Home > News > All News > Jenna Wiens

Jenna Wiens

Seventeen papers by CSE researchers at NeurIPS 2024

Papers by CSE authors cover a variety of topics related to machine learning and neural information processing.

Accounting for bias in medical data helps prevent AI from amplifying racial disparity

Some sick Black patients are likely labeled as “healthy” in AI datasets due to inequitable medical testing.

These CSE PhD alums have accepted faculty positions

Congrats to these new faculty!

Widely used AI tool for early sepsis detection may be cribbing doctors’ suspicions

When using only data collected before patients with sepsis received treatments or medical tests, the model’s accuracy was no better than a coin toss.

Clinicians could be fooled by biased AI, despite explanations

Regulators pinned their hopes on clinicians being able to spot flaws in explanations of an AI model's logic, but a study suggests this isn't a safe approach.

Fourteen papers by CSE researchers presented at NeurIPS 2023

CSE authors are presenting new research in the area of machine learning and neural networks.

Jenna Wiens honored with Humboldt Foundation Research Award

The award recognizes her career achievements in artificial intelligence and machine learning and will support her continued collaboration with colleagues in Germany.

Sarah Jabbour selected for CSE HACKS Spirit Award

Through her contributions, Sarah embodies the values that are central to who CSE is as a community.

Jenna Wiens receives U-M Sarah Goddard Power Award for outstanding research and advocacy for women in academia

The award recognizes U-M faculty and staff who have significantly contributed to the betterment of current challenges faced by women.

“It’s a supportive and collaborative environment” — making connections as a PhD student in and outside the classroom

U-M CSE PhD candidate Sarah Jabbour discusses how collaboration is centered in her experience as a graduate student.

Decisive differences in healthcare AI

When decisions about your healthcare are informed by AI, bias in machine learning can have dire consequences. Ph.D. student Trenton Chang researches how inequities in healthcare delivery impact machine learning and AI.

Open-source patient model tops industry standard

Tested without needing hospitals to share data, the method for developing the model could speed further improvements in medical prediction tools

$1.1M grant supports learning more about early Alzheimer's with machine learning

Data from patient records could provide a valuable historical perspective on which factors increase Alzheimer's risk.

Seven papers by CSE researchers presented at AAAI 2021

Twelve students and faculty co-authored papers spanning several key application areas for AI.

Precision health in the palm of your hand

Recent breakthrough developments in technologies for real-time genome sequencing, analysis, and diagnosis are poised to deliver a new standard of personalized care.

Faster than COVID: a computer model that predicts the disease’s next move

Predictive model could help care providers stay safe, anticipate patient needs.

Computer scientists employ AI to help address COVID-19 challenges

Five multidisciplinary research teams are working on projects to assist with the coronavirus outbreak and to help find solutions to pressing problems.

Jenna Wiens recognized with Sloan Research Fellowship

She was recognized for her work harnessing patient data to improve healthcare outcomes.

2020 EECS Outstanding Achievement Awards

EECS honors four faculty members for their outstanding accomplishments to the community.

Michigan AI celebrates second annual symposium

The goal of the symposium is to facilitate conversations between AI practitioners from Michigan and beyond.

Taking machine-learning models in health care from concept to bedside

The authors provide an overview of common challenges to implementing ML in a health-care setting, and describe the necessity of breaking down the silos in ML.

Jenna Wiens Named New Precision Health Co-Director

Wiens is transitioning to Co-Director from a successful role as a Co-Lead for Precision Health’s Data Analytics & IT Workgroup, which expanded access to data and research tools across the university.

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.

Preventing deadly hospital infections with machine learning

Model successfully applied to data from medical centers with different patient populations, electronic health record systems

Jenna Wiens named Morris Wellman Faculty Development Professor

This professorship is awarded to junior faculty members in CSE in recognition of outstanding contributions to teaching and research.

CS kickStart wants first-year women to succeed in computer science

CS KickStart is a free week long summer program for incoming first-year students that aims to improve the enrollment and persistence of women in U-M’s computer science program.

Precision health pioneer named to MIT Technology Review innovator list

The national magazine recognized Jenna Wiens as one of 2017’s 35 Innovators Under 35.

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.

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.

Two new faculty join CSE in fall 2014