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Michigan hosts 7th annual Learning for Dynamics & Control Conference

The conference attracted 300 people from around the world to discuss the latest cross-disciplinary approaches in this new scientific area.

Qing Qu Receives 2025 Google Research Scholar Award for Developing Efficient Generative AI Models

Prof. Qu’s research aims to reduce the cost and complexity of fine-tuning and training large-scale foundation models, while advancing the accessibility and sustainability of high-performance generative AI.

Electrical and Computer Engineering curriculum prepares students to join the AI revolution

Best Student Paper Award for work in universal training of neural networks

ECE alum Mohammadreza Tavasoli Naeini, a former student of Prof. Al Hero, was first author on the paper and award recipient.

Siyi Chen awarded Predoctoral Fellowship to support research on Controllable and Interpretable AI models

Chen, Ph.D. student in Electrical and Computer Engineering, is working to improve the usability, safety, and reliability of AI systems in real-world applications.

Can Yaras awarded Predoctoral Fellowship to support research on deep learning and generative AI models

Yaras, Ph.D. student in Electrical and Computer Engineering, is working to better understand the inner workings of deep learning and provide better access to foundation models in AI.

Bridging gaps in rural health care with AI-powered mobile clinics

General practitioners with AI help could make diagnoses, run and interpret tests, and perform procedures like specialists.

New generative AI model can reconstruct a high-quality, sparse-view 3D CT scan with a much lower X-ray dose

Improvements move the deep learning technique towards use in 3D medical imaging.

Andrew Owens’ research group uses visual illusions to test the limits of diffusion models

Members of Andrew Owens's research group, Daniel Geng, Aaron Park, and Ziyang Chen, are using ambiguous image generation to understand diffusion models.

Fifteen papers by ECE researchers to be presented at the Conference on Neural Information Processing Systems

Topics of accepted ECE NeurIPS papers include diffusion models, large language models, multi-armed bandit models, and more.

ECE faculty design chips for efficient and accessible AI

Faculty specializing in architecture, hardware, and software innovation accelerate machine learning across a range of applications.

Andrew Owens receives NSF CAREER Award for research to improve machine perception systems

Prof. Owens’ research will help fully autonomous systems interact with their environments without human supervision.

Matthew Raymond recognized for research using ML techniques to design new types of medicine

Doctoral student Matthew Raymond wants to facilitate the development of new and groundbreaking nanomedicines.

Can Yaras recognized for his research aimed at efficient algorithms for LLMs

Doctoral student Can Yaras wants to reduce the carbon footprint of AI.

Leveraging artificial intelligence for early detection of lung cancer

Predictive models developed by an interdisciplinary U-M research team have improved early lung cancer detection beyond traditional measures, with the potential to save lives.

New textbook teaches students about matrix methods and their real world applications

Linear Algebra for Data Science, Machine Learning, and Signal Processing, written by ECE Professors Jeffrey Fessler and Raj Nadakuditi, provides an accessible and interactive guide to matrix methods.

OptoGPT for improving solar cells, smart windows, telescopes and more

Taking advantage of the transformer neural networks that power large language models, engineers can get recipes for materials with the optical properties they need.

Fourteen papers by ECE researchers to be presented at the International Conference on Machine Learning

Accepted papers for the ICML conference span topics including deep representation learning, language model fine-tuning, generative modeling, and more.

GenAI diffusion models learn to generate new content more consistently than expected

Award-winning research led by Prof. Qing Qu discovered an intriguing phenomenon that diffusion models consistently produce nearly identical content starting from the same noise input, regardless of model architectures or training procedures.

Linking online and offline social networks to better predict real world impact

Prof. 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.

Improving generative AI models for real-world medical imaging

Professors Liyue Shen, Qing Qu, and Jeff Fessler are working to develop efficient diffusion models for a variety of practical scientific and medical applications.

Neural Collapse research seeks to advance mathematical understanding of deep learning

Led by Prof. Qing Qu, the project could influence the application of deep learning in areas such as machine learning, optimization, signal and image processing, and computer vision.

Improving the accuracy and applicability of large language models, like ChatGPT

Prof. 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.

Understanding attention in large language models

How do chatbots based on the transformer architecture decide what to pay attention to in a conversation? They’ve made their own machine learning algorithms to tell them.

A coaching bot for students learning coding, computational Machine Learning, and AI

Prof. Raj Rao Nadakuditi is developing a generative AI coaching bot that provides feedback to strengthen self-regulated learning skills.

Research describing quantum-inspired computational imaging earns impact award

This Q&A with award co-recipient Alfred Hero offers a glimpse into the emerging field of single photon imaging.

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.

Nanobiotics: AI for discovering where and how nanoparticles bind with proteins

A new tool in the fight against superbugs goes beyond protein folding simulations like AlphaFold, potentially revealing antibiotic candidates.

A brain game may predict your risk of infection

When a person's cognitive function is highly variable, they're likely to be more infectious and have more symptoms after exposure to a respiratory virus.

