November 2024

Welcome to the October edition of the Data Science Initiative newsletter!

In this issue, we celebrate the incredible success of the recent Women in AI and Data Science (WiADS) Conference, where over 1,000 attendees came together to connect, learn, and champion diversity in data science. You’ll also find highlights on innovative research, upcoming events, and achievements within our data science community. Whether you’re catching up on recent events or looking for ways to get involved, we’re excited to bring you the latest updates from the DSI!

Explore our website for more, and as always, thank you for your support in advancing data science at UMN.

Take a moment to complete this survey or share it with a friend:

Help us map our campus!

As a member of the University of Minnesota-Twin Cities, you know from first-hand experience that this is a big campus. How big? There are over 100 buildings across the East and West Bank. The fascinating thing is that we all differ in the parts of campus we are familiar with – some buildings we know really well while others are obscure to us. Help us uncover this diversity!

As part of this research project, we are looking to answer two questions: What part of campus do you know? What part of campus do your (UMN) friends know? Complete our survey, share it with your friends, and you will have a chance to win $50, $100, or $250.

Your responses will be kept confidential and used only for the purpose of this study.

Access the survey

Featured Article/Celebrating Success

WiADS 2025 - A success beyond measure!

On November 4th, 2024, the University of Minnesota’s Data Science Initiative hosted the Women in AI and Data Science (WiADS) Conference in collaboration with MinneAnalytics at the McNamara Alumni Center. This sold-out event brought together over 1,000 registrants, including over 550 in-person attendees, and showcased the work of women, non-binary, and gender-diverse voices in data science. Attendees represented nearly 300 units from about 230 distinct business and academic institutions, highlighting the wide-ranging interest and support for advancing gender representation in this growing field.

The event featured distinguished speakers from both academia and industry, including participants from the University of Minnesota and major Minnesota-based organizations like Target, Optum, CHS, and U.S. Bank. The conference embodied a spirit of connection, support, and inspiration, enabling participants to make meaningful connections and fostering a supportive community for data science professionals at all career stages.

In her welcome address, Provost Rachel Croson expressed pride in the University’s commitment to promoting diversity in data science and spoke to the importance of interdisciplinary collaboration:

“We at the University of Minnesota are very proud of the work that the DSI is doing in its role as the ‘front door’ to data science and AI at the University. Interdisciplinary collaboration is a priority at our institution, and the DSI is a shining example of that commitment.”

Provost Croson also highlighted the importance of mentorship and peer relationships for women in underrepresented fields:

“Women are underrepresented in data science, just as they are in my field, economics. In my own professional work, I created, funded, and implemented a mentoring program to help female junior faculty succeed. What I found is that the most impactful aspect of that program were the peer-to-peer relationships that developed, were sustained, and eventually proved to be pivotal to the participants’ success.”

She encouraged attendees to embrace the spirit of collaboration:

“Check in with each other regularly, celebrate your successes, and help each other through your struggles. This is not a competition. We all do better when we all do better.”

Feedback from attendees highlighted the unique, empowering nature of the event. One attendee shared:

“As a woman, it was AMAZING to see only women speakers. They were confident and knowledgeable. It was so inspirational! Thank you for putting on this wonderful event. I enjoyed attending virtually but hope to attend in person next time.”

Another noted the importance of having such a conference in the local community:

“I love that this conference exists. I think it is very important that this event continues to exist in our community! Thanks for putting it on.”

Attendees also appreciated the thoughtful touches, from seasonal refreshments to handmade bracelets:

“I loved the apple cider and the bracelets. Nice touch. I also love that the more accomplished women were so willing to talk with anyone.”

Our dedicated volunteers, who helped make the day a success, shared their own highlights:

“The opportunity to hear world-class presentations by industry leaders.”

“The ability to meet with and connect with colleagues in the field.”

The DSI extends a heartfelt thank you to our volunteers, speakers, attendees, and sponsors for making WiADS 2024 a success and for inspiring the future of data science.

Missed the event or want to revisit some of the sessions?
Learn more about access the event recordings and relive the WiADS experience.

We look forward to continuing this tradition and welcoming even more attendees to the WiADS community in years to come!

New dataset to advance health research benefiting underrepresented communities

UMN researchers now have expanded access to health data from communities that have historically been underrepresented in research thanks to a new research data warehouse from CTSI and the Community-University Health Care Center (CUHCC).

