Taking place on April 12-14, 2023 in Ann Arbor, Michigan, this event offers outstanding graduate students and postdocs from around the US the opportunity to engage in research discussions with peers and with research leaders, and receive career mentoring, as they grow to become future research leaders in data science and Artificial Intelligence (AI).
2023 Theme: “Responsible data science and AI”
Data science and AI are having a significant impact on society in uncountable ways, leading to huge benefits in many cases. Yet, increasingly complex analytical pipelines working with poorly understood heterogeneous data sets can give rise to harms in many ways. Furthermore, there could be deleterious systemic effects such as the magnification of disinformation or surveillance capitalism. There has been tremendous recent interest in understanding and managing these concerns. We invite nominations for young scholars whose research is related to topics in this broad area, including, but not limited to:
- Equity and fairness, particularly in automated decision making
- Explainability of analytical results
- Reproducibility and replication of scientific results
- Systemic issues, particularly those impacting marginalized populations
- New in 2023: Responsible AI in science and engineering. MIDAS has recently established a large postdoctoral training program (the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, a Schmidt Futures Program). With this, we are dedicated to promoting responsible data science and AI for natural sciences and engineering.
- Research talks by the attendees and by leading researchers.
- Career mentoring sessions by University of Michigan faculty members, department chairs, and industry representatives.
- Networking sessions with other attendees, University of Michigan faculty and trainees, and industry representatives.
Who should be nominated:
- Doctoral candidates and postdoctoral fellows whose research falls within this year’s theme;
- They should be ready to apply for jobs (either academic or non-academic, postdoctoral positions included) in 2023 or 2024.
- Exceptional students in a Master’s Program will be considered, if they are from a university that does not offer PhD programs in a data science or AI related field.
- University of Michigan PhD students and postdocs are eligible.
Who should be the nominators:
Nominations may be from department chairs, institute directors, deans / associate deans or other university leaders.
Diversity and inclusion:
We are particularly interested in developing a diverse group of scholars, considering diversity in all respects, including race, gender, national origin, and socioeconomic background. In the past, more than half of the attendees have been women and underrepresented minorities, and we strongly encourage the nomination of trainees from underrepresented groups.
The nomination process:
Nominations may be uploaded through this online form.
The nomination package should be one .pdf file including the following:
- The CV of the nominee.
- A one-page statement from the nominee that describes their current research project (s), long-term research interest and what they want to gain from attending this Summit.
- A letter of support from the nominator delineating the strengths and experiences of the nominee and why this Summit will benefit them.
- Each nominator may submit up to two nominations.
- Only one nominee from each university may be accepted to the Summit and attend at no cost (MIDAS will cover the cost of travel, lodging and food).
- If spaces allow, we may accept a second nominee from a university but will not be able to cover the cost.
- Nomination: by 11:59 pm, Feb. 17, 2023
- Notification of decisions: by Feb, 24, 2023
Please direct any queries to email@example.com.
About the Faculty Mentors
Prominent researchers from academia and industry will be mentors for the attendees, and will offer career guidance and research insight. The 2023 mentors are to be determined, previous years’ mentors include:
- Dr. Marybeth Broadbent, Data Scientist at Google
- Dr. Jeffrey Fessler, Professor of the Department of Electrical and Computer Engineering, University of Michigan
- Dr. H. V. Jagadish, Professor of Computer Science and Engineering, MIDAS Director, University of Michigan
- Dr. Frauke Kreuter, Professor of Survey Methodology, Co-Director of Social Data Science Center, University of Maryland
- Dr. Margaret Levenstein, Director of the Inter-university Consortium for Political and Social Research, University of Michigan
- Dr. David Mongeau, Director, School of Data Science, Professor of Practice, University of Texas at San Antonio
- Dr. Shashi Shekhar, Professor of Computer Science, University of Minnesota
- Dr. Kevin Ward, Professor of Emergency Medicine, University of Michigan
- Dr. Michael Wellman, Professor and Chair of the Department of Computer Science and Engineering, University of Michigan