Events

Join us for the University of Minnesota Day of Data 2022! This year will feature a series of virtual events that foster data enthusiasm and encourage critical thinking around the role of data across our University and in society as a whole.

All experience levels are welcome

This event is open to all students, faculty, staff, and alumni from all University of Minnesota campuses. The event is free of charge to attend. Whether you are new to data or a data expert, you are welcome! Come explore some exciting ways that "data matters" across disciplines.

Connect with other data enthusiasts

Many people and groups across the University are implementing interesting approaches to data, methods, and workflows, but we don’t always get a chance to share our work across departments and units. U of M Day of Data offers virtual opportunities to connect with other data enthusiasts to share and learn from each other.

View the UMN Day of Data webpage for more information.

The Institute for Mathematics and Its Applications (IMA) Data Science Seminars are a forum for data scientists of IMA academic and industrial partners to discuss and learn about recent developments in the broad area of data science. The seminars take place on Tuesdays from 1:25 p.m. - 2:25 p.m

This week's speaker, Eran Halperin (UnitedHealth Group), will be giving a talk titled "New Methods for Disease Prediction using Imaging and Genomics."

You may attend the talk either in person in Walter 402 or registering via Zoom.

Abstract

Diagnosis and prediction of health outcomes using machine learning has shown major advances over the last few years. Some of the major challenges remaining in the field include the sparsity of electronic health records data, and the scarcity of high-quality labeled data. In this talk, I will present a couple of examples where we partially address these challenges. Specifically, I will provide an overview of a new neural network architecture for the analysis of three-dimensional medical imaging data (optical coherence tomography) under scarce labeled data and demonstrate applications in age-related macular degeneration. Then, I will describe in more detail a new Bayesian framework for the imputation of electronic health records (addressing sparsity) using DNA methylation data. Our framework involves a tensor deconvolution of bulk DNA methylation to obtain cell-type-specific methylation from bulk data, which we demonstrate is predictive of many clinical outcomes.

Biography

Dr. Eran Halperin is the SVP of AI and Machine Learning in Optum Labs (United Health Group), and a professor in the departments of Computer Science, Computational Medicine, Anesthesiology, and Human Genetics at UCLA. Prior to his current position, he held research and postdoctoral positions at the University of California, Berkeley, the International Computer Science Institute in Berkeley, Princeton University, and Tel-Aviv University. Dr. Halperin’s lab developed computational and machine learning methods for a variety of health-related applications, including different genomic applications (genetics, methylation, microbiome, single-cell RNA), and medical applications (medical imaging, physiological waveforms, and electronic medical records). He published more than 150 peer-reviewed publications, and he received various honors for academic achievements, including the Rothschild Fellowship, the Technion-Juludan prize for technological contribution to medicine, the Krill prize, and he was elected as an International Society of Computational Biology (ISCB) fellow.

In collaboration with the Minnesota Center for Industrial Mathematics, the Industrial Problems Seminars are a forum for industrial researchers to offer a first-hand glimpse into industrial research. The seminars take place Fridays from 1:25 p.m. - 2:25 p.m.

This week's speaker is Tetiana Grinberg (Intel Corporation).

The UMN Machine Learning Seminar Series brings together faculty, students, and local industrial partners who are interested in the theoretical, computational, and applied aspects of machine learning, to pose problems, exchange ideas, and foster collaborations. The talks are every Thursday from 12 p.m. - 1 p.m. during the Fall 2021 semester.

This week's speaker is Lingzhou Xue (Penn State).

In collaboration with the Minnesota Center for Industrial Mathematics, the Industrial Problems Seminars are a forum for industrial researchers to offer a first-hand glimpse into industrial research. The seminars take place Fridays from 1:25 p.m. - 2:25 p.m.

This week's speaker is Hamit Hamutcu (Initiative for Analytics and Data Science Standards).

The UMN Machine Learning Seminar Series brings together faculty, students, and local industrial partners who are interested in the theoretical, computational, and applied aspects of machine learning, to pose problems, exchange ideas, and foster collaborations. The talks are every Thursday from 12 p.m. - 1 p.m. during the Fall 2021 semester.

This week's speaker is Yangyang Xu (Rensselaer Polytechnic Institute).

Hear from top national experts on how the COVID-19 pandemic is changing research ethics. Experts will discuss how to advance ethics and equity when conducting pandemic research, how to reconcile the need for research with the clinical imperative to save lives, and how the pandemic is affecting research design. As a large, public, land-grant research university, we aim to explore these vital issues with our faculty, staff, trainees, students, and community, as well as a national audience.

View the full webpage here

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