Learn more about the new dataset to advance health research

Initiative Updates

Congratulations to Dr. Genevieve Melton-Meaux on Her Election to the National Academy of Medicine

We are thrilled to announce that Dr. Genevieve Melton-Meaux, Professor in the Division of Colon & Rectal Surgery and Co-Chair of the Data Science Initiative, has been elected to the National Academy of Medicine (NAM). This prestigious honor recognizes her exceptional achievements and commitment to advancing healthcare.

NAM cited Dr. Melton-Meaux for her groundbreaking work in integrating AI with healthcare, bridging surgery and informatics, and developing learning health systems. Her research has transformed clinical practice and policy, from optimizing electronic health records to detecting social and behavioral health determinants in clinical data.

Congratulations to Dr. Melton-Meaux for this outstanding achievement and her contributions to healthcare and data science!

Generative AI Workshop Sparks Key Conversations on "AI and Elections: A Conversation With Secretary Steve Simon of Minnesota"

At the Data Science Initiative’s Spring Research Workshop on Generative AI, Secretary Steve Simon and other experts discussed pivotal themes in AI, including the use of AI within elections. Following this event, Secretary Simon collaborated with researchers, contributing to a recent Harvard Data Science Review article, "AI and Elections: A Conversation With Secretary Steve Simon of Minnesota" This article builds on insights sparked at our workshop and highlights important considerations for advancing reliable AI applications.

Research Spotlight - Seed Grant Awardee

Title: CancerLLM: Development of a Cancer-domain Large Language Model to Extract diagnostic information

PI(s): Rui Zhang, Steve Johnson, Anne Blaes

DSI Track: Digital Health

MnDRIVE Area(s): Cancer Clinical Trials

Summary Paragraph:

Extracting cancer tumor characteristics and other relevant data from these reports are vital for supporting clinical research in cancer domains and for other downstream use cases such as (1) the secondary use of observational EHR data to understand treatment effectiveness and safety in real-world patient populations and (2) identifying eligible cancer patients for clinical trial matching. Natural language processing (NLP) is key to large-scale extraction of nuanced data within clinical texts. The objective of this project is to develop a privacy preserving cancer domain specific large language model (LLM) capable of extracting diagnostic information for breast cancer. The current project extends our prior work (CancerBERT) to develop a domain-specific LLM (CancerLLM) to extract diagnosis information from breast cancer patients. CancerLLM will enable researchers to process notes in a privacy-preserving manner and not release healthcare data to external services. The ability to extract these concepts more accurately will improve the use of unstructured observational data in cancer research, allow patients to be better matched to clinical trials and ultimately improve patient outcomes.

View 2023 Seed Grant Awardees

Events

AI Makerspace Hours

When: Every other Friday starting September 13, 2024
Where: Walter 575

The DSI and MSI invite all students, staff, and faculty to our AI Makerspace Hours, a unique event where you can dive into AI on our state of the art HPC with hands-on experience. With the support of our expert MSI staff, you'll learn everything from basic coding to training advanced generative AI models. Enjoy access to dedicated HPC nodes for practical learning and a set of comprehensive tutorials.

RSVPs are not required but highly recommended; otherwise, attendees will need to spend a few minutes creating an account on the HPC. Please bring your own laptop (it doesn't need to be a high-performance one). There will be one or two laptops available to loan out if needed.

Don’t miss out on this opportunity to learn, explore, and innovate with us! RSVP Now!

Save the Date: DSI Seed Grant Showcase

When: December 3rd, 2024
Where: Coffman Union’s President’s Room

Join us to celebrate the impactful work of the DSI seed grant recipients. This event fosters community, encourages collaboration, and sparks ideas for future research development. Light refreshments will be provided—don’t miss this chance to connect with fellow data science enthusiasts and explore cutting-edge research.

More details to come!

Data Discovery Across Departments

Events in other departments/initiatives/institutions - (External (Non-DSI Events)

AI Community of Practice Share Time (Opens Google Docs)

When: Wednesday, November 13⋅10:00 – 10:50am
Where: Zoom

Agenda:

Updates and Events Coming Up
OIT for systemwide AI related infrastructure/tooling/security updates
Speaker: Dr. Richard Landers: “Exploring academic integrity, a new age of assessment, and personal growth through Generative AI”

Richard Landers is a professor of industrial-organizational psychology on the Twin Cities campus. His research primarily focuses on exploring the design and value of new technology in facilitating employee hiring, training, and development. In this talk, he'll cover the last two years of his work in AI, focusing on

the mechanisms for and effectiveness of cheating with generative AI,
the use of generative AI for developing meaningful assessment materials, and
the use of generative AI agents for supporting extracurricular personal development.

