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Workshop organizers believe a key strategy to increasing the number of women in computing research is to introduce them to the research process early on.

PhD student Emily Sheetz is working to design more dexterous robots to work alongside humans in space.

The project enables neural networks to model how people are positioned based on only partial views of their bodies, like perspective shots in instructional videos or vlogs.

The Rising Star Award is based on an individual’s whole body of work in the first five years after the PhD.

Discover Computer Science provides a basic background in all the skills a student needs to pursue further education in computing.

A Q&A with Chad Jenkins.

The model is a practical method for robots to look for target items in complex, realistic environments.

The virtual interviewer uses therapeutic writing techniques to help users cope with difficult situations.

The system can add more flexibility to task management apps to help learning users make informed decisions about their time.

The project, which received a best paper award, demonstrated that a certain bias in humans who train intelligent agents significantly reduced the effectiveness of the training.

Mihalcea specializes in identifying the underlying emotions, beliefs, and values expressed in written text, and using that to draw inferences about the meaning of the text and certain characteristics of the writer.

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

Mower Provost talks about getting awards, doing industry research, understanding human behavior – and Star Wars.

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

Her work uses machine learning to measure mood, emotion, and other aspects of human behavior for purposes of providing early or real-time interventions for people in managing their health.

The nine students represent a broad range of research areas in the department.

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.

Researchers have demonstrated the ability to “unlearn” sensitive identifying data from audio used to train machine learning models.

A team at Michigan proposed an approach to generating realistic and high-fidelity stock market data to enable broader study of financial markets.

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

This award is the highest honor awarded to a faculty member by the College.

The ARC works to solve a broad set of issues pertaining to the modeling and simulation of ground vehicle systems.

For “exemplifying the leadership and vision of Dr. King,” four CSE students and faculty were honored as part of U-M’s annual MLK symposium.

This round of funding strongly encourages pioneering work with the potential for major expansion.

Mihalcea is recognized for her outstanding research on natural language processing.

Koutra specializes in advancing network methods to speed up a variety of big data applications.

The panel covered a number of challenges to expect working as a computer scientist, and the skills they found necessary to overcome them.

Jenkins was recognized for his work on human-robot interaction and methods that enable robots to learn human skills.

The CSE faculty include Prof. David Fouhey, Prof. Danai Koutra, Prof. Rada Mihalcea, and Research Scientist Veronica Perez-Rosas.

Comparing graphs the team’s tool is up to an order of magnitude faster than competitive baselines.

The workshop brings together outstanding women interested in pursuing academic careers in electrical engineering and computer science.

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

Nominees were selected based on their career accomplishments, impact in their field, and contributions to their community.

Pennock’s research is focused on designing intelligent markets to crowdsource forecasts and improve decision making.

The new additions to the department offer a breadth of research and educational experience, with projects spanning robotic interaction and the future of programming languages.

May Mobility intends to gradually acclimate the public to the experience of autonomous driving.

The goal of Lasecki’s proposal is to create methods for making AI systems more robust and flexible.

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.

Baveja’s paper tackled the difficult problem of giving artificial intelligence a way to understand and represent knowledge collected over time.

New algorithm can help robots go from structured environments like factories to complex, unstructured places like our homes.

Danai Koutra earned the award for her proposal to innovate the way we use networks to understand the world and speed up our technology.

Jenkins has been appointed as one of seven new members on the Computing Community Consortium (CCC) Council, which is affiliated with the Computing Research Association (CRA). His term begins July 1.

Perez’s research focuses on analyzing speech patterns of patients with Huntington Disease.

Burdick has done extensive work as an instructor in EECS courses and promoter of diversity in the department.

The goal of the work was to identify seven things about who the subject was talking to just by analyzing text messages.

Danai Koutra has earned an Army Young Investigator Award to speed up graph methods for distributed applications.

