Data Science Updates is the University of Wisconsin-Madison's resource for news, training, events, and professional opportunities in data science, brought to you by the Data Science Institute, powered by American Family Insurance, and the Data Science Hub.
February 8, 2024
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“Geology to Stained Glass AI Morph” by Ben Rush
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Data in Art opens at the Research Bazaar
Ben Rush creates AI-generated images that morph scientific domains like geology with art styles such as stained glass. Excel spreadsheets inspire Dian Yao’s watercolor art. You can experience their creations, plus ceramics by Erwin Lares and an LED-adorned Christmas tree by Timothy Black, at Data in Art. This exhibit opened yesterday at the Discovery Building as part of the the Research Bazaar.
The theme of this year’s Research Bazaar is Data in Action. Data in Art demonstrates how artists and data scientists alike translate information into visual and aesthetic forms that create meaning from complexity and influence both research and society.
Data in Art will be open for public viewing in Hub Central and the Image Lab through March. We encourage you to stop by and check it out in room 1160! The participating artists include:
- Timothy Black, University of Chicago
- Erwin Lares, DoIT Research Cyberinfrastructure
- Ben Rush, Department of Radiology, SMPH
- Dian Yao, SMPH Fiscal Affairs Transaction Team
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Resources are available to help you apply to the American Family Funding Initiative
Thinking about submitting a proposal to the American Family Funding Initiative? To help applicants create competitive applications, this program offers resources including a Town Hall meeting this Friday, February 9, office hours with American Family Insurance, and more. We encourage you to take advantage of these opportunities. Details are available here.
The American Family Funding Initiative is an internal funding competition offering up to $150K to stimulate and support cutting-edge research in the rapidly growing field of data science. American Family Insurance has partnered with UW–Madison through the Data Science Institute to provide this research funding opportunity. UW–Madison faculty and staff with permanent PI status are eligible to apply. Proposals are due March 1. Learn more here.
The UW–Madison Data Science Institute, powered by American Family Insurance, aims to bring the power of data science to every discipline. Visit the DSI website to learn how DSI can support your data science needs.
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At the second annual American Family Funding Initiative Networking Meeting, UW–Madison researchers shared their work with American Family Insurance business leaders.
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Chats with AI shift attitudes on climate change, Black Lives Matter
How well do large language models perform in complex conversations with people? Data Science Institute Affiliates Kaiping Chen and Sharon Li recruited thousands of participants to have conversations about climate change and Black Lives Matter with a popular AI chatbot. They found that the participants who had the lowest levels of agreement with these topics had the least satisfying interactions with the chatbot, but they left the conversations more supportive of the scientific consensus on these issues..
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Intro to Text Analysis
March 26-28, 9:00 a.m. - 12:00 p.m., Online. Join this upcoming Carpentries workshop for a practical Introduction to Text Analysis, designed for those with Python experience. The workshop covers Natural Language Processing (NLP) basics, API usage, data preparation, document/word embeddings, topic modeling, Word2Vec, Transformer models using Hugging Face, and ethical considerations. Students and researchers working in the digital humanities are especially encouraged to attend! Register for the text analysis workshop.
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Workshop Series: Methods for Biological Data
February through May, Dr. Claudia Solis-Lemus and Dr. Emile Gluck-Thaler from Plant Pathology are hosting the workshop series "Methods for Biological Data" for Spring 2024. This interactive workshop will help students and postdocs engage with new methods for analyzing their data. All students and postdocs are welcome!
The workshops will take place on the first Wednesday of the next four months from 2-3:30pm in 584 Ruseell Labs (Feb 7, March 6th, April 3, May 1st). Local and virtual speakers will be invited to demo new statistical and bioinformatic methods with opportunities for students/postdocs to try out the methods in real-time on their data.
Their first speaker today (February 7) will be Kris Sankaran from UW's Stats Department who will present "Simulation in Omics".
