Upcoming events

UMN Machine Learning Seminar: Tackling the Challenges of Next-generation Healthcare: NVIDIA’s Applied Research in Medical Imaging

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, Holger Roth (NVIDIA), will be giving a talk titled "Tackling the Challenges of Next-generation Healthcare: NVIDIA’s Applied Research in Medical Imaging."

Abstract

Recent advances in computer vision and artificial intelligence caused a paradigm shift in medical image computing and radiological image analysis. Deep learning has been widely applied to many radiological applications, replacing, or working together with conventional methods. The advantage of being able to learn from that data directly is promising for many imaging tasks. Some key factors and current challenges preventing the widespread adaption of machine learning techniques in the clinic are algorithmic considerations, computational power, and, most critically, high-quality data for training.

NVIDIA wants to provide solutions to make the widespread adoption of deep learning and artificial intelligence easier in the real world. This talk will highlight NVIDIA’s efforts in the healthcare sector and medical imaging research, for example, around federated learning and COVID-19 image analysis, and introduce platforms & hardware considerations for modern machine learning at scale.

Biography

Holger Roth is a Sr. Applied Research Scientist at NVIDIA focusing on deep learning for medical imaging. He has been working closely with clinicians and academics over the past several years to develop deep learning based medical image computing and computer-aided detection models for radiological applications. He is an Associate Editor for IEEE Transactions of Medical Imaging and holds a Ph.D. from University College London, UK. In 2018, he was awarded the MICCAI Young Scientist Publication Impact Award.

Minnesota Natural Language Processing Seminar Series: Natural Language Inference with Reasoning and Knowledge

The Minnesota Natural Language Processing (NLP) Seminar is a venue for faculty, postdocs, students, and anyone else interested in theoretical, computational, and human-centric aspects of natural language processing to exchange ideas and foster collaboration. The talks are every other Friday from 12 p.m. - 1 p.m. during the Fall 2021 semester.

This week's speaker, Yohan Jo (Amazon Alexa AI), will be giving a talk titled "Natural Language Inference with Reasoning and Knowledge."

Abstract

Our society is overloaded with information, and people are getting more passive and dependent on information delivered by technologies. In order to build machine learning models that support human decision-making in a truthful way, we need a better understanding of how humans reason and how to incorporate human-like reasoning and knowledge into computational models to process information. In this talk, I'm going to focus on the problem of natural language inference and present my recent work from an argumentation perspective. I will be presenting approaches that incorporate logical mechanisms and knowledge graphs, followed by a practical application of counterevidence retrieval system.

Biography

Yohan Jo has worked on natural language processing for various aspects of dialogue in domains like argumentation, education, and clinical notes. His interests lie in modeling human reasoning and emotion, and his Ph.D. thesis focuses on computational analysis and generation of argumentation. Yohan recently received a Ph.D. degree from Carnegie Mellon University and joined Amazon for the Alexa AI – Natural Understanding team.

Rooted in STEM Information Session

Are you a current CSE undergraduate student interested in doing high school outreach to local high school 11th/12th graders? Please consider the brand new Rooted in STEM program!

Information Session for Potential Mentors
Friday, September 17
4 - 5 p.m.
Bruininks Hall 420B

About the Program
This program will focus on historically excluded and underserved students from Twin Cities high schools who are interested in STEM and will be capped at 25 participants. The ratio for mentors/mentees will likely be one undergraduate mentor to every three high school mentees.

Undergraduates with BIPOC, First Generation, and LGBTQIA+ identities are especially encouraged to apply!

Requirements for Mentors
Mentors will be asked to mentor one Saturday per month (October-April) for 4 hours each in addition to several pre-program trainings.

To support 25 high school participants, Rooted in STEM is now recruiting 8-9 CSE undergraduate students with a 2.5+ cumulative GPA to serve as mentors. Highly dedicated mentors will be essential program staff and must be able to fulfil to the following:

Minimum Commitment

  • Pass a background check required by the University’s Safety of Minors policy (For more information, please visit the policy website: policy.umn.edu/operations/minorsafety)
  • Attend required mentor training on EITHER Friday, October 8 from 8:00-10:00am OR Wednesday, October 13 from 11:30am-1:00pm.
  • Attend all program sessions from 9:30am-1:30pm on the following Saturdays: October 16, November 13, December 11, January 22, February 19, March 19, and April 30
  • Attend periodic mentor meetings


Perks

  • Mentors who fulfill their commitment will be eligible for a $500 scholarship at the end of the program
  • Catered lunch provided during Saturday program sessions


Questions? Email Dan Garrison, Assistant Director for Diversity and Inclusion for CSE Collegiate Life.