Graphs that are customized, stored locally, and able to change over time can enable faster and more accurate searching and digital assistants

Congratulations to these recipients of the EECS Outstanding Achievement Award

“What I’m doing is trying to come up with ideas to let the agent continue learning different skills across its life.”

Mihalcea has dedicated substantial effort to developing programs aimed at introducing women to the world of computing

Laird has been an energetic contributor to AI and cognitive science for over 30 years

The Michigan AI Lab at CSE celebrated 30 years of leading research with its first annual AI Symposium, AI for Society.

The result will be new measurement methods to determine how moods are shaped by both the behavior of an individual and daily interactions over time

The new $2.5 million endowment to support a professorship is the second U-M sponsorship from Toyota

The papers provide data-driven solutions to hospital infection and the use of machine learning in healthcare.

A Q&A with machine learning expert Emily Mower Provost.

Researchers used hierarchical trees to provide a better idea of how concepts are represented and related in a collection of text.

“We are trying to change the stereotypes.”

As part of a celebration of the film’s 50th anniversary, leading researchers discussed artificial intelligence and deep space travel.

New, preliminary research found automated speech test accurately diagnoses Huntington’s disease 81 percent of the time and tracks the disease’s progression.

Jonathan Kummerfeld is recognized for his work in artificial intelligence, with a particular focus on language.

Mihalcea and Wendlandt believe a key strategy to increasing the number of women in computing research is to introduce them to the research process early on.

System sniffs out fakes up to 76 percent of the time.

The most exciting use of AI for me focuses around a better collective use of our available resources, says Corso.

Carvalho plans to pursue research at the intersection of reinforcement learning, machine learning, and computational cognitive science.

Rada Mihalcea is a rock star professor of Electrical Engineering and Computer Science at U-M’s College of Engineering and a champion for the growth and retention of women in that field.

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.

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.

Aldeneh’s research focuses on identifying the features of speech that make human interaction feel natural.

Profs. Jia Deng, Roya Ensafi, and Manos Kapritsos have been selected to receive Google Faculty Research Awards.

Xinchen Yan was selected for both fellowships to support his research in machine learning and its application in computer vision, graphics and robotics.

Tara Safavi’s research focuses on scalable and adaptive data mining algorithms using tools like hashing and sampling.

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

Other investors include Detroit Venture Partners, Maven Ventures, SV Angel, Tandem Ventures, Trucks Ventures, and YCombinator.

The award is for papers that present ideas and visions that can stimulate the research community to pursue new directions, such as new problems, new application domains, or new methodologies.

Prof. Deng was selected for his work in computer vision and machine learning.

The debate was held at the American Museum of Natural History and was hosted by Neil deGrasse Tyson.

External factors, ranging from weather, news exposure, social network emotion charge, timing, and mood predisposition may have a bearing on one’s emotion level throughout the day.

The award recognizes his significant and consequential contributions in service to the academy and his professional communities.

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

Increasingly, market manipulators are attacking market integrity through complex computer-controlled attacks.

Word associations vary across different demographics, allowing researchers to build better natural language processing models if they can account for demographics.

With Codeon, developers can request help by speaking their requests aloud within the context of their Integrated Development Environment (IDE).

Kurator is a hybrid intelligence system leveraging mixed-expertise crowds to help families curate their personal digital content, including videos and photos.

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

Jenkins hopes to cultivate new and leading-edge ideas in both robotics and the human-centered sciences.

Lee Rutledge, CSE graduate student, is working at U-M’s autonomous robotics lab this fall to help AI agents map and navigate their surroundings on the fly.

Michael Wellman, a U-M Engineering professor, recently took part in a workshop to anticipate and prevent possible adverse outcomes of artificial intelligence.

Prof. Mower Provost’s research interests are in human-centered speech and video processing, multimodal interfaces design, and speech-based assistive technology.

Professor Wellman brings expertise on algorithmic trading and other computational techniques that are transforming financial markets and the financial system.

