Faculty Mentors
Each Fellow must have at least one U-M faculty member as the primary mentor at the time of the application (the list of participating faculty will be posted by Sept. 1, and will keep being updated). A second mentor with complementary expertise is required when the Fellow starts in the program. If needed, the primary mentor can help identify a suitable second mentor. Working together with MIDAS, the mentors will provide career guidance to the Fellows, meet with them regularly to assess research progress, help the Fellows seek opportunities for career advancement, and participate in activities that strengthen the Fellows community and the U-M data science and AI community.
While all faculty members in research domains within the scope of this program are eligible to be mentors, not all have funding or bandwidth to accept new postdocs. In order to help postdoc applicants connect with potential mentors, we maintain a list of faculty members who have opted in this program. If you would like to opt in, please sign up with this form. Please note that faculty members who are not on this list can still be mentors. Being on the list simply makes it easier for applicants to find you.
For the sake of the program’s scientific diversity, faculty mentors of the current Fellows are discouraged to be mentors of new applicants.
Expectations
- Cost share: Faculty mentors and MIDAS will provide 50:50 cost share to cover the postdoc’s salary and benefits.
- Salary: Commensurate to norms in each research field, funded jointly by MIDAS and faculty mentors. Faculty mentors will work with MIDAS to determine the exact salary.Â
- Office space: Fellows are expected to conduct their work on U-M’s Ann Arbor Campus. They will be expected to spend at least 50% of time at MIDAS so that they can be part of the data science and AI postdoc network and enhance the interdisciplinary reach of MIDAS.Â
- Professional service: The Fellows will be expected to spend 10% of their effort on MIDAS programs that strengthen MIDAS’s core pillars. Based on their career plans, they can choose to be involved in activities such as developing tools for research, training and mentoring, and data science projects for positive societal impact. They will also be expected to interact with the U-M data science and AI community through research presentations and other events.Â
- Selection process:Â A faculty review committee will select the top candidates. MIDAS will consult with their faculty mentors to determine the salary, then notify the candidates.
How to participate
- MIDAS faculty members can sign up to participate in this program, with the understanding that, if their applicant is selected, their portion of the funding needs to be in place before the Fellows start at U-M. You do not need to tell us what the source of funding will be until it is time to make offers. The only constraint is that the funding should not require substantial non-research time commitment from the fellow, such as teaching a course.
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- Anyone who is currently not a MIDAS affiliate faculty member will need to join before they can be placed on the participating faculty list.
- Any faculty member who is not on the participating faculty list may still submit an application with a candidate. Not being listed simply means that it is very unlikely you will receive inquiries from potential applicants.Â
- MIDAS will post the participating faculty list online by Aug. 30, and will update the list as we receive information from faculty. Candidates and potential mentors will need to first agree on research direction and mentor funding commitment before submitting applications to MIDAS. The deadline for application is 11:59 pm EST Nov. 30, 2023.
Current Data Science Mentors
| Name | Title | Primary Department: | Tagline: |
| Arun Agrawal | Professor | School for Environment and Sustainability | The politics of international development, and environmental conservation, institutional change |
| Raed Al Kontar | Assistant Professor | Industrial and Operations Engineering, College of Engineering | Smart and connected products and systems |
| Camille Avestruz | Assistant Professor | Physics, LSA | Evolution of galaxy clusters, machine learning in cosmology |
| Veera Baladandayuthapani | Professor | Biostatistics, School of Public Health | High-dimensional modeling and Bayesian inference |
| Elizabeth Bondi-Kelly |
Assistant Professor | Computer Science and Engineering | AI for social impact |
| David Brang | Associate Professor | Psychology | Multisensory, electrophysiology, machine learning, neuro-oncology, neuroscience |
| Christopher Brooks | Research Assistant Professor | School of Information Director, Learning Analytics and Research in the Office of Digital Education & Innovation |
Visualizing the interaction between learners and learning technology |
| Ceren Budak | Assistant Professor | School of Information | Computational social science |
| Bilal Butt | Associate Professor | School for Environment and Sustainability | Agritech, Big Data, Environmental Social Sciences |
| Eunshin Byon | Associate Professor | Industrial and Operations Engineering, College of Engineering Civil and Environmental Engineering, College of Engineering |
Sustainable energy systems and reliability engineering |
| Dallas Card | Assistant Professor | School of Information | Natural language processing, and computational social science, machine learning |