 

    Canceled: CS&E Colloquium

    The computer science colloquium for Monday, September 20 has been canceled.

    The colloquia series will resume Monday, September 27 at 11:15 a.m.

    Last day to cancel full semester classes and not receive a "W"

    The last day to cancel full semester classes and not receive a "W" is Monday, September 20. This is also the last day to receive a 75% tuition refund for canceling full semester classes.

    In addition, this is the last day to add classes without college approval and to change grade basis (A-F or S/N) for full semester classes.

    View the full academic schedule on One Stop.
     

    Fall 2021 College of Science and Engineering Virtual Career Fair

    Tuesday, September 21 and Wednesday, September 22, 2021
    Noon - 6 p.m. each day
    The fair will be held via Handshake

    View the day one list of companies recruiting and the day two list of companies recruiting now and begin signing up for time slots to speak individually with companies beginning September 14, 2021 at 8:00 a.m.

    Visit the Career Information for Students webpage for more information!

    For questions, contact the CSE Career Center at csecareer@umn.edu or by calling 612-624-4090.
     

    Last day to apply for fall undergraduate graduation

    The last day to apply for fall undergraduate graduation is Tuesday, September 21.

    View the full academic schedule on One Stop.
     

    Fall 2021 College of Science and Engineering Virtual Career Fair

    Tuesday, September 21 and Wednesday, September 22, 2021
    Noon - 6 p.m. each day
    The fair will be held via Handshake

    View the day one list of companies recruiting and the day two list of companies recruiting now and begin signing up for time slots to speak individually with companies beginning September 14, 2021 at 8:00 a.m.

    Visit the Career Information for Students webpage for more information!

    For questions, contact the CSE Career Center at csecareer@umn.edu or by calling 612-624-4090.
     

    UMN Machine Learning Seminar

    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 Mikhail Belkin (University of California San Diego).

    Abstract

    Coming soon

    Biography

    Coming soon

    CS&E Colloquium: At the deep end: addressing the underwater human-robot collaboration problem

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

    This week's speaker, Junaed Sattar (University of Minnesota), will be giving a talk titled "At the deep end: addressing the underwater human-robot collaboration problem."

    Abstract

    Autonomous underwater vehicles (AUV) have traditionally been used for standalone missions, with limited or no direct human involvement, in applications where it is infeasible for humans to closely collaborate with the robots (e.g., long-term oceanographic surveys, search-and-rescue, infrastructure inspection). However, in recent decades, the advent of smaller AUVs suitable for working closely with humans (termed co-AUVs) has enabled robots and humans to collaborate on many subsea tasks. The underwater domain, nonetheless, is unique in many ways and stands out with its numerous challenges -- in sensing, control, and human-robot interaction -- that can justifiably be considered extreme. Our research at the Interactive Robotics and Vision Lab at the University of Minnesota looks into numerous issues in robust underwater human-robot collaboration. Specifically, we investigate underwater bidirectional human-robot communication, underwater imagery enhancement, localization/mapping of underwater objects of interest using multimodal sensing, and biological and non-biological object tracking. We primarily investigate computational solutions to these problems, and use methods from robotics, machine vision, stochastic reasoning, and (deep) machine learning. This talk will present a brief overview of our research and present an in-depth discussion of some recent work in underwater human-robot interaction and imagery enhancement.

    Biography

    Junaed is an assistant professor at the Department of Computer Science and Engineering at the University of Minnesota and a MnDrive (Minnesota Discovery, Research, and Innovation Economy) faculty, and a member of the Minnesota Robotics Institute. He is the founding director of the Interactive Robotics and Vision Lab, where he and his students investigate problems in field robotics, robot vision, human-robot communication, assisted driving, and applied (deep) machine learning, and develop rugged robotic systems. His graduate degrees are from McGill University in Canada, and he has a BS in Engineering degree from the Bangladesh University of Engineering and Technology. Before coming to the UoM, he worked as a post-doctoral fellow at the University of British Columbia where his research focused on human-robot dialog and assistive wheelchair robots, and at Clarkson University in New York as an Assistant Professor. Find him at junaedsattar.info, and the IRV Lab at irvlab.cs.umn.edu, @irvlab on Twitter, and their YouTube page at https://www.youtube.com/channel/UCbzteddfNPrARE7i1C82NdQ.