Description: Simulation is the Swiss Army knife of omics data science: by using historical data it can help us imagine hypothetical experimental results, design well-powered studies, benchmark new methods, and perform statistical inference. We will reflect on these applications, tinker with some real-world microbiome examples, and explore the statistical ideas the lie behind modern omics simulators. In the code demos, we will highlight strategies for writing modular code and creating clear visualizations. Finally, we will speculate on the form of future analysis workflows, especially the role of interactive exploration and problem solving.
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Workshop Series: Python and R Programming Languages for Data Analysis
February and March, Learn programming skills for computational research during the R workshop series and the Python workshop series. Attend any or all of the sessions. Brought to you as a part of the UW Libraries Graduate Support workshop series. Open to all UW-Madison students, faculty, and staff. Location: Instruction online via Zoom with in-person help at satellite locations for some workshops.
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Next Generation Data Analysis Workshops
March and April, The Bioinformatics Resource Core (BRC) at the UW Biotechnology Center ( UWBC) is offering heavily hands-on workshops on Next-Generation Sequencing (NGS) Data Analysis skills:
- Access and analyze data with bash command line
- SNP and RNA-Seq analysis examples with open-source software on a Linuxplatform
These day-long workshops are in-person sessions and do have a fee associated with them. Read workshops descriptions, access registration links, and view the calendar at the Bioinformatics website.
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Have questions about anything data science-related? Come see the Data Science Hub facilitators at Coding Meetup on Tuesdays and Thursdays from 2:30-4:30 p.m. CT. To join Coding Meetup, join data-science-hubgroup.slack.com.
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ML4MI Seminar Series: AI in Precision Oncology
February 12, 10:00 a.m., The Machine Learning for Medical Imaging Seminar Series is hosting a talk from Dr. Jakob Kather, Professor of Medicine and Computer Science from the Technical University of Dresden titled "AI in Precision Oncology." Read the abstract below and attend online with this Zoom link.
Abstract: Histopathology images are available for every single patient with a solid tumor. These images contain a large amount of information. In particular, they reflect underlying genetic changes which are present in the tumor cells. Recent work has shown that deep learning-based image analysis can predict genetic alterations just from routine pathology slides. This talk will summarize the state of the art, show the limitations of this method and discuss how spatial intratumor heterogeneity can be evaluated from the tumor phenotype. Ultimately, these recent advances set the stage for multimodal artificial intelligence models which simultaneously use pathology slides and genomics as an input, yielding biomarkers for treatment response to immunotherapy and targeted therapy.
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Geospatial Data Science Speaker Series: Scalable Spatial Data Science for Social Scientists
February 13, 12:00 p.m. - 1:00 p.m., The Geospatial Data Science Lab @ UW-Madison and the Data Science Institute are hosting a seminar by Dr. Amr Magdy, Assistant Professor of Computer Science and Engineering and co-founding faculty member of the Center for Geospatial Sciences at UC Riverside (NSF CAREER award in 2023) on scalable spatial data science for social scientists at Science Hall 140, 550 N Park St, Madison. Learn more at the seminar posting.
Abstract: The proliferation of spatial data from prevalent technologies has resulted in large datasets ripe for extracting insightful knowledge that can drive many applications. Spatial statistical analysis emerges as a critical tool enabling social scientists to analyze large spatial data, while maintaining statistical significance in their results. This seminar talk will introduce innovative query processing techniques that amplify both query expressiveness and scalability.
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Data Science for Social Good
Why Apply?
- Real-world projects
- Cutting-edge data science
- Robust support structure
- Motivated team members
- Mentoring relationships
- Seattle summer (it’s amazing, FYI)
Applications are now open for our 2024 program. Accepting applications for:
- Student Fellows: Student Fellows Application - Open until 11:59 PST, February 12th
- Project Proposals: Community Project Proposal Submissions - Open until 11:59 PST, February 20th
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ML+X Forum: Navigating Gravitational Waves with AI Insights
February 13, 12:00 p.m. - 1:00 p.m., ML+X is looking forward to kicking off the spring ML+X forum (in-person at the Discovery Building, and online). The first forum of the year will start February’s forum with announcements on new initiatives in the community and a small group discussion activity to get everyone acquainted. In the second half of the hour, Bella Finkel will speak; Bella is a graduate student who is seeking input on AI explainability methods to better understand convolutional neural networks trained on spectrogram data (representing gravitational waves). Register using this Google form to guarantee a lunch ticket.