Healthcare, Data Science & AI Working Group Kickoff Workshop

Date: Friday, November 15 from 12:00-3:30 PM
Format: In-person on the East Bank & Zoom

Lunch: Provided for in-person attendees

The workshop will help us:

Connect researchers across disciplines at the intersection of Healthcare, DS, and AI related fields
Identify shared interests and challenges
Plan future topic-focused meetings

The session will be recorded and materials shared within the group, with opt-out options available for presenters. To receive an invitation, please email [email protected]. A follow-up Google Calendar invitation will confirm the specific event location and Zoom details.

Inaugural AI Use Faculty Café

When: November 15, 2024 9 AM - 10 AM
Where: 2-122 Molecular and Cellular Biology, Twin Cities Campus - Zoom link

Presentations:

Kristin Shingler & Karin Quick: GenAI Ethics: Decision-Making Activities to Build GenAI Literacy

Tim Doherty: A Pragmatic Approach to Using Generative AI in Chemistry Lab Report Writing

Who Should Attend? Anyone interested in leveraging AI in teaching. Feel free to share this invitation!
RSVP? Not required, but appreciated for refreshment planning. RSVP link
Interested in Presenting?: We encourage faculty to share their AI use cases. If you’d like to present at a future event, please fill out this form, and we will contact you.

Minnesota Demography & Aging Seminar Series

When: Mondays from 12:15-1:15 PM CT
Where: 50 Willey Hall in the Seminar Room or via Zoom

Snacks and beverages will be served.

For the most up-to-date information, view the full schedule on either the LLC website or the MPC website.

Fall 2024 Schedule

NOVEMBER 11
Effect of System Affiliation on Hospital Choice: Evidence from Rural Markets

Caitlin Carroll - Assistant Professor, Division of Health Policy & Management, University of Minnesota School of Public Health
DECEMBER 2
Granular Income Inequality and Mobility using IDDA: Exploring Patterns across Race and Ethnicity

Abigail Wozniak - Vice President at the Federal Reserve Bank of Minneapolis, Director of the Opportunity & Inclusive Growth Institute

Donuts and Data Hackathon

When: Friday, November 22nd 8 am - 1 pm
Where: 530 Bruininks hall

The goal is to connect students, staff and faculty of all experience levels with experts in data visualization tools (like Tableau, R-Shiny, Power BI) to help prepare for the Data Viz Championship - plus free donuts and coffee! Please sign-up here (Opens Google forms).

Learning Resources

IRSA's Statistical Consulting Center is now accepting applications. Our statistical counseling support is tailored to your needs, whether you're inside or outside of the University. Our services are available for those seeking a long-term collaboration or a brief counseling session. We’re here to help elevate your research with data and expert statistical counseling.

Discover more: IRSA Statistical Consulting Center

Course: Why Data Science?

Data Informs Decision-Making and Drives Innovation Data science is the study of data to extract meaningful insights.

Data Science is a multidisciplinary approach that combines principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering to analyze large amounts of information. GEMS Learning courses are modular data science education tailored to food, agriculture, and natural resource applications for working professionals and students. Across the curriculum, instructors have built their course content from their own work executing large-scale data science projects to solve pressing agricultural problems.

Fall 2024 Courses

NEW High Performance Computing for Agriculture (beta course for UMN affiliates only)

If you are a researcher that works in the Agri-food domain (e.g., breeder, molecular biologist, food scientist, socioeconomist), you know a little bit of programming (e.g., in R and/or Python), but you feel a little limited (e.g., some of your calculations run for days on your laptop), then you could benefit from this course. We wish to show you how to step up to the next level, improve your coding efficiency, and make use of High Performance Computing (HPC) and Cloud resources readily available to you.

Breaking the Compute Barrier, Upskilling Agri-Food Researchers to Utilize HPC Resources, September 16 - November 18

Computing Basics for the Agri-food Sector (self paced)

Are you a field or bench scientist and always wanted to feel more comfortable with your computing skills? These self-paced online courses are designed for those who have never used the command line, but realize that the responsibilities they have or will soon take on require them to automate tasks. Learn basic UNIX command-line skills, enable participants to work remotely on more powerful machines, create and run scripts to automate complex workflows, and synchronize your scripts with the larger community with Github.

Analyzing Spatial Agriculture data in R

Is accounting for spatial dependency in your analyses critical to your work?

