Transforming Your Research with Generative AI

Tutorial Series

Generative AI is revolutionizing the landscape of research by enabling unprecedented levels of automation and innovation, and facilitating major breakthroughs across all research fields. To leverage this, MIDAS and the College of Literature, Science, and the Arts are co-hosting a series of tutorials on generative AI during the Winter ’24 semester.

If you are a U-M researcher looking to learn more about when, why, and how to integrate generative AI tools into your research, join us at one of our upcoming sessions. We cover topics ranging from administrative tasks, literature review and synthesis, data analysis, and writing and presentations.

No prior experience with generative AI tools is required. Participants will need to supply their own laptop for each session.

Questions? Please reach out to midas-research@umich.edu

Series co-organizer

Upcoming Sessions

Location

All sessions will be held in-person. We are not able to offer live-streaming for this series. Unless otherwise noted, all sessions will take place on the 10th Floor of Weiser Hall (500 Church St., Ann Arbor MI 48109).

Recordings and materials from past sessions will be posted to this page when available.

Visualizing and presenting data

Wednesday, May 29, 2024; 10:00 AM-12:00 PM

Location: In-person, 10th Floor of Weiser Hall

(500 Church St., Ann Arbor MI 48109).

About: This session on using generative AI for data visualization is tailored for participants with a background in R. Basic familiarity with R syntax, reading in and manipulating data, installing packages from CRAN or GitHub, and basic knowledge of writing custom functions will be helpful. We will focus on practical examples of leveraging LLM tools in data visualization workflows, including an overview of the principles of data visualization and a discussion of GPT models for writing code and data exploration.

Note: Access to and familiarity with R/RStudio is required for the hands-on exercises. We recommend a local installation (https://www.r-project.org/https://posit.co/download/rstudio-desktop/), but a browser-based Windows virtual environment is available through UM Virtual Sites (U-M login required). A list of needed packages will be provided before the workshop.
Instructor: Dr. Jacob Berv, Schmidt AI in Science Fellow, Michigan Institute for Data Science

Past Events – Winter 2024

Data Analysis: Quantitative Data

Tuesday, May 14, 2024; 10:00 AM-12:00 PM

(500 Church St., Ann Arbor MI 48109)

About: In this open-ended session, we will try to get ChatGPT, Claude, and other LLMs to generate code and graphics  — both classically in R and Bayesianly in Stan — for some of the most common models run in the social and physical sciences, starting with standard regression and working our way up to various nonlinear models (e.g., GAMs, GPs), time-series / panels, and discrete choices (e.g., binary and multinomial logit). The emphasis will be on data exploration, generalizing code to relax assumptions underlying more computationally simple models, and locating bottlenecks in existing code.

Note for participants: Bring your laptop! This session will include use of custom GPTs, accessible through ChatGPT Plus ($20/monthly). Test data will be distributed in advance, but participants can bring some of their own to see if we can analyze it collectively in real-time. It is recommended, but optional, to have RStudio installed on your own laptop or to be able to run it remotely (e.g., on Great Lakes).

Instructor: Fred Feinberg, Joseph Handleman Professor, Professor of Marketing, Stephen M Ross School of Business and Professor of Statistics, College of Literature, Science, and the Arts

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Putting it all together: Farm-to-table GenAI

Monday, May 13, 2024; 12:00 PM – 3:00 PM

(500 Church St., Ann Arbor MI 48109)

About: Dr. Juan B. Gutiérrez, Professor and Chair of Mathematics at the University of Texas at San Antonio, will guide participants on how to constrain ChatGPT through custom instructions to maximize the likelihood of obtaining scientifically correct answers to your queries, with a focus on reproducibility. Develop (or hone) your ChatGPT skills developing an analysis pipeline for a real dataset that will teach you something you maybe did not know about your own community in the US (the 2018 Civil Rights Dataset from the Department of Education). There will be step-by-step tutorials, or open exploration suggested for beginner, intermediate, and advanced participants; the only prerequisite is to bring a laptop. The techniques applied in this workshop can be re-deployed in research projects in multiple domains. Participants can have ChatGPT write their manuscripts for peer-review using this rich dataset.

