Lin Ma

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My research interests lie in the intersection of database management systems (DBMSs) and machine learning (ML), especially using ML/AI techniques to automate database administration/tuning to remove human impediments.

Catherine Kaczorowski

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The Kaczorowski laboratory, led by Dr. Catherine Kaczorowski, pioneers techniques to identify and validate genetic and cellular mechanisms that promote resilience to cognitive aging, Alzheimer’s disease, and other age-related dementias. By combining mouse and human systems; genomic, anatomic, and behavioral approaches; and integrative analyses across multiple scales, data types, environmental factors, and species, we are accelerating the discovery of the precise genetic mechanisms of cognitive resilience that could yield the next generation of targets and therapeutic strategies for promoting brain health. We are now uniquely poised to propel the field of personalized medicine forward using our genetically diverse, yet reproducible models of human neurodegenerative dementias, having already contributed conceptual and technical advances that revolutionized our ability to study complex diseases, specifically human AD dementia.

Mosharaf Chowdhury

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I am a computer scientist and an associate professor at CSE Michigan, where I lead the SymbioticLab (https://symbioticlab.org/). My research improves application performance and system efficiency of AI/ML and Big Data workloads with a recent focus on optimizing energy consumption and data privacy. I lead the ML Energy initiative (https://ml.energy/), a consortium of researchers focusing on understanding, controlling, and reducing AI/ML energy consumption. Over the course of my career, I have worked on a variety of networked and distributed systems. Recent major projects include Infiniswap, the first scalable memory disaggregation solution; Salus, the first software-only GPU sharing system for deep learning; FedScale, a scalable federated learning and analytics platform; and Zeus, the first GPU energy optimizer for AI. In the past, I invented the coflow abstraction for efficient distributed communication, and I am one of the original creators of Apache Spark. Thanks to my excellent collaborators, I have received many individual awards, fellowships, and paper awards from top venues like NSDI, OSDI, ATC, and MICRO.

Peter Reich

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Reich conducts global change research on plants, soils, ecosystems and people across a range of scales. His work links fundamental physiology with community dynamics and ecosystem structure and function, from the patch to the globe, within the context of the myriad of global environmental challenges that face us. This includes studying the effects on natural and human ecosystems of rising CO2 and associated climate change, biodiversity loss, and wildfire. This research involves a variety of tools and approaches (long-term experiments, observations, global data compilations, statistical and simulation models), a diverse set of ecosystems (boreal forest, temperate grassland, and more), and a range of scales (local, regional, global). The overarching goal is to understand what we humans are doing to nature in order to help orchestrate a shift towards a nature-forward prioritization that will in turn support and sustain human society.

I studied physics and creative writing and became interested in the fate of our environment; over time I began using tools from each focal area to advance ecological science in a changing world

Cheng Li

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My research focuses on developing advanced numerical models and computational tools to enhance our understanding and prediction capabilities for both terrestrial and extraterrestrial climate systems. By leveraging the power of data science, I aim to unravel the complexities of atmospheric dynamics and climate processes on Earth, as well as on other planets such as Mars, Venus, and Jupiter.

My approach involves the integration of large-scale datasets, including satellite observations and ground-based measurements, with statistical methods and sophisticated machine learning algorithms including vision-based large models. This enables me to extract meaningful insights and improve the accuracy of climate models, which are crucial for weather forecasting, climate change projections, and planetary exploration.

Qiong Yang

Qiong Yang

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My research program at the University of Michigan (UM) integrates the fields of biophysics, quantitative systems biology, and bottom-up synthetic biology to understand complex stochastic cellular and developmental processes in early embryos.
We have developed innovative computational and experimental techniques in microfluidics and imaging to allow high-throughput quantitative manipulation and single-cell lineage tracking of cellular spatiotemporal dynamical processes in various powerful in vitro and in vivo systems we established in my lab. These systems range from cell-free extracts, synthetic cells reconstituted in microemulsion droplets, presomitic mesoderm (PSM) and progenitor zone (PZ) cells dissociated from the zebrafish tail buds, their re-aggregated 2D and 3D cell-cell communications, ex vivo live tissue explants, and live embryos.
Our current research questions center around the understanding of the design-function relation of robust biological timing, growth, and patterning, how individual molecules and cells communicate to generate collective patterns, and how biochemical, biophysical, and biomechanical signals work together to shape morphogenesis during early embryo development.

Chuan Zhou

Chuan Zhou

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With a passion for developing decision support systems that integrate cutting edge techniques from artificial intelligence, quantitative image analysis, computer vision, and multimodal biomedical data fusion. Research interests have been focusing on characterizing diseases abnormalities and predicting their likelihood of being significant, with the goal to enable early diagnosis and risk stratification, as well as aiding treatment decision making and monitoring.

David Williams

David Williams

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I have several areas of study that touch on the fields of Data Science.

First I am the UM PI of PCORnet a national network of over 80 institutions that support clinical research. PCORnet possesses a common data model allowing for the harmonization of the electronic health record across the network. The common data model is helpful in cohort discovery, development of computable phenotypes, the study of rare diseases, and applications of machine learning for identifying patterns in disease and health care services that can help to form better models of precision care.

My second area of interest is in the use of big data to support behavioral change. PainGuide is a digital pain self-management program developed at UM that offers a variety of evidence-based methods for improving and managing pain. User data can inform AI algorithms to refine content and recommendations for the participants so as to personalize care and improve outcomes.

Nishil Talati

Nishil Talati

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I am a research faculty at the Computer Science and Engineering department at University of Michigan. I work with a group of talented PhD students on computer architecture, compiler techniques, and software engineering. My group focuses on developing novel software and hardware solutions to optimize large-scale data intensive worklods (e.g., graph traversals).

I earned my PhD degree in CSE from University of Michigan, Ann Arbor, USA, master’s degree in EE from Technion – Israel Institute of Technology, Haifa, Israel, and an undergraduate degree in EEE from BITS Pilani, Goa Campus, Goa, India.

Sarah Mills

Sarah Mills

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Sarah Mills’ research looks at how renewable energy development impacts rural communities (positively and negatively), the disparate reactions of rural landowners to wind and solar projects, and how state and local policies facilitate or hinder renewable energy deployment. Through a grant from the Department of Environment, Great Lakes and Energy, she also helps communities in incorporating clean energy in their planning and zoning. With respect to data science, in addition to conducting social science surveys, Sarah has also developed a unique database–energyzoning.org–which includes local government zoning regulations from six states across the Midwest

 


Research Highlights