Linking online and offline social networks to better predict real world impactProf. Lei Ying leads a new MURI that is focused on the interplay between online and offline networks and how they could impact disruptive behavior and events.
Nouman Khan works to study and improve the operation of multi-agent systems and networksKhan was awarded a Rackham International Student Fellowship for his research on data-driven control of multi-agent systems, as well as research that studies the spread of information in networks.
Improving generative AI models for real-world medical imagingProfessors Liyue Shen, Qing Qu, and Jeff Fessler are working to develop efficient diffusion models for a variety of practical scientific and medical applications.
Improving the accuracy and applicability of large language models, like ChatGPTProf. Al Hero’s new method, which enhances the reliability of predictive models and promises to reduce the risk of AI hallucinations, was selected as a spotlight paper at NeurIPS 2023.
Open-source training framework increases the speed of large language model pre-training when failures arisePipeline templates strike a balance between speed and effectiveness in resilient distributed computing.
Research to simplify big data graphs earns Best Paper Award at IEEE SSP 2023Research by PhD student Neophytos Charalambides and Professor Alfred Hero addresses computational and storage bottlenecks for graphs used in statistical problems, signal processing, large networks, combinatorial optimization, and data analysis.
H.V. Jagadish named Edgar F. Codd Distinguished University Professor of EECSProfessor Jagadish is being recognized for his work as one of the nation’s most visible and influential researchers in the interdisciplinary field of data science
Teaching Machine Learning in ECEWith new courses at the UG and graduate level, ECE is delivering state-of-the-art instruction in machine learning for students in ECE, and across the University
Immune to hacks: Inoculating deep neural networks to thwart attacksThe adaptive immune system serves as a template for defending neural nets from confusion-sowing attacks
Qing Qu receives CAREER award to explore the foundations of machine learning and data scienceHis research develops computational methods for learning succinct representations from high-dimensional data.
New grant aims to create better algorithms to manage big data by getting “non-real”Professors Laura Balzano and Hessam Mahdavifar are developing new ways to compress data through randomized algorithms to remove redundancies
The artistry of mathematical modelsArtist and professor Jessica Wynne features Prof. Laura Balzano’s blackboard in a photography series that captures the abstract beauty of problem solving.
Prof. Qing Qu uses data and machine learning to optimize the world
A new faculty member at Michigan, Qu’s research has applications in imaging sciences, scientific discovery, healthcare, and more.
Prof. Danai Koutra recognized as rising star with ACM SIGKDD Award
The Rising Star Award is based on an individual’s whole body of work in the first five years after the PhD.
Tracking COVID-19 spread faster, and more accurately
A new application for an ongoing NSF project could bolster contract tracing efforts.
How predictive modeling could help us reopen more safely
Graphical online simulation could spur more targeted COVID-19 protection measures.
Game theory and the COVID-19 outbreak: Coordinating our interests at individual to national levels
A major defense project pivots to explore how to encourage COVID-safe behavior effectively.
Catching nuclear smugglers: fast algorithm could enable cost-effective detectors at borders
The algorithm can pick out weak signals from nuclear weapons materials, hidden in ordinary radiation sources like fertilizer.
Xueru Zhang awarded Rackham Predoctoral Fellowship
Zhang is working to improve data security and address important ethical issues related to AI and discriminatory data sets.
Could a smartwatch identify an infection before you start spreading it?
A wrist-worn device detected disrupted sleep 24 hours before study participants began shedding flu viruses.
Analytical model predicts exactly how much a piece of hardware will speed up data centers
The analytical model, called Accelerometer, can be applied in the early stages of an accelerator’s design to predict its effectiveness before ever being installed.
Advancing the future of circuit design with Intel’s Dr. Eric Karl
Karl (BSE MSE PhD EE) talks about how his time at Michigan helped prepare him for his dream job at Intel and a career advancing embedded memory technology and circuits.
Using machine learning to detect disease before symptoms manifestProf. Alfred Hero speaks to ECE about his work using data to predict the transmission of infectious disease among people who are pre-symptomatic or asymptomatic and how it relates to COVID-19.
Big data, small footprint
How changing the rules of computing could lighten Big Data’s impact on the internet.
Generating realistic stock market data for deeper financial research
A team at Michigan proposed an approach to generating realistic and high-fidelity stock market data to enable broader study of financial markets.
Prof. Laura Balzano wins Education Excellence Award from the College of Engineering
Balzano is honored for her all-around excellence in teaching, mentorship, and curriculum development.