Researchers at the University of Michigan have developed an algorithm that can analyze and measure the amount that one candidate linguistically matches their opponent and have found that matching your opponent in a debate leads to higher polling numbers.

This project aims to improve goal-directed dexterous robotic manipulation in cluttered and unstructured environments.

Vulcan, the intelligent robotic wheelchair, aims to help the elderly and those with disabilities effortlessly move around their environment.

Cogitai was formed with the aim of developing AI technology that empowers machines to learn from interaction with the real world.

The annual SIGKDD doctoral dissertation award recognizes excellent research by doctoral candidates in the field of data mining and knowledge discovery.

A frequent call market may help prevent ‘flash crashes.’

This innovative software guides users through the process of collecting a set of images of a calibration target.

Prof. Emily Mower Provost is collaborating to develop new technologies that provide individuals with insight into how the disease changes over time.

Text Mining brings together a broad range of contemporary qualitative and quantitative methods to provide strategic and practical guidance on analyzing large text collections.

The award is to support his research in reinforcement learning.

Prof. Wellman’s research applies principles of computation and economics to engineer rational decision-making strategies and analyze complex systems of interacting agents.

The paper explores how automated speech recognition and crowd-sourced human correction and generation of transcripts can be traded off to improve accuracy and latency.

Yu-Wei is a third year PhD student whose research focuses on computer vision and machine learning.

Prof. Wiens will continue to use machine learning techniques to study the disease.

The team used machine learning to extract information from NBA sports data for automatically recognizing common defense strategies to ball screens.

His work impacts computer vision, audio recognition, robotics, text modeling, and healthcare.

Her primary research interests lie at the intersection of machine learning and healthcare.

The project aims to develop a cognitive system that functions as an academic advisor for undergraduate computer science and engineering majors at the university.

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

The solution Ford and U-M are working on involves high-resolution 3D maps. U-M researchers have developed these maps and Ford’s test vehicles are equipped with them.

U-M researchers are building a unique lie-detecting software that works from studying real world data from real, high-stakes court cases.

His research takes place at the intersection of information retrieval, natural language processing, machine learning, bioinformatics, text and data mining, social networks, social media, collective behavior, text generation, information extraction, and artificial intelligence.

Fairy doors have been sighted around town for a number of years, with the fairies apparently choosing iconic Ann Arbor landmarks in which to site their homes.

The scope of the project consists of a number of thrusts including a key research collaboration led by Profs. Edwin Olson and Ryan Eustice, who are playing a leading role in the development of the critical sensing and decision-making found in the Ford test vehicles.

The research outcomes will be distributed through publications, talks, and tutorials.

In their study, the researchers took a computational approach to studying the contest to gain insights into what differentiates funny captions from the rest.

Over the next year, U-M researchers will develop autonomy capabilities and build a mobile phone interface users can use to request a ride.

The proposed work investigates computational methodologies to differentiate emotion perception patterns of healthy controls and individuals with Major Depressive Disorder or Bipolar Disorder.

Abernethy’s research is in machine learning, with additional interests in game theory, decision theory, optimization, market mechanism design, and other financial applications.

Prof. Corso believes that this research could make it easier to search for certain types of videos on the web.

Prof. Deng’s primary research interest is in the area of computer vision, with a focus on image and video understanding, human computation, and large-scale machine learning.

Winners are chosen for their outstanding accomplishments in teaching, research, and service.

Congratulations to the following CSE Faculty recipients of 2014-15 College of Engineering Awards.

Prof. Mihalcea’s research interests are in computational linguistics, with a focus on lexical semantics, graph-based algorithms for natural language processing, and multilingual natural language processing.

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

The goal of the research is to revolutionize how Municipal Solid Waste (MSW) is managed to provide a transformative means of extracting utility-scale energy from waste.

Deng’s research in computer vision focuses on image and video understanding through big visual data, human computation, and large-scale machine learning.

Congratulations to these amazing faculty members!