Miniature and durable spectrometer for wearable applications

A team led by P.C. Ku and Qing Qu have developed a miniature, paper-thin spectrometer measuring 0.16mm2 that can also withstand harsh environments.

Neophytos Charalambides receives Best Poster Award for research in the area of Data Science

The research can be applied to a wide range of big data applications that rely on the multiplication of two matrices in linear algebra.

Designing Synthetic Human Gut Microbiome with AI

Prof. Al Hero was interviewed and gave a presentation about his research using machine learning to improve our understanding of the human gut

In Digital Signal Processing, students experiment with sensors for creative projects

Students created everything from a Wordle helper to a tool for melanoma detection to a program that identifies different marine species based on their underwater song.

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 University

Qing 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.

Katie Bouman talks legacy of the black hole imaging project and favorite U-M memories

Before Bouman became the face of the project that brought us the first ever image of a black hole, she was wowing ECE professors with design projects and hoarding Domino’s pizza with her HKN family.

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

$20M NSF AI-EDGE Institute aims to transform 5G and beyond networks

University of Michigan is a core member of a new NSF-led Institute that is a collaboration between 11 institutions, three government research labs, and four global companies

Three teams of graduate students awarded prizes for their final projects in Image Processing (EECS 556)

KLA sponsored prizes for three outstanding projects focused on improving image processing for neurosurgery and satellite applications and MRI reconstruction techniques.

3D motion tracking system could streamline vision for autonomous tech

Transparent optical sensor arrays combine with a specialized neural network in new University of Michigan prototype

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.

Caroline Crockett awarded Rackham Predoctoral Fellowship for research bridging two fields

Crockett’s dissertation will integrate two fields: image processing & machine learning and engineering education research

Research to improve medical imaging of the brain receives Magna cum Laude Merit award

The interdisciplinary team was able to dramatically speed up the process while potentially doubling the quality of the image

Magna cum Laude Merit Award for research to detect the progress of diseases such as multiple sclerosis

The researchers’ imaging technique is fast, accurate, and reproducible

Melissa Haskell receives NIH Fellowship for research to improve brain imaging

ECE postdoc Melissa Haskell works on improving functional magnetic resonance imaging so we can better measure and understand brain activity.

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.

Live public street cams are tracking social distancing

Voxel51, a U-M startup led by Prof. Jason Corso, uses custom AI to continuously track vehicle, cyclist, and pedestrian traffic in real time at some of the most visited places in the world.

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.

Alfred Hero named Fellow of Society for Industrial and Applied Mathematics (SIAM)

Hero was elected "for contributions to the mathematical foundations of signal processing and data science."

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.

A 3D camera for safer autonomy and advanced biomedical imaging

Researchers demonstrated the use of stacked, transparent graphene photodetectors combined with image processing algorithms to produce 3D images and range detection.

Creating a place where kids of all abilities can play together

Prof. Hun-Seok Kim helped design iGYM, an augmented reality system that allows disabled and able-bodied people to play physical games together.

Machine Learning and Systems: A conversation with 2020 Field Award winners Al Hero and Anders Lindquist

Hero and Lindquist took a few minutes to talk about the impact of machine learning on Signal Processing and Control Systems, and what they plan to do about it

Beyond Apollo 11: U-M ECE’s role in advancing space exploration

For the 50th anniversary of the Apollo 11 moon landing, U-M ECE takes a look back – and a look forward – to how our professors, students, and alums have made their mark on the field.

Alfred Hero Receives 2020 IEEE Fourier Award

Hero’s research in signal processing has explored theoretical foundations and applications including personalized health imaging and information networks.

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.

Laura Balzano receives AFOSR Young Investigator Award for research that addresses massive streaming data

Prof. 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.

Students win prizes for improving image processing techniques for liver cancer detection and much more

Students in EECS 556: Image Processing, explore methods to improve image processing in applications such as biomedical imaging and video and image compression

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.

Seeing through materials

By developing a fast algorithm to map out the paths light takes through yogurt, researchers aim to someday see through skin.

Students in EECS 556 win prizes for improving image processing techniques for camera motion blur and facial recognition

These students are learning to improve images in medical imaging, and improve facial recognition

Student teams earn prizes for analog-digital converter circuit designs in EECS 511

The winning projects were designed for battery-operated mobile applications as well as instrumentation and measure applications.

Gopal Nataraj receives U-M Rackham Predoctoral Fellowship to support high-impact research in medical imaging

Award for outstanding doctoral candidates near the end of their study.

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.

Alfred O. Hero, III named John H. Holland Distinguished University Professor of EECS

Hero is honored for his extraordinary accomplishments that have brought distinction to himself, his students, and to the entire University.

A better 3D camera with clear, graphene light detectors

While 3D films are currently made using multiple cameras to reconstruct each frame, this new type of camera could record in 3D on its own.

