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Research to simplify big data graphs earns Best Paper Award at IEEE SSP 2023
Research 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.Teaching Machine Learning in ECE
With 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 UniversityImmune to hacks: Inoculating deep neural networks to thwart attacks
The adaptive immune system serves as a template for defending neural nets from confusion-sowing attacksQing Qu receives CAREER award to explore the foundations of machine learning and data science
His 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 redundanciesThe artistry of mathematical models
Artist 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.
Tracking COVID-19 spread faster, and more accurately
A new application for an ongoing NSF project could bolster contract tracing efforts.
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.
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 manifest
Prof. 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.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.
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.
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.
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.
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.
Laura Balzano partners with 3M to advance research in big data
Prof. Laura Balzano received a 2018 3M Non-Tenured Faculty Award to advance her research in Big Data.$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.
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.
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.
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.
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.
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.
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.