Instructor: Juan Gutiérrez, Professor and Chair of Mathematics, University of Texas at San Antonio

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From Search to Synthesis: AI Tools for Literature Discovery and Summarization

Monday, April 22, 2024; 10:00 AM-12:00 PM

About: This session introduced generative AI tools that can assist you with literature discovery, summarization, and synthesis. Featured tools include Open AI’s chatGPT, UMGPT, Anthropic’s Claude, ResearchRabbit, and more.

Instructors:
Jamie Niehof, Engineering Librarian
Tyler Nix, Associate Director, Research & Informatics, Taubman Health Sciences Library
Sarah Barbrow, Assistant Director, Engineering Librarian

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GenAI Tools for Writing and Presentation

Monday, March 25, 2024; 1:00 PM-3:00 PM

About: This session will introduce you to using ChatGPT and other tools for academic writing, including topics such as drafting communications, making posters and presentations, brainstorming ideas, and organizing notes.

Instructor: Stephanie Moody, Lecturer II, English Department and Sweetland Center for Writing

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Text as Data

Monday, March 11, 2024

About: attendees learned about generative AI tools for working with text data, including creating and analyzing data from a variety of sources; discussion of benefits, capabilities, and challenges including how to assess bias. Hands-on exercises focused on real-world examples using text data. Instructor Dr. Mark Hansen was the inaugural director for the David and Helen Gurley Brown Institute of Media Innovation and is a data scientist at Columbia University working at the intersection of data, art and technology. His work has appeared in the Museum of Modern Art in New York, the Whitney Museum, and the lobby of the New York Times.

Instructor: Mark Hansen, David and Helen Gurley Brown Professor of Journalism and Innovation; Director, David and Helen Gurley Brown Institute of Media Innovation, Columbia Journalism School, and Professor, Department of Statistics

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An Introduction to Generative AI Tools for Research

Friday, February 16, 2024

About: This session will introduce you to some useful ways to incorporate Generative AI tools in your research, including a brief outline of tools and topics to be covered in depth in the subsequent sessions. It will also include an introduction to prompting with ChatGPT.

Instructor: James Boyko, Schmidt AI in Science Postdoctoral Fellow, Michigan Institute for Data Science

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Past Events – Fall 2023

During the Fall ’23 semester, MIDAS and the Michigan AI Laboratory jointly offered the inaugural series of Generative AI tutorials, aimed to help researchers across fields to incorporate Generative AI tools and methodologies in their research. Each session consisted of lectures, demonstrations, and hands-on tutorials. See below for session recordings, materials, and slides where available.

See also: MIDAS, Michigan AI Lab host interactive generative AI workshopThe Michigan Daily

Making Generative AI Better for You: Fine-tuning and Experimentation for Custom Research Solutions

November 29, 2023

Making Generative AI Better for You: Fine-tuning and Experimentation for Custom Research SolutionsShane Storks, Graduate Student Research Assistant, Computer Science and Engineering, College of Engineering

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Tutorial: Fine-tuning LLMSShane Storks, Graduate Student Research Assistant, Computer Science and Engineering, College of Engineering

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Integrating Generative Image AI into Your Research Workflow

October 27, 2023

Generative Image Models in Research – Jeong Joon Park, Assistant Professor of Electrical Engineering and Computer Science, College of Engineering

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Tutorial: Generative Adversarial Networks (GANs)Anthony Carreon, Graduate Student Research Assistant, Aerospace Engineering, College of Engineering

MATERIALS

Code Smarter, Not Harder: Harnessing Generative AI for Research Programming Efficiency

October 18, 2023

Using Generative AI to Enhance Coding in Research – Sindhu Kutty, Lecturer IV in Electrical Engineering and Computer Science, College of Engineering

VIEW RECORDINGMATERIALS

Tutorial: Using Generative AI to Improve Your Code (focusing on Python but applicable to other languages too) – Qiyuan Zhao, Research Fellow, Medicinal Chemistry, College of Pharmacy

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Writing, Planning and Literature Review: Enhancing Professional Productivity with Generative AI

October 2, 2023

Ethical Considerations for Using Generative AI in Research – H. V. Jagadish, Edgar F Codd Distinguished University Professor of Electrical Engineering and Computer Science, Bernard A Galler Collegiate Professor of Electrical Engineering and Computer Science, Professor of Electrical Engineering and Computer Science, College of Engineering; Director of the Michigan Institute for Data Science

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Tutorial: Using Generative AI to Enhance Research Workflows James Boyko, Schmidt AI in Science Postdoctoral Fellow, Michigan Institute for Data Science

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