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Kickstarter for Buddie: open source, AI-enabled earbuds

Collaborating faculty at the University of Michigan and Fudan University are crowdfunding a new wearable AI audio interface to enable always-listening context awareness, improve privacy, and allow AI application developers to try new ideas.

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.
Laser Focus World: September 30, 2024

OptoGPT harnesses AI to automate, speed design of optical structures

An optics-based machine-learning framework developed by ECE Prof. Jay Guo could be a game-changer in the push to design more advanced devices.
PV Magazine: July 29, 2024

US engineers develop ChatGPT algorithm to design solar cells

OptoGPT is a new algorithm that harnesses the computer architecture underpinning ChatGPT. L. Jay Guo, ECE professor, says that it will enable researchers and engineers to design optical multilayer film structures for a wide range of applications, including solar cells.

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.

Rada Mihalcea receives Distinguished Faculty Achievement Award

Mihalcea is being recognized for her contributions to computational linguistics and her efforts to broaden participation in the field of computer science.

Paper by U-M researchers selected for Best Paper in IEEE Transactions on Affective Computing

The research on automatic speech emotion recognition is one of the five papers featured in the collection.
Technovation: May 5, 2020

5 Women You Should Know Working in AI

Rada Mihalcea, the Janice M. Jenkins Collegiate Professor of Computer Science and Engineering and Director of the U-M AI Lab, is featured for her work in computational sociolinguistics.

Student awarded NSF Fellowship for automating speech-based disease classification

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

Paper award for identifying speaker characteristics in text messages

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

Gaining a deeper understanding of how personal values are expressed in text

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

Detecting Huntington’s disease with an algorithm that analyzes speech

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

Fake news detector algorithm works better than a human

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

Chat tool simplifies tricky online privacy policies

Automated chatbot uses artificial intelligence to weed through fine print

Emotions predicted by examining the correlation between tweets and environmental factors

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.

Improving natural language processing with demographic-aware models

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

Rada Mihalcea co-authors new book on text mining

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

U-M, IBM partner on advanced conversational computing system

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

Lie-detecting software uses real court case data

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