Team devising methods to make computer chips more energy efficient, sustainable
A Mizzou Engineering team is devising a method to make computer chips designed to run deep neural networks (DNNs) not only reliable, but also energy efficient and sustainable.
Mizzou Engineer secures NSF grant to increase computational storage at MU
A Mizzou Engineer is leading an interdisciplinary project that will provide a large-scale storage solution for the thousands of images being generated daily and will leverage artificial intelligence to help researchers analyze the data they collect.
Longtime AI researcher stays grounded as new bots turn field upside down
Generative artificial intelligence (AI) systems such as ChatGPT can provide a lot of convincing answers to user queries. What these models can’t do so well is explain how they derived their result and how confident they are in the output. And large language models (LLMs) aren’t the only machines making decisions that impact us. Professor Derek Anderson has been studying complex issues around AI for 20 years.
Mizzou Engineering team develops video retrieval system based on captioning
t’s not hard to search for a cute cat video on the internet. But if you want to find a video of a cat chasing a dog down a street on a sunny day, it gets trickier. Now, a Mizzou Engineering team has developed a novel system that relies on image captioning to find video clips of specific objects and scenes.
AI software can predict ‘roadmap’ for protein location, biological discoveries
Recently, Dong Xu, Curators' Distinguished Professor in the Department of Electrical Engineering and Computer Science at the University of Missouri, and colleagues updated their protein localization prediction model, MULocDeep, with the ability to provide more targeted predictions, including specific models for animals, humans and plants.
Cheng developing software to predict protein function using generative AI
A Mizzou Engineer has received funding from the National Science Foundation to develop a tool that will predict how a protein functions based on its order of amino acids. Jianlin “Jack” Cheng envisions developing open source software that would allow a user to enter the sequence, then the system would predict not only how that string of amino acids will form into a structure but also the role it will carry out within a cell. Additionally, the system would pinpoint the specific site of the protein that carries out the function.
Mizzou Engineer helping develop badging system for open source software
A Mizzou Engineer is helping develop a new badging system that will give those in the open source software community an easy way to gauge a project’s diversity, equity and inclusivity.
Team develops technique to segment carbon nanotube forests in images
Mizzou Engineering researchers are another step closer to controlling the properties of carbon nanotubes growing in mass quantities.
Calyam, collaborators using AI to assist local news organizations
Each day, local newsrooms across the United States are inundated with a myriad of press releases and story pitches competing for attention from a staff already strapped for time. Prasad Calyam, a professor of electrical engineering and computer science, and his team are among an elite group of researchers working to integrate automation and artificial intelligence to help local news organizations solve this challenge and others.
Mizzou Engineer lends protein prediction expertise to climate change studies at Danforth Plant Science Center
An inter-institutional research team is using the power of computational analysis to pinpoint which plant genes confer resilience against rising temperatures that threaten global food supplies in the coming decades. Mizzou Engineering Professor Jianlin “Jack” Cheng — one of the first scientists in the world to use deep learning, a powerful artificial intelligence technique, to predict protein structures — adds a unique perspective to the work. Since 2018, he’s been collaborating with Dr. Ru Zhang, a plant scientist at the Danforth Plant Science Center in St. Louis, to leverage computational tools in the study of plant genes.