Bell Finkel's "Classifying gravitational wave modes from core-collapse supernovae" Abstract: Core-collapse supernovae are promising gravitational wave sources that play an important role in the evolution of galaxies and the formation of heavy elements. I will describe recently developed software for quickly generating large and diverse sets of synthetic gravitational wave signals and its use in an ongoing project that employs a convolutional neural network to classify gravitational wave signals from core-collapse supernovae. Our approach offers novel opportunities for controlling features of the input waveforms and the noise level of the dataset. At this ML+X forum, I’ll solicit feedback on strategies for interpreting the model to determine salient features in the input spectrograms and optimizing a model that works with inherently stochastic data.
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ML+Coffee
February 14, 9:00 a.m. - 11:00 a.m., Hosted by the ML+X community in the Hub Central lobby at the Discovery Building (330 N Orchard St), the monthly ML+Coffee social brings together machine learning (ML) practitioners across campus so that they can connect with one another, discuss and work on ML projects, and enjoy some caffeinated refreshments ☕. Attendees are encouraged to bring their laptops and/or any questions about ML. Learn more about ML+Coffee at the ML+X website. Register for the event (so ML+X can order enough catering) with this form.
New this semester! Via the event registration form, participants can optionally sign up to either (1) discuss a problem that they would like to apply ML to or (2) give a casual and low-stakes demo of an ML-related tool or concept. View the ongoing queue of problems and demos we will discuss. Please fill out the registration form if you plan to attend!
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EVIL in Spring 2024
February 16, 10:00 a.m. - 11:00 a.m., The Ethics, Values, Information, and Law (EVIL) reading group pursues scholarship in the intersections of ethics, law, and data and information technologies. The EVIL Reading group meets every three weeks (roughly), Fridays, online, and is hosted in collaboration with the iSchool and ML+X. This meeting discusses " Large image datasets: A pyrrhic win for computer vision?" and Tiny Image's response with additional supplemental reading. Learn more about the community and how to attend the meeting at the EVIL website.
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The Carpentries is seeking new members to bring additional diversity and expertise into its instructional community. Among other benefits, members have opportunities to advance their technical and teaching skills by attending computational workshops and participating in an optional instructor training program. Join the google group if interested in learning more!
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PROFESSIONAL
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Research Specialist
Apply by February 12th at 11:55 p.m. CT. The Wisconsin Center for Education Research in the School of Education is looking for a research specialist that will serve as a project manager and will organize the day-to-day operations of the project under the supervision of a Principal Investigator (PI). Read the job summary, responsibilities, and qualifications, then apply, all at the job posting.
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STUDENT
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Pegus-III Experiment Undergraduate Student Position
The Pegasus-III Experiment is seeking undergraduate students to join its team. Position pays $15/hour. If selected for the position, there may be an opportunity to attend a ML/AI for Fusion Energy Summer School at William & Mary in Virginia during June 3-14, 2024. If interested, please contact sjdiem@wisc.edu ASAP.
Job Duties:
- Learn about data processing and experimental operations in university-based fusion experiments
- Work with team members to develop python-based data processing and analysis tools for Pegasus-III
- Work with team members to curate datasets to use with ML/AI tools for fusion energy
Pegasus-III is a new fusion energy and plasma science experiment at UWMadison that creates strong magnetic bottles to confine hot plasma, the fourth state of matter, to develop a new clean energy source.
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DATA VISUALIZATION OF THE WEEK
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Reposted from the Data Science Community Newsletter, an Academic Data Science Alliance project.
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The Academic Data Science Alliance (ADSA) is a network of academic data science practitioners, educators, and leaders, and academic-adjacent colleagues, who thoughtfully integrate data science best practices in higher education. UW-Madison is a founding member of ADSA.
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Data Science Updates is a collaborative effort of the Data Science Institute and Data Science Hub.
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