A team of undergraduate students from the cybersecurity club in UCI’s Department of Computer Science is moving on to the National Collegiate Cyber Defense Competition following their recent first-place finish in the Western Regionals against several formidable opponents. Only the winners out of the nine regionals across the nation can directly advance to the national competition.[Read more…]
UCI researchers have harnessed digital technology and deep-learning neural networks to develop a next-generation eye prosthetic that can match the pupil movements of the natural eye.
Read the full story at UCI Health.
Many people who experience long-term symptoms from the coronavirus did not feel sick at all when they were initially infected, according to a new study that adds compelling information to the increasingly important issue of the lasting health impact of Covid-19.
Read the full article at The New York Times.
Interdisciplinary group to combine research, clinical care to empower people[Read more…]
Deep learning, a family of machine-learning methods based on artificial neural networks, has revolutionized applications such as image interpretation, natural language processing and autonomous driving. In a study published recently in Science Advances, UCI researchers describe how the technique can also be successfully used to observe gene regulation at the cellular level. Until now, that process had been limited to tissue-level analysis.[Read more…]
IEEE Computer Society (IEEE CS) announces that 51 IEEE CS members and 17 IEEE members evaluated by the IEEE CS Fellow Evaluation Committee will be elevated to IEEE Fellow grade in 2021. The grade of Fellow recognizes unusual distinction in the profession.[Read more…]
Sameer’s work centers on large-scale and interpretable machine learning applied to information extraction and natural language processing. We caught up with Sameer right after he was awarded the best paper award at ACL 2020 for his work on Beyond Accuracy: Behavioral Testing of NLP Models with CheckList. In our conversation, we explore CheckLists, the task-agnostic methodology for testing NLP models introduced in the paper. We also discuss how well we understand the cause of pitfalls or failure modes in deep learning models, Sameer’s thoughts on embodied AI, and his work on the now famous LIME paper, which he co-authored alongside Carlos Guestrin.
Listen below or at the TWIML AI Podcast.
At the University of California, Irvine, campus managers will keep an eye on how crowded buildings are, using a system that has been under development for years with a grant from the US Defense Advanced Research Projects Agency. As students’ phones and laptops search for Wi-Fi signals in buildings, they generate ‘probe events’ that will be used to estimate how many people are in each area.
Read the full story at Nature.
At the University of California, Irvine, a team of researchers is hoping to put those [privacy] concerns to rest by developing a web-based app that uses data the school already collects. Instead of requiring students and employees to turn over troves of personal information, the system works by tracking the number of devices connected to the campus Wi-Fi. To avoid overcounting people, it uses machine learning techniques to determine if two or more devices are moving together, suggesting they belong to the same person.
Read the full story at Education Dive.