Welcome-back social and faculty research pitch

Wednesday, September 6, 2023
2:30 pm – 4:30 pm

Palmer Commons, Great Lakes Room
100 Washtenaw Avenue, Ann Arbor

Overview

The Michigan Institute for Data Science (MIDAS) invited all to kick off the new academic year with us at our annual Welcome-back Social and Faculty Research Pitch, with opportunities to talk with MIDAS affiliate faculty members and others in the U-M data science and AI research community, hear research collaboration opportunities, find out upcoming research and training activities at MIDAS, and discuss how MIDAS can work with you! 

Also at the event were three student organizations, discussing research participation with faculty, and meeting students who would like to join.

All U-M researchers were welcome to attend and present pitches, especially those faculty members who are new to U-M, or new to MIDAS. To give a research pitch, presenters need to be a MIDAS affiliated faculty member (for those who would like to join, fill out the application form). 

Speakers

Presentations

2:30 PM – 3:00 PM

Stacy Rosenbaum, Assistant Professor, Anthropology.
Research area: Evolutionary causes and consequences of social behavior.

Anne Draelos, Assistant Professor, Biomedical Engineering, Computational Medicine and Bioinformatics.
Research area: Real-time machine learning for adaptive neuroscience applications.

Minji Kim, Assistant Professor, Computational Medicine and Bioinformatics.
Research area: Computational 3D genomics.

Cam McLeman, Associate Professor, Mathematics and Applied Sciences.
Research area: Graph-Based Methods, Machine Learning, Mathematical and Statistical Modeling, Networks, Statistics.

Runzi Wang, Assistant Professor, Environment and Sustainability.
Research area: Built environment, landscape architecture, machine learning, stormwater management, stream water quality, urban hydrology.

 

3:00 PM – 3:30 PM

Yan Chen, Professor, Information.
Research area: Causal inference, data science for social good, experiment design.

Hui Jiang, Professor, Biostatistics.
Research area: Bioinformatics, computational statistics, machine learning, optimization, statistical genomics.

Sean Johnson, Assistant Professor, Astronomy.
Research area: Galaxy evolution, quasars, the circumgalactic medium, the intergalactic medium.

Liang Zhao, Associated research scientist, Climate and Space Science and Engineering.
Research area: Solar wind plasma, heliophysics.

Stella Yu – Professor, Computer Science and Engineering.
Research area: Representation learning with minimal supervision.

Nishil Talati, Assistant Research Scientist, Computer Science and Engineering.
Research area: Hardware-software co-design for efficient and secure data analytics.

 

3:30 PM – 4:00 PM

Wei Hu, Assistant Professor, Computer Science and Engineering.
Research area: Deep Learning, Representation Learning, machine learning, optimization, theory.

Max Z. Li, Assistant Professor, Aerospace Engineering, Industrial and Operations Engineering.
Research area: Design, management, and optimization of air transportation systems.

Elizabeth Bondi-Kelly, Assistant Professor, Computer Science and Engineering.
Research area: AI for social impact.

Liang Qi, Associate Professor, Materials Science and Engineering.
Research area: Atomistic simulations, computational materials science, machine learning.

Hui Deng, Professor, Physics.
Research area: Deep learning for nanophotonics applications.

Shai Revzen, Associate Professor, Electrical and Computer Engineering.
Research area: Biologically Inspired Robotics and Dynamical Systems.

P.C. Ku, Professor, Electrical and Computer Engineering.
Research area: Optoelectronic devices.

Majdi Radaideh, Assistant Professor, Nuclear Engineering and Radiological Sciences.
Research area: Autonomous Control, Nuclear Reactor Design, Physics-informed Machine Learning, Uncertainty quantification, optimization.

FAQ

Who should attend this event? Anyone interested in learning more about, becoming involved in, or meeting new people in the U-M data science and AI research ecosystem, but especially MIDAS affiliate faculty members, new U-M faculty members and those new to MIDAS, students or postdocs seeking faculty mentors and projects.

What is the format of the event? 

  • Each presenter will give a 3-minute research pitch, with up to three slides, followed by 1 question.
  • Audience members will vote for the “Best Research Pitch”. 
  • Ample networking time. 

Information for presenters:

You can present anything you’d like people to know about your research. It could be an overview of your research, or a specific project that needs collaboration or students, or a crazy idea that you want feedback about. But please consider the following:

  • How do you tell a compelling and clear story?
  • What do you want the audience to learn from your pitch?
  • How does your story help you achieve your goal of giving a pitch?

Outcomes

Audience members will select the “Best Research Pitch” awards.

Following the event, a special edition of the MIDAS newsletter will be dedicated to showcasing the research pitch award winners. We will publish all research pitch videos to the MIDAS YouTube channel and add the videos to the faculty profile pages on MIDAS website. (See here for a past example.) Presenters who want to use cloud computing resources may also have the opportunity to receive consultation and resources from Microsoft.

We are excited to showcase your research and to help you make connections in our community and across other institutions.

If you have any questions, please contact Beth Uberseder (MIDAS Research Manager) at ubersbe@umich.edu.