Al Hero gets a shoutout from the court

Hero was recognized as part of a program that sheds light on the University’s most distinguished faculty.

Al Hero receives 2015 IEEE Signal Processing Society Award

This is the highest award given by the Signal Processing Society, and honors outstanding technical contributions in the field.

Jeff Fessler receives Distinguished Faculty Achievement Award

Prof. Fessler has revolutionized medical imaging with groundbreaking mathematical models and algorithms that improve both safety and quality.

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.

Using data science to achieve ultra-low dose CT image reconstruction

Ultra-low dose CT scans that provide superior image quality could not only benefit patients, but they could open up entirely new clinical applications.

Prize winning class team project for improved image processing

The project entails investigating a recent paper and both reproducing and extending the research.

Yelin Kim wins Best Student Paper Award at ACM Multimedia 2014 for research in facial emotion recognition

She computationally measures, represents, and analyzes human behavior data to illuminate fundamental human behavior and emotion perception, and develop natural human-machine interfaces.

Raj Nadakuditi awarded DARPA Young Faculty Award for research that could help reveal the brain’s secrets

His research will impact the ability to investigate the structure of brain circuits through the use of optical imaging techniques.

Fighting lung cancer: Faster image processing for low-radiation CT scans

This advance could be important for fighting lung cancers, as symptoms often appear too late for effective treatment.

Chia-Hsiang Chen awarded Intel PhD Fellowship

Chia-Hsiang’s research focuses on designing low-power and error-resilient circuit techniques for digital signal processing applications.

Student Spotlight: Nick Asendorf – Matrix Musician

Nick specializes in the area of machine learning and statistical signal processing.

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.”

Hao Sun earns 3 Paper Awards for medical imaging research

Hao’s research is focused on improving the quality of images from magnetic resonance imaging pulse design.

Mai Le receives CoE Distinguished Leadership Award

Mai has served as Community Service Co-chair of the Graduate Society of Women Engineers since arriving at Michigan in 2011.

Student Spotlight: Mai Le – Finding a better way to diagnose breast cancer with MRI

The research group is using statistical signal processing to create crisper images with only 20% of the data required by a traditional MRI scan.

David Hong awarded NSF Graduate Research Fellowship

Hong intends to apply machine learning and signal processing techniques to the massive data sets now available to researchers.

Gopal Nataraj earns Best Paper Award for improving MRI

Nataraj is using big data techniques to transform the field of medical imaging

Gopal Nataraj receives ISA Fellowship to support research that will improve MRIs

Nataraj’s research aims to generate higher-quality and faster MRI images, resulting in improved diagnostics of neurological disorders and autoimmune diseases.

Zhaoshi Meng receives Best Paper Award at CAMSAP 2013

This work will provide a way to efficiently reveal relationships between even distant entities in a network.

Al Hero named 2013 IEEE SPS Technical Achievement Award Winner

Prof. Hero is an internationally recognized expert in the field of signal and image processing.

Pin-Yu Chen receives Rackham Chia-Lun Lo Fellowship

Chen’s work can be used in community detection in social networks, network vulnerability assessment in communication systems, and more.

Jeff Fessler receives 2013 IEEE Edward J. Hoffman Medical Imaging Scientist Award

This award recognizes outstanding contributions to the field of medical imaging science.

Research that will lead to sharper photos earns best paper award

The method they developed compares favorably with the best of current techniques, while being faster and easier.

Jae Young Park receives Best Student Paper Award for research impacting structural health monitoring

SHM systems are critical for monitoring aging structures and infrastructure in a cost-effective manner.

Research in distributed networks earns Notable Paper Award at AISTATS

The research provides a way to efficiently reveal relationships between even distant entities in a network.

Predicting your risk of illness

Imagine a future when you could predict whether or not you are at risk of becoming sick.

New technology allows CT scans to be done with a fraction of the conventional radiation dose

“We’re excited to be adding Veo to the measures we already have in place to ensure that we get diagnostic images using the lowest amount of radiation possible.”

Breakthrough: Researchers find wide gap in immune responses of people who did or didnt get the flu after exposure

If scientists can understand what happens at the genome level that makes people more or less susceptible to viral illness, they could potentially develop therapies to prevent illness.

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.

Gyemin Lee receives Best Paper Award for research in machine learning for biomedical diagnosis

Lee’s primary motivation is to apply his research methods to hematopathology, the study of blood-related diseases.

U-M researchers win 2010 Signal Processing Best Paper Award

The work, published in 2006, will be acknowledged at the EUSIPCO Conference in Denmark.

Al Hero receives 2009 Signal Processing Magazine Best Paper Award

The paper addresses the importance of knowing where networks of sensors are located once they’ve been deployed.

Clay Scott Receives CAREER Award for Research in Signal Processing

Yong Long receives Best Poster Award for work in medical imaging

Long’s work describes a new algorithm for performing model-based methods in a way that requires less computation yet provides improved image quality.