| Tim Cernak | Assistant Professor | Medicinal Chemistry, College of Pharmacy Chemistry, LSA Graduate Program in Chemical Biology |
Computational design of chemical reactions and synthesis |
| Sriram Chandrasekaran | Assistant Professor | Biomedical Engineering, College of Engineering | Computer models of protein networks |
| Yang Chen | Assistant Professor | Statistics, LSA | Statistical inference and applied statistics in biology and astronomy |
| Thomas L. Chenevert | Professor | Radiology, Michigan Medicine | Longitudinal Image Registration, Oncologic MR Imaging, Quantitative Imaging Biomarkers, Tumor Volume Segmentation |
| Lia Corrales | Assistant Professor | Astronomy | Statistical techniques for studying astrophysical aerosols in the X-ray and UV |
| Walter Dempsey | Assistant Professor of Biostatistics, Assistant Research Professor at the Institute of Social Research | Department of Biostatistics | Mobile Health, Network Science, Statistical Methods |
| Paramveer Dhillon | Assistant Professor | School of Information | Computational social science, Natural language processing, Statistical Machine Learning, and Field/Digital Experiments |
| Ivo D. Dinov | Professor | Computational Medicine and Bioinformatics Human Behavior and Biological Sciences Michigan Institute for Data Science (MIDAS) |
Mathematical modeling, statistical analysis and data visualization |
| Marisa Eisenberg | Assistant Professor | School of Public Health | Mathematical modeling of disease mechanisms, and intervention design, forecasting |
| August (Gus) Evrard | Professor | Physics and Astronomy, LSA | Computational cosmology |
| Anne Fernandez | Associate Professor | Psychiatry, Medical School | Applying precision health approaches to advance the science of addiction treatment |
| Jeff Fessler | Professor | EECS, College of Engineering Biomedical Engineering, College of Engineering Radiology, Michigan Medicine |
Large-scale inverse problems in image reconstruction |
| Nancy Fleischer |
Associate Professor | Epidemiology | Survey methodology, epidemiology, health equity, policy, public health |
| Lana Garmire | Associate Professor | Computational medicine and bioinformatics, Medical School | Data science for actionable transformation of human health from the bench to bedside |
| Andrew Gronewold | Associate Professor | School for Environment and Sustainability | Quantifying and communicating uncertainties arising within long-term hydrological monitoring networks and data |
| Anhong Guo | Assistant Professor | EECS, College of Engineering, School of Information |
Hybrid human-AI intelligent interactive systems to provide access to visual information in the real world
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| Libby Hemphill | Research Associate Professor | School of Information | Digital data, justice, social media |
| Wei Hu | Assistant Professor | Computer Science and Engineering | Deep Learning, Representation Learning, machine learning, optimization, theory |
| Xun Huan | Assistant Professor | Mechanical Engineering, College of Engineering | Uncertainty quantification, and numerical optimization, data-driven modeling |
| Xianglei Huang | Professor | Department of Climate and Space Sciences and Engineering | Climate diagnostics, data modeling, optimization, remote sensing, time-series analysis |
| Ivy F. Tso | Associate Professor | Psychiatry | Psychiatric disorders, brain network, computational and predictive models |
| Meha Jain | Assistant Professor | School for Environment and Sustainability | Agriculture, machine learning, remote sensing, sustainability |
| David Jurgens | Assistant Professor | School of Information | Computational social science and natural language processing |
| Jian Kang | Associate Professor | Biostatistics | Bayesian methods, composite likelihood approach and missing data problems, efficient statistical computation algorithms, graphical models, latent source separation methods, network inference, ultrahigh-dimensional feature selection |
| Evan Keller | Professor of Urology and Pathology | Urology | Single cell and spatiotemporal analyses of healthy and diseased tissues |
| Nicholas Kotov | Professor | Chemical Sciences and Engineering | Biomimetic Nanostructures |
| Arpan Kusari | Assistant Research Scientist | Assistant Research Scientist, UMTRI | LiDAR, Reinforcement Learning, autonomous vehicles, realistic simulation, uncertainty estimation |
| Elizaveta Levina | Vijay Nair Collegiate Professor | Statistics, LSA | Statistical inference on realistic models for network |
| Gen Li | Assistant Professor | Department of Biostatistics | Data Integration, Dimension Reduction, Microbiome Research, Parsimonious Models, graphical models, predictive modeling |
| Yi Li | Professor | Biostatistics, School of Public Health Kidney Epidemiology and Cost Center |
Statistical methods for kidney epidemiology |
| Max Li | Assistant Professor | COE (AERO, IOE, CEE) | Design, Management, and Optimization of Air Transportation Systems |
| Zhongming Liu | Associate Professor | Biomedical Engineering | Computational and cognitive neuroscience, deep neural networks |
| Jie Liu | Assistant Professor | Computational Medicine and Bioinformatics | Machine learning and computational genomics |
| Sabine Loos | Assistant Professor | Civil and Environmental Engineering | Data and user-driven approaches on disasters and equity |
| Wei Lu | Professor | Mechanical Engineering | Integrating human knowledge into machine learning |