Three faculty earn MIDAS grants to broaden the frontiers of data science
This round of funding strongly encourages pioneering work with the potential for major expansion.
Beyond Moore’s Law: taking transistor arrays into the third dimension
Thin film transistors stacked on top of a state-of-the-art silicon chip could help shrink electronics while improving performance.
Prof. Dave Neuhoff says farewell after 45 years championing students, faculty, and the department
Neuhoff, an internationally recognized expert in information theory, source coding, and image processing, retired earlier this year.
$2M NSF grant to explore data equity systemsResearchers plan to establish a framework for a national institute that would enable research using sensitive data, while preventing misuse and misinterpretation.
$1M NSF grant supports new system for gathering, structuring data with ease
The team's new tool will combine of software and data to make gathering structured data dramatically easier.
Automated tool optimizes complex programs better than humans
Erie provided database repairs that were previously performed exclusively by human programmers.
Computer vision: Finding the best teaching frame in a video for fake video fightback
The frame in which a human marks out the boundaries of an object makes a huge difference in how well AI software can identify that object through the rest of the video.
Laura Balzano aims to improve precision medicine as a Fulbright Scholar
Balzano will work with Portuguese researcher Mário Figueiredo to develop new machine learning methods impacting medical diagnosis and treatment.
Laura Balzano receives NSF CAREER Award to improve machine learning for big data applications
Her research deciphering messy data sets will first tackle applications in genetics and computer vision.
‘Air traffic control’ for driverless cars could speed up deployment
Human-generated responses could remotely assist autonomous vehicles decision’s during times of uncertainty.
Laura Balzano receives ARO Young Investigator Award to improve high-dimensional big data problems
Applications include managing large networked systems, such as sensor networks, power grids, or computer networks.
ECE and data science: a natural connection
Electrical and Computer Engineering (ECE) faculty and students at Michigan are part of the revolution in data science that is happening today.
Two papers announced among 10 most influential in healthcare and infection control
The papers provide data-driven solutions to hospital infection and the use of machine learning in healthcare.
Prof. Laura Balzano receives AFOSR Young Investigator Award for research that addresses massive streaming data
Balzano uses statistical signal processing, matrix factorization, and optimization to unravel dynamic and messy data.
Michigan Data Science Team wrangles big data
MDST brings together students from many fields to get their hands dirty with real data science problems and tools.
Tool for structuring data creates efficiency for data scientists
Foofah is a tool that can help to minimize the effort and required background knowledge needed to clean up data.
Undocumented immigrants’ privacy at risk online, on phones
When it comes to their smartphones, immigrants struggle to apply instinctive caution, according to a study by a team of University of Michigan researchers.
Cafarella Receives VLDB Test of Time Award for Structured Web Data Search
This award is given to the VLDB paper published ten years earlier that has had the most influence since its publication.
Laura Balzano partners with 3M to advance research in big dataProf. Laura Balzano received a 2018 3M Non-Tenured Faculty Award to advance her research in Big Data.
Study maps careers of CS PhDs using decades of data
The researchers identified movement between industry, academia, and government work, tracked the growth of important organizations, and built predictive models for career transitions and employer retention.
“Stitching” together a web user from scattered, messy data
Even though we interact with different web services in different ways, there are clues in the data that can indicate trends and identify a unique profile.
$6.25M MURI project will decode world’s most complex networks
New tools could fight crime, protect financial system
Improving communication between humans and robots in 20 noisy questions
Hero and his team may have discovered a better way to facilitate communication using a twist on the classic game of 20 Questions.
Alfred Hero illustrates common threads of complex networks in Distinguished University Professor lecture
Lecture part of highest professorial honor bestowed on U-M faculty.
U-M, Cavium partner on Big Data research computing platform
The new partnership will provide scalable storage and an analytic software framework available to all U-M researchers.
$1.6M toward artificial intelligence for data science
DARPA is trying to build a system that can turn large data sets into models that can make predictions, and U-M is in on the project.
Michigan, Georgia Tech researchers funded to deter financial market manipulation
Increasingly, market manipulators are attacking market integrity through complex computer-controlled attacks.
“Learning database” speeds queries from hours to seconds
Verdict can make databases deliver answers more than 200 times faster while maintaining 99 percent accuracy.
Codeon is the intelligent assistant for software developers
With Codeon, developers can request help by speaking their requests aloud within the context of their Integrated Development Environment (IDE).
Kurator Will Help You Curate Your Personal Digital Content
Kurator is a hybrid intelligence system leveraging mixed-expertise crowds to help families curate their personal digital content, including videos and photos.
