Upcoming events

IMA Data Science Seminar

Data science seminars hosted by the The Institute for Mathematics and Its Applications (IMA) take place on Tuesdays from 1:25 p.m. - 2:25 p.m.

This week, William Leeb (University of Minnesota), will be giving the lecture.

View the full list of IMA data science seminars.

Graduate Programs Information Session

Prospective students can RSVP for an information session to learn about the following graduate programs:

  • Computer Science M.S.
  • Computer Science MCS
  • Computer Science Ph.D.
  • Data Science M.S.
  • Data Science Post-Baccalaureate Certificate

During the information session, we will go over the following:

  • Requirements (general)
  • Applying
  • Prerequisite requirements
  • What makes a strong applicant
  • Funding
  • Resources
  • Common questions
  • Questions from attendees

IMA Data Science Seminar

Data science seminars hosted by the The Institute for Mathematics and Its Applications (IMA) take place on Tuesdays from 1:25 p.m. - 2:25 p.m.

This week, Vahan Huroyan (University of Arizona), will be giving the lecture.

View the full list of IMA data science seminars.

IMA Data Science Seminar: Large-Scale Semi-supervised Learning via Graph Structure Learning over High-dense Points

Data science seminars hosted by the The Institute for Mathematics and Its Applications (IMA) take place on Tuesdays from 1:25 p.m. - 2:25 p.m.

This week's speaker, Li Wang (University of Texas at Arlington), will be giving a talk titled "Large-Scale Semi-supervised Learning via Graph Structure Learning over High-dense Points".

Abstract

We focus on developing a novel scalable graph-based semi-supervised learning (SSL) method for a small number of labeled data and a large amount of unlabeled data. Due to the lack of labeled data and the availability of large-scale unlabeled data, existing SSL methods usually encounter either suboptimal performance because of an improper graph or the high computational complexity of the large-scale optimization problem. In this paper, we propose to address both challenging problems by constructing a proper graph for graph-based SSL methods. Different from existing approaches, we simultaneously learn a small set of vertexes to characterize the high-dense regions of the input data and a graph to depict the relationships among these vertexes. A novel approach is then proposed to construct the graph of the input data from the learned graph of a small number of vertexes with some preferred properties. Without explicitly calculating the constructed graph of inputs, two transductive graph-based SSL approaches are presented with the computational complexity in linear with the number of input data. Extensive experiments on synthetic data and real datasets of varied sizes demonstrate that the proposed method is not only scalable for large-scale data, but also achieve good classification performance, especially for extremely small number of labels.

Biography

Dr. Li Wang is currently an assistant professor with Department of Mathematics and Department of Computer Science Engineering, University of Texas at Arlington, Texas, USA. She worked as a research assistant professor with Department of Mathematics, Statistics, and Computer Science at University of Illinois at Chicago, Chicago, USA from 2015 to 2017. She worked as the Postdoctoral Fellow at University of Victoria, BC, Canada in 2015 and Brown University, USA, in 2014. She received her Ph.D. degree in Department of Mathematics at University of California, San Diego, USA, in 2014. Her research interests include data science, large-scale optimization and machine learning.

View the full list of IMA data science seminars.

CS&E Colloquium: Humanizing Data with Interactive Visualization

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m.

This week's speaker, Daniel F. Keefe (University of Minnesota; a member of the data science faculty), will be giving a talk titled "Humanizing Data with Interactive Visualization".

Abstract

Data-intensive computing is central to so many aspects of society today.  Scientists and engineers continue to collect and simulate data that challenge our most sophisticated computational tools.  However, today's users of data-intensive computing extend well beyond these "traditional users" to include, for example, designers, visual artists, the general public, and Indigenous communities.  Our research explores how processes of analyzing and communicating about data will change in the future and can better serve this wide range of users and computing applications.  Our methods, employed with interdisciplinary collaborators across a range of projects, include a combination of novel visual designs, interactive techniques, and computer graphics and data processing algorithms.  In this talk, I will present specific examples that include: 1) advanced art-inspired algorithms for rendering multi-variate global climate data in immersive environments, 2) interactive simulation-based engineering design tools for understanding supercomputer ensemble datasets, and 3) interdisciplinary cultural revitalization and data storytelling within the UMN Indigenous Futures Grand Challenges project.

Biography

Dan Keefe is a Distinguished University Teaching Professor and Associate Professor in the Department of Computer Science and Engineering at the University of Minnesota. His research centers on interactive data visualization, immersive computer graphics, art+science collaborations, and computing for social good. Keefe’s awards include the National Science Foundation CAREER award; the University of Minnesota Guillermo E. Borja Award for research and scholarly accomplishments at the time of tenure; the University of Minnesota McKnight Land-Grant Professorship; and the 3M Non-tenured Faculty Award. He also shares multiple IEEE and ACM conference best paper awards with his students and collaborators.  Outside of computer science venues, Keefe has published and exhibited work in top international venues for digital art, such as South by Southwest, Northern Spark, ISEA, and Leonardo.  His research and art practice have been supported by grants from the National Science Foundation; the National Institutes of Health; the National Academies Keck Futures Initiative; the US Forest Service; the City of Minneapolis office of Arts, Culture, and the Creative Economy; and industry. Before joining the University of Minnesota, Keefe did post-doctoral work at Brown University jointly with the departments of Computer Science and Ecology and Evolutionary Biology and with the Rhode Island School of Design. He received the Ph.D. in 2007 from Brown University’s Department of Computer Science and the B.S. in Computer Engineering summa cum laude from Tufts University in 1999.

IMA Data Science Seminar

Data science seminars hosted by the The Institute for Mathematics and Its Applications (IMA) take place on Tuesdays from 1:25 p.m. - 2:25 p.m.

This week, Tyler Maunu (Massachusetts Institute of Technology), will be giving the lecture.

View the full list of IMA data science seminars.

IMA Data Science Seminar: How COVID-19 has Changed the World and What the Future Holds

Data science seminars hosted by the The Institute for Mathematics and Its Applications (IMA) take place on Tuesdays from 1:25 p.m. - 2:25 p.m.

This week's speaker, Michael Osterholm (University of Minnesota), will be giving a talk titled "How COVID-19 has Changed the World and What the Future Holds".

Abstract

This presentation will provide a current and in depth review of the COVID-19 pandemic. It will also provide a glimpse into the future as to how this pandemic will continue to unfold and the impact it will have worldwide.

View the full list of IMA data science seminars.

IMA Data Science Seminar

Data science seminars hosted by the The Institute for Mathematics and Its Applications (IMA) take place on Tuesdays from 1:25 p.m. - 2:25 p.m.

This week, Anna Little (The University of Utah), will be giving the lecture.

View the full list of IMA data science seminars.

IMA Data Science Seminar

Data science seminars hosted by the The Institute for Mathematics and Its Applications (IMA) take place on Tuesdays from 1:25 p.m. - 2:25 p.m.

This week, Levon Nurbekyan (University of California, Los Angeles), will be giving the lecture.

View the full list of IMA data science seminars.

IMA Data Science Seminar

Data science seminars hosted by the The Institute for Mathematics and Its Applications (IMA) take place on Tuesdays from 1:25 p.m. - 2:25 p.m.

This week, Naoki Saito (University of California, Davis), will be giving the lecture.

View the full list of IMA data science seminars.

The University of Minnesota and the greater Twin Cities area hosts many activities related to data science in a wide variety of specializations. Visit the following sites for more information on these activities.