June Newsletter

June Announcement

Welcome to the vibrant month of June, data enthusiasts! As we step into this new month, we're excited to highlight the success of our Spring Research Workshop on Generative AI, which took place at the end of May, from the 22nd to the 24th, at the Humphrey Conference Center. The workshop delivered insightful discussions on the innovative role of Generative AI in shaping healthcare, public policy, and beyond.

As the month unfolds, there will be numerous chances for you to connect with the data science community, explore funding opportunities, and contribute to cutting-edge research. Whether you're seeking to deepen your knowledge, network with fellow enthusiasts, or showcase your latest projects, June offers a wealth of avenues to engage and grow in the field of data science.

So, stay tuned as we guide you through the month, highlighting funding opportunities, calls for papers, and other events that will keep you at the forefront of the data science landscape. Let's make the most of June's offerings and continue our journey of driving impactful advancements in data science together!

Community Corner Spotlight

Benjamin Toff 

Intrigued to learn more? Head to the Community Corner page on our website to delve deeper into Benjamin's answers to our community corner questions.

The Latest Community Corner Spotlight

Initiative Updates

The UMN DSI's 2024 Spring Workshop has successfully concluded! 

The UMN DSI's 2024 Spring Workshop has successfully concluded, and we are deeply grateful for its success and to everyone who participated. We hope attendees found the event both insightful and engaging, and we sincerely appreciate your contributions. The event fostered rich discussions and collaboration, inspiring future research and innovation in generative AI.

We are excited to announce that this workshop will be an annual event with different topics, and we hope it continues to foster conversation within our data science community. We look forward to welcoming you to future DSI events!

Highlights from the Event:

Day 1 Highlights: GenAI Foundations and UMN Capabilities (May 22)

The workshop began with a welcome from Dr. Shashank Priya, followed by Dr. Xiao-Li Meng's keynote on the challenges of generative AI. Dr. Jisu Huh discussed AI's impact on advertising, and Dr. Steven Wu presented a novel approach to reinforcement learning. Afternoon sessions included talks by Dr. Jie Ding on scalable AI, Dr. Jonathan Bentz on computing evolution, and Dr. Ben Lynch on AI support at the Minnesota Supercomputing Institute. The day concluded with Data Set Lightning Talks and a reception.

Day 2 Highlights: GenAI and Public Policy and Societal Impacts (May 23)

Nancy Sims opened the day, followed by Dr. Baobao Zhang on AI governance and Michael Corey on community co-creation in Mapping Prejudice. David Maeda and Secretary Steve Simon discussed AI's impact on elections. The afternoon featured Eran Kahana on AI data quality and Dr. Claire Segijn on ethical issues in AI surveillance.

Day 3 Highlights: GenAI and Health Data (May 24)

Dr. Lucila Ohno-Machado's keynote on AI in medicine opened the final day, followed by Dr. Dave Little, Dr. Louis Kazaglis, and Dr. Andrea Noel from EPIC on AI in electronic health records. Dr. Shauna Overgaard on closing the AI translation gap in medicine, Mark Gardner on FDA regulations, Dr. Serguei Pakhomov, Dr. Hari Trivedi, and Dr. Scott Friedman presented on various health data topics. The workshop concluded with a thank-you from Dr. Galin Jones.

If you would like access to Keynote Recordings:

Access recordings of the keynote talks on the DSI MediaSpace Kaltura.

Access speaker presentations within the DSI shared file. 

This event was highly successful, and we are immensely thankful to the presenters for sharing their expertise on generative AI, as well as to all attendees who asked insightful questions. The support from our participants and members is crucial to fostering the vibrant data science community we are building together.

We look forward to welcoming our subscribers to future DSI events!

Reminder: DSI’s New Website is now live!

Check out our new website: Find details about all of the data science initiatives, centers, and educational programs on our UMN Data Science Directory! Look for exciting Data Science events from around campus on our new events page! Request assistance in anything from help with creating an event, to writing a grant, to getting in touch with the right expert in the new incarnation of the DASH email via our request assistance form! And learn more about our leaders and core members and how to become one!

We need your help!

The DSI’s internal and external partnerships working group would like to know more about your current industry engagement and what you need most from a potential industry partner! Please fill out the survey and have your voice heard!

K-12 Opportunity for Faculty

Interested in co-teaching GCC 3026? This unique course mentors undergraduates in science projects at Murray and offers a weekend at Wolf Ridge. Learn more. Reach out to Cheryl Olman ([email protected]) if you are interested or for more details!

Please note that while this position entails overload teaching, potential negotiation for workload credit is possible.