Movie design for specific target audiences
Researchers are working to design a successful movie that will attract the interest of a targeted demographic by leveraging user ratings, reviews, and product characteristics.
Social interaction patterns provide clues to real life changes
The identified changes in social media behavior may point to real events and changes, some of which can benefit from intervention.
COVE: a tool for advancing progress in computer vision
Centralizing available data in the intelligent systems community through a COmputer Vision Exchange for Data, Annotations and Tools, called COVE.
Shadows in the Dark WebSecrets lurk in the dark web, the 95 percent of the internet that most of us can't see. One U-M professor is bringing some of those secrets to light, making the digital and the real world a little safer.
Summer Bootcamp prepares undergraduates for work with big data
The Big Data Summer Bootcamp is a six-week interdisciplinary training and research program at the University of Michigan.
Collecting data to better identify bipolar disorder
Prof. Emily Mower Provost is collaborating to develop new technologies that provide individuals with insight into how the disease changes over time.
Fighting cyber crime with data analytics
QuadMetrics offers a pair of services to help companies both assess the effectiveness of their security and decide the best way to allocate (or increase) their security budget.
Google, U-M to build digital tools for Flint water crisis
CSE students and faculty will collaborate as a part of a larger team to help respond to the crisis.
Clark Zhang earns NSF Fellowship for data processing in MEMS networks
Clark proposed framing the issue of collecting data from a network of different sensors as an optimization problem, making a solution easier to formulate for different systems.
U-M researchers launch fight against C. difficile with $9.2M grant from NIH
Prof. Wiens will continue to use machine learning techniques to study the disease.
Machine learning proves useful for analyzing NBA ball screen defense
The team used machine learning to extract information from NBA sports data for automatically recognizing common defense strategies to ball screens.
Michael J. Cafarella selected for Sloan Research Fellowship
He has built software systems for information extraction, database integration, and feature engineering and applied these to problems in the social sciences.
Jenna Wiens receives NSF CAREER Award to increase the utility of machine learning in clinical care
Her primary research interests lie at the intersection of machine learning and healthcare.
Barzan Mozafari receives NSF CAREER Award to improve predictability of database systems
Prof. Mozafari is passionate about building large-scale data-intensive systems that are more scalable, more robust, and more predictable.
Censys enables fast searching of actionable internet data
The software enables users to ask questions about the hosts and networks that compose the Internet and get an immediate reply.
The Promise and Perils of Predictive Policing Based on Big Data
Such tactics, even if effective in reducing crime, raise civil liberty concerns.
Laura Balzano receives Intel Early Career Faculty Honor Program Award for research in big data
The purpose of the ECFHP is to help Intel connect with the best and brightest early career faculty members who show great promise.
Michigan Institute for Data Science: Bringing the MIDAS touch to big data
MIDAS is the new focal point for the multidisciplinary discipline of data science at Michigan, and part of Michigan’s $100M Data Science Initiative.
A real-world approach to digital signal processing
Students could use sensors or other data collection tools to pursue a goal of their choosing.
Yang Liu receives Best Applications Paper Award for cyber security research in phishing
His paper detailed his use of big data analysis to solve a major problem of cyber security.
Mapping the brain with lasers
Yoon is leading a team that will design new light sources with lasers capable of zooming in on individual neuron circuits within the brain.
Researchers Expose Security Flaws in Backscatter X-ray Scanners
Researchers demo hack to seize control of municipal traffic signal systems
Barzan Mozafari and collaborators chosen for best demo at ACM SIGMOD
Research in machine learning earns Notable Paper Award at AISTATS 2014
Prof. Scott’s research is in the field of machine learning, and his paper builds upon “supervised pattern classification.”
Gopal Nataraj earns Best Paper Award for improving MRI
Nataraj is using big data techniques to transform the field of medical imaging
Image processing 1,000 times faster is goal of new $5M contract
Lu plans to design and fabricate a computer chip based on so-called self-organizing, adaptive neural networks.
Third Annual Data Mining Workshop Brings Together 100+ Researchers100+ researchers from across the University of Michigan and from industry gathered on North Campus for the third U-M Workshop on Data Mining.
Prof. Raj Nadakuditi receives 2012 SPS Young Author Best Paper Award
Nadakuditi’s research has applications in biomedical signal processing, wireless communications, geophysical signal processing, array processing, and finance.
New techniques in medical informatics lead to improved diagnosis of MDS
The technique involves a visualization method that renders clinical flow cytometry data more interpretable to pathologists.