| Qiaozhu Mei | Associate Professor | School of Information EECS, College of Engineering |
Information retrieval and text mining |
| Briana Mezuk | Associate Chair and Associate Professor, Epidemiology | Department of Epidemiology | Depression, epidemiology, integrative lifespan, suicide aging |
| Emily Mower | Professor | Computer Science and Engineering | Provost Emotion modeling and assistive technology |
| Nambi Nallasamy | Assistant Professor of Ophthalmology and Visual Sciences and Assistant Professor of Computational Medicine and Bioinformatics | Ophthalmology and Visual Sciences | Machine learning algorithms for the enhancement of outcomes in cataract surgery |
| Joshua P Newell | Associate Professor | School for Environment and Sustainability | Geographic information systems, gis, remote sensing, resource flow analysis, sustainability, urban systems |
| Samet Oymak | Assistant Professor | Electrical Engineering and Computer Science | Decision-making, efficient and robust ML, learning and optimization theory |
| Bruce Allen Palfey | Associate Professor & Associate Director of Academic Programs, Chemical Biology Program, Life Sciences Institute | Biological Chemistry, Medical School | Mechanisms of flavin-containing enzymes of pyrimidine metabolism, dihydroorotate dehydrogenases, dihydrouridyl-tRNA synthases, thymidylate synthases |
| Yulin Pan | Assistant Professor | Department of Naval Architecture and Marine Engineering | Data assimilation, fluid mechanics, physical oceanography |
| Vitaliy Popov | Assistant Professor | Medical School, Department of Learning Health Sciences | Clinical simulations, learning analytics, multimodal |
| Qing Qu | Assistant Professor | EECS, College of Engineering | Deep Learning, Inverse Problems, Nonconvex Optimization, Representation Learning |
| Majdi Radaideh | Assistant Professor | Nuclear Engineering and Radiological Sciences | Autonomous Control, Nuclear Reactor Design, Physics-informed Machine Learning, Uncertainty quantification, optimization |
| Arvind Rao | Associate Professor | Computational Medicine and Bioinformatics, Michigan Medicine Radiation Oncology, Michigan Medicine Biomedical Engineering, College of Engineering |
Multi-modal decision algorithms that integrate clinical measurements |
| Daniel Romero | Associate Professor | Information, School of Information, Complex Systems, LSA, Electrical and Computer Engineering, College of Engineering |
Empirical and theoretical analysis of social and information networks |
| Perry Samson | Professor | Climate and Space Science, College of Engineering School of Information |
Relationships between student performance and behaviors |
| Maureen Sartor | Professor | Computational Medicine and Bioinformatics | Bioinformatics, biomarkers, cancer, classification, epigenomics, integrative omics, prediction, regulatory genomics |
| Xu Shi | Assistant Professor | Department of Biostatistics | EHR data, causal inference |
| Yajuan Si | Research Assistant Professor | Survey Research Center, Institute for Social Research | Bayesian, confidentiality protection, missing data, statistics, survey |
| Peter Song | Professor | Biostatistics, School of Public Health | Data Integration, distributed inference, machine learning |
| Wencong Su | Assistant Professor | EECS, College of Engineering | Efficient management of a large number of devices through distributed intelligence |
| Vijay Subramanian | Associate Professor | EECS, College of Engineering | Stochastic modeling, decision and control theory and applications to networks |
| Misha Teplitskiy | Assistant Professor | School of Information | Computational methods, experimental methods, science of science |
| Ivy F. Tso | Associate Professor of Psychiatry, Adjunct Associate Professor of Psychology | Psychiatry | Psychiatric disorders, brain network, computational and predictive models |
| V. G. Vinod Vydiswaran | Assistant Professor | Learning Health Sciences, Michigan Medicine School of Information |
Text mining, NLP, and ML for extracting relevant information from health-related text corpora |
| Yixin Wang | Assistant Professor | Statistics, LSA | Large-scale probabilistic machine learning, causal inference, machine learning for science |
| Joshua Welch | Assistant Professor | Computational Medicine and Bioinformatics | Machine learning for representing molecular cell states |
| Zhenke Wu | Assistant Professor | Biostatistics, School of Public Health | Statistical methods for precision medicine |
| Ming Xu | Professor | School for Environment and Sustainability Civil and Environmental Engineering, College of Engineering |
Computational and data-enabled methodology for sustainability |
| Qiong Yang |
Associate Professor | Biophysics, and affiliated with Bioinformatics, CDB and CMB | Biophysics of Living Systems, Quantitative Systems/Synthetic Biology |
| Yang Zhang | Professor | Department of Nuclear Engineering and Radiological Sciences, Department of Materials Science and Engineering, Department of Robotics, Applied Physics Program | Far-from-equilibrium physics, extreme robots, liquid state physics, long timescale phenomena, neutron scattering, rare events, soft robots, statistical mechanics, swarm robots |
| Xiang Zhou | John G Searle Assistant Professor | Biostatistics, School of Public Health | Statistical and computational methods for genetic and genomic studies |
| Paul Zimmerman | Assistant Professor | Chemistry, LSA | Computational chemical reaction discovery |