Or do you need to create a continuous surface of data (i.e., raster) based on a sample point date taken at selected locations?

Introduction to spatial data analysis in R, November 6, 13 and 20th

Explicitly Accounting for Location in Agriculture in Python (self paced)

Learn how to work with spatial data in Python, starting from importing different spatial datasets and creating simple maps, to conducting basic geocomputation on vector and raster data.

Funding Opportunities and Deadline

If you're interested in exploring these or other data science opportunities, whether it's finding the right team, preparing your submission, or partnering with industry on federal and state funding initiatives, please reach out—we’re here to help!

Quad AI-ENGAGE - AI-ENGAGE, NSF, JST, ICAR and CSIRO invite joint multilateral proposals from researchers in at least three of the Quad countries. Proposals involving researchers from all four countries are encouraged and will be prioritized for funding. Proposers from the Quad countries collaborate to write a single proposal that will undergo a single review process coordinated by NSF, the Coordinating Agency. Questions regarding details of AI-ENGAGE submission to partner agencies should be addressed to: Yuta Kobayashi, JST, Department of Moonshot R&D Program, [email protected]
NEH Digital Humanities Advancement Grants - The Digital Humanities Advancement Grants program (DHAG) supports work that is innovative, experimental, and contributes to the critical infrastructure that underpins scholarly research, teaching, and public programming in the humanities. Optional draft due: Nov. 13, 2024; deadline: Jan. 9, 2025
NIH AHRQ - Examining the Impact of AI on Healthcare Safety - The purpose of this NOFO is to invite grant applications that support healthcare safety by determining (1) whether and how certain breakthrough uses of Artificial Intelligence (AI) systems can affect patient safety; and (2) how AI systems can be safely implemented and used. AI has the potential to improve the safety, effectiveness, efficiency, accessibility, and affordability of healthcare. However, as with most technologies, this potential must be balanced by identifying and mitigating potential risks for patient harm and user burden. Deadline: Jan. 25, 2024
NSF Emerging Mathematics in Biology - The Emerging Mathematics in Biology (eMB) program seeks to stimulate the development of innovative mathematical theories, techniques, and approaches to investigate challenging questions of great interest to biologists and public health policymakers. It supports the development of the mathematical foundation of Artificial Intelligence/Deep Learning/Machine Learning (AI/DL/ML) enabling explainable AI or mechanistic insight. The program emphasizes the uses of mathematical methodologies to advance our understanding of complex, dynamic, and heterogenous biological systems at all scales (molecular, cellular, organismal, population, ecosystems, evolutionary, etc.). Deadline - March 3, 2025
NSF Ethical and Responsible Research (ER2) - The ER2 program supports projects that focus on what constitutes or promotes responsible and ethical research in science, technology, engineering, and mathematics (STEM) fields. The ER2 program promotes the development, improvement, and dissemination of responsible and ethical research practices and aims to build on organizational cultures that value and reward such practices. Deadline - January 23, 2025
DOD FY25 Minerva Research Initiative University Research Program - Minerva’s University Research program aims to support innovative basic research projects that contribute to the advancement of social science and provides new methods and understandings on social and behavioral questions of security and defense-related interest. Minerva aims to improve DoD's basic understanding of the social, cultural, behavioral, and political forces that shape regions of the world of strategic importance to the U.S. The research program seeks to: Leverage and focus the resources of the Nation's top universities; Define and develop foundational knowledge about sources of present and future conflict with an eye toward better understanding of the political trajectories of key regions of the world; and Improve the ability of DoD to develop cutting-edge social science research and foreign area and interdisciplinary studies that is developed and vetted by the best scholars in these fields. Deadline - Feb. 28, 2025

For students:

The NSF PACK fellowship: The PACK fellowship is a graduate student opportunity to conduct research at the University of Kiel, Germany for 3 weeks. Applicants from any science or engineering discipline are encouraged to apply now!

Open Positions: Assistantships and Internships

Honeywell Internships - Honeywell is looking for 8 Artificial Intelligence interns in Honeywell Aerospace (US Person Required) and 22 interns will be a part of other Honeywell businesses (Non US Persons Possible)
Quantinuum Internships - Quantinuum is looking for summer interns in Health Safety and Environment, Manufacturing Engineering, Optics Engineering, Metasurface Design (PhD), Trapped-ion Quantum Computing Theory (PhD), PMO Project Engineering, and Technical Solutions Consulting.
IT Research and Security Project Manager (Opens Google Docs)

Social Media/Website Links

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