Research Spotlight - Seed Grant Awardee

Multi-task Deep Learning Models for Neurodegenerative Disease Risk Prediction

PI(s): Chad Myers

DSI Track: Digital Health

MnDRIVE Area(s): Brain Conditions
 

A primary goal of genetic studies on complex diseases is to build predictive models to assess an individual's disease risk based on their genome. Current approaches primarily rely on collections of individual genetic variants identified through traditional GWAS analysis and provide limited predictive accuracy. However, genes function in the context of a complex biological system, engaging in interactions with other genes to fulfill diverse functions. Thus, accurate disease risk prediction models will need to incorporate genetic interaction effects. We recently developed a method, called BridGE, that provides a new, computational approach for discovering genetic interactions from GWAS data by incorporating knowledge of biological pathways. BridGE has been applied successfully to identify interactions for six diseases to date but has not yet been incorporated into individual disease risk prediction models. In the proposed work, we aim to build more accurate disease risk prediction models for neurodegenerative diseases (Parkinsons, Alzheimer’s disease and ALS). We will leverage a state-of-the-art graph neural network deep learning approach that is specifically designed to capture interaction effects and enables joint learning of multiple human phenotypes simultaneously. Successful completion of the project will produce more accurate individual risk prediction models and new insights into the genetic basis of neurodegenerative disease.

Events

Join us for insightful seminars that delve into the world of data and its foundational principles as well as its wide-ranging applications in data science.

Events in Data Discovery Across Departments  

28th Annual IEEE High Performance Extreme Computing Virtual Conference

September 23rd to 27th, 2024

Venue: Virtual

The 28th Annual IEEE High Performance Extreme Computing Virtual Conference is happening from September 23rd to 27th, 2024. They are seeking submissions showcasing advancements in High-Performance Computing, AI/Machine Learning, and more. 

Submission deadline: July 7, 2024. Don't miss this chance to contribute to cutting-edge computing technology! 

For details, visit the conference website.

Learn more about IEEE

Learning Resources

Request:

Are you interested in or already looking into a UMN specific instance of a Large Language Model (LLM) like ChatGPT for productivity or research?

Email the DSI to join our working group! [email protected]

HPC for Ag: Breaking the Compute Barrier, Upskilling Agri-Food Researchers to Utilize HPC Resources

When: Mondays 10:30 - Noon from September 16 - November 18

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.

TOPICS COVERED: The upcoming event will delve into several key topics, including "HPC for Ag: Breaking the Compute Barrier" and "Upskilling Agri-Food Researchers to Utilize HPC Resources." Additionally, participants will gain insights into "Intro to Cloud Computing," "HPC Basics," "Expanding HPC Skills," "Computer Science for the Agri-Food researcher," and "HPC and Cloud Concepts." Moreover, discussions will encompass "Computer Hardware and Resources" pertinent to this event, fostering a comprehensive understanding of high-performance computing and its application in agricultural research. 

Register now for the HPC for Ag Course 

Funding Opportunities and Deadlines

If you are interested in any of these or other data science related opportunities and need help organizing your submission or finding the right team please contact us, we’re here to help!

Upcoming Funding

• NSF MFAI: Mathematical Foundations in AI Deeper mathematical understanding is essential to ensuring that AI can be harnessed to meet the future needs of society and enable broad scientific discovery, while forestalling the unintended consequences of a disruptive technology. The overall goal is to establish innovative and principled design and analysis approaches for AI technology using creative yet theoretically grounded mathematical and statistical frameworks, yielding explainable and interpretable models that can enable sustainable, socially responsible, and trustworthy AI. Full proposal due: Oct. 10th, 2024
• NSF Campus Cyberinfrastructure: The Campus Cyberinfrastructure (CC*) program invests in coordinated campus-level cyberinfrastructure improvements, innovation, integration, and engineering for science applications and distributed research projects. Projects that help overcome disparities in cyber-connectivity associated with geographic location, and thereby advance the geography of innovation and enable populations based in these locales to become more nationally competitive in science, technology, engineering, and mathematics (STEM) research and education are particularly encouraged. Deadline: Oct. 15th, 2024
• NEH Digital Humanities: The Digital Humanities Advancement Grants program (DHAG) supports innovative, experimental, and/or computationally challenging digital projects, leading to work that can scale to enhance scholarly research, teaching, and public programming in the humanities. Deadline: June 13th, 2024

Upcoming Deadlines

• NSF: Developmental Science research. Due July 30th, 2024 (and also Jan. 30th, 2025)
• NEH: The Dangers and Opportunities of Technology: Perspectives from the Humanities. Due Sept. 12, 2024

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!