Past events

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

The BIPOC Voices in STEM speaker series is free and open to students of all identities who are interested in or currently studying STEM at the University of Minnesota. The series highlights the experiences of UMN alumni who have current or past careers or degrees in STEM. Registration is required.

Hardisha White from General Mills will speak about their experiences as a first generation college student and choice to relocate for work. White is looking forward to sharing their experiences with you.

Register for the BIPOC Voices in STEM Zoom event
 

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

This week's speaker, Favonia (University of Minnesota), will be giving a talk titled "Program Testing with Polymorphic Types."

Abstract

Many programming languages allow programmers to write polymorphic programs that work for data of different types, which significantly reduces code duplication. What is less known is that polymorphic programs are also easier to test if correct techniques are applied. The intuition is that fewer programs are polymorphic, and thus lesser testing is needed to distinguish correct programs from incorrect ones. The ignorance of a program about its input data is its greatest strength.

In this talk, I will discuss techniques for testing polymorphic programs, including the recent progress made by my student Zhuyang Wang and me.

Biography

Favonia is an assistant professor at the University of Minnesota. They received their Ph.D. in 2017 from Carnegie Mellon University. Their main research interest is the correctness of programs and mathematical proofs, and they have been working on proof mechanization, type theory, programming language theory, and property-based testing.

Topic

Medical Device Cybersecurity: Where Safety and Security Intersect

Speakers

Bill Aerts, Managing Director of the U of MN Center for Medical Device Cybersecurity. Bill was the Executive Director of the Archemedies Center for Healthcare and Medical Device Security at the University of Michigan and the former Director of Global Product Security at Medtronic. Bill has a BA in Management and Economics from the University of Wisconsin - Green Bay.

Dan Mooradian, Ph.D., Senior Fellow and James J. Renier Chair in Technology Management and Director of Graduate Studies for the U of MN MS in Medical Device Innovation and a member of the CMDC faculty. Dan is a Ph.D. Pathologist by training with more than 15 years experience in the Medical Device Industry focusing on Research & Development, Product Development, Clinical, and Regulatory Science.

Description

In an era where medical devices are increasingly a part of the Internet of Things (IoT), the benefits of connectivity (i.e., more convenient and cost-effective healthcare delivery with better clinical outcomes) come with increased security risk. Medical devices, like other computer systems, may be vulnerable to security breaches, potentially impacting both safety and effectiveness. Device manufacturers, healthcare providers, and regulators have a shared responsibility for reducing (and eliminating where possible) cybersecurity vulnerabilities and threats that contribute to these risks. Bill and Dan will share their experiences as leaders working with Medical Device Manufacturers, Healthcare Providers, and Regulators in this exciting and fast-growing field.

This week's speaker, Stephen Guy, will be giving a talk titled "Simulating Human Motions for Social AI."

Biography

Stephen J. Guy is an associate professor in the Department of Computer Science & Engineering at the University of Minnesota. His research focuses on the development of artificial intelligence for use in autonomous robotics (e.g., collision avoidance and path planning under uncertainty) and computer simulations of human movement and behavior (e.g., crowd simulation and virtual characters). Stephen's work has had a wide influence in games, VR, and real-time graphics industries: his work on motion planning has been licensed by Relic Entertainment, EA, and other digital entertainment companies; he has been a speaker in the AI Summit at GDC, the leading conference in the games development industry. He is the recipient of several awards including the Charles E. Bowers Faculty Teaching Award and multiple best paper awards for his research work in simulation and planning. Stephen's academic work has appeared in top venues for robotics, AI and computer graphics including SIGGRAPH, IJRR, IEEE Trans. on Robotics, AAMAS, AAAI, and IJCAI. His work on simulating virtual humans has been widely covered in popular media including newspapers, magazines, documentaries, and late-night TV. Prior to joining Minnesota, he received his Ph.D. in Computer Science in 2012 from the University of North Carolina - Chapel Hill with support from fellowships from Google, Intel, and the UNCF, and his B.S. in Computer Engineering with honors from the University of Virginia in 2006.

We invite you to attend the Data Science Poster Fair! This semester's event will be held virtually via GatherTown on Friday, December 3 from 11:30 a.m. - 1:30 p.m.

Every year, data science M.S. students present their capstone projects during this event. The poster fair is open to the public and all interested undergraduate and graduate students, alumni, staff, faculty, and industry professionals are encouraged to attend. Attendees will have the ability to move between poster presentations as they please.

View the full schedule on the Data Science website

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, Yangyang Xu (Rensselaer Polytechnic Institute), will be giving a talk titled "First-order methods for nonlinear-constrained optimization."

Abstract

First-order methods (FOMs) have recently been applied and analyzed for solving problems with complicated functional constraints. Existing works show that FOMs for functional constrained problems have lower-order convergence rates than those for unconstrained problems. In particular, an FOM for a smooth strongly-convex problem can have linear convergence, while it can only converge sublinearly for a constrained problem if the projection onto the constraint set is prohibited. In this talk, I will first give a lower-bound result of FOM for solving affine-constrained problems. Then I will show that the slower convergence is caused by the large number of functional constraints but not the constraints themselves. When there are only O(1) functional constraints, I will show that an FOM can have almost the same convergence rate as that for solving an unconstrained problem, even without the projection onto the feasible set. Finally, I will give an adaptive primal-dual method for problems with many constraints. Experimental results on quadratically-constrained quadratic programs will be shown to demonstrate the theory.

Biography

Yangyang Xu is now a tenure-track assistant professor in the Department of Mathematical Sciences at Rensselaer Polytechnic Institute. He received his B.S. in Computational Mathematics from Nanjing University in 2007, M.S. in Operations Research from the Chinese Academy of Sciences in 2010, and Ph.D. from the Department of Computational and Applied Mathematics at Rice University in 2014. His research interests are mainly in optimization theory and methods and their applications, such as in machine learning, statistics, and signal processing. His research has been supported by NSF and IBM. He was awarded the gold medal in the 2017 International Consortium of Chinese Mathematicians (ICCM).

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

This week's speaker, Andreas Zeller (CISPA Helmholtz Center for Information Security and Saarland University), will be giving a talk titled "Learning the Language of Failure."

Abstract

Software test generation (fuzzing) can be made much more effective if one knows what to search for. But how can users inform fuzzers about the program, its domain, and its input language? And how can they control what a fuzzer should do?

In this talk, I present and introduce tools and techniques that allow users to specify and learn the languages of program inputs, from recursive languages such as JavaScript to complex binary inputs, leveraging hundreds of existing format specifications. Our all-new FormatFuzzer tool that produces thousands of valid inputs per second, is now available as open source.

Biography

Andreas Zeller is faculty at the CISPA Helmholtz Center for Information Security and professor for Software Engineering at Saarland University, both in Saarbrücken, Germany. His research on automated debugging, mining software archives, specification mining, and security testing has proven highly influential. Zeller is an ACM Fellow and holds an ACM SIGSOFT Outstanding Research Award.

The University of Minnesota will be closed (floating holiday).

View the full schedule of University holidays.
 

The University of Minnesota will be closed in observance of Thanksgiving Day.

View the full schedule of University holidays.