical method development.
Author
Applied Mathematics & Statistics
Registration Date
2020-11-20
Hits
101
Three Professors of AMS SUNY Korea received NRF Grant
Professor Tan Cao, Professor Suil O, and Professor Myoungshic Jhun have been selected as a recipient of the National Research Foundation research grant funded by the Ministry of science and ICT. Prof. Cao’s project is on “Optimal Control of the Sweeping Process and Its Applications” for 3 years, Prof. O’s project is on “Factors and eigenvalues of graphs” for 3 years and Prof. Jhun’s project is on “On the Use of Adaptive Nearest Neighbors for Classification and Regression” for 2 years.
Author
Administrator
Registration Date
2020-06-03
Hits
240
Prof. Suil O published a research paper with students at Incheon Academy of Science and ...
In the summer of 2018, Professor Suil O gave a special mini-lecture about graph theory to students at Incheon Academy of Science and Arts as a part of the STEAM activity for the first-grade students in the school. With some of the students, he carried out a research work from March 2019 to February 2020 as for the second-grade students. The research work has been published online in a mathematics journal this year. He is going to carry out research work with some students in the school from the late of April 2020 again.
Author
Administrator
Registration Date
2020-04-17
Hits
258
Interview with Dr. Joseph Mitchell, Stony Brook AMS Chair
[SUNY Korea] Strength of AMS, SUNY Korea | Stony Brook AMS Chair Joseph Mitchell Check out the interview video https://youtu.be/F27fNGpSb-Y Do you want to know about Applied Mathematics & Statistics in SUNY Korea? http://sunykorea.ac.kr/page/sbu201095 Sign up for SUNY Korea's biweekly newsletter https://page.stibee.com/subscriptions...
Author
Administrator
Registration Date
2020-04-01
Hits
208
[Seminar] Neural dynamics and computation: Does brain compute like a computer?
Speaker: Il Memming Park, Department of Neurology and Behavior, Stony Brook University Place: B203 Time: Mon, 09/23/2019 - 19:00 Abstract How does the brain represent information and process it? By controlling and analyzing the input to and output from the brain -- the sensory stimulus and the behavior -- we have made great advances in modeling cognitive computation which is often well described by simple mathematical models such as a network of noisy leaky integrators and comparators. However, despite extensive efforts, how the brain implements those computations as a biophysical system is still largely unknown. One of the main obstacles is the subsampling problem: there are many (hundreds to hundreds of millions of) neurons across brain areas involved in transforming sensory information to producing the behavior, however, our experimental technology has been limited to observing neural signals from a small fraction of neurons in a handful of areas at the same time. This vast subsampling has limited our ability to infer the physical implementation of cognitive computation in the brain. We had to heavily rely on theoretical principles, intuition, and imagination as to how they might be implemented by a complex network of spiking neurons. Fortunately, recent advances in neural recording technology is allowing us access to several orders of magnitude more neurons at a high temporal precision. This is opening up new opportunities to directly infer the neural implementations: how external and internal information is represented in the population, and how it is transformed over time and across areas. Even for the simplest cognitive processes, such a bottom-up approach has not been successful so far in uncovering the underlying neural dynamics. In this presentation, I lay a principled approach that can tackle the subsampling problem by exploiting the low-dimensional structure of tasks and neural variability. This new approach to studying neural codes and computation is possible through advances in statistical and machine learning techniques aimed at extracting interpretable, i.e., scientifically useful, mathematical models. We have developed interpretable probabilistic models and Bayesian inference algorithms suitable for reverse engineering neural computation from large-scale population data.
Author
Applied Mathematics & Statistics
Registration Date
2019-9-23
Hits
108
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