Rutgers Computer Scientist Named Sloan Fellow

A Rutgers professor who studies and improves the design of algorithms – human-made instructions computers follow to solve problems and perform computations – has been selected to receive a 2024 Sloan Research Fellowship.

Aaron Bernstein, an assistant professor in the Department of Computer Science in the School of Arts and Sciences at Rutgers University-New Brunswick, was named one of 126 researchers drawn from a select group of 53 institutions in the U.S. and Canada.

Shuffling the deck for privacy

By integrating an ensemble of privacy-preserving algorithms, a KAUST research team has developed a machine-learning approach that addresses a significant challenge in medical research: How to use the power of artificial intelligence (AI) to accelerate discovery from genomic data while protecting the privacy of individuals

Is brain learning weaker than artificial Intelligence?

Can the brain, with its limited realization of precise mathematical operations, compete with advanced artificial intelligence systems implemented on fast and parallel computers? From our daily experience we know that for many tasks the answer is yes! Why is this and, given this affirmative answer, can one build a new type of efficient artificial intelligence inspired by the brain? In an article published today in Scientific Reports, researchers from Bar-Ilan University in Israel solve this puzzle.

Study shows how machine learning could predict rare disastrous events, like earthquakes or pandemics

When it comes to predicting disasters brought on by extreme events (think earthquakes, pandemics or “rogue waves” that could destroy coastal structures), computational modeling faces an almost insurmountable challenge: Statistically speaking, these events are so rare that there’s just not enough data on them to use predictive models to accurately forecast when they’ll happen next.

Ancient DNA Analysis Sheds Light on the Early Peopling of South America

Using DNA from two ancient humans unearthed in two different archaeological sites in northeast Brazil, researchers have unraveled the deep demographic history of South America at the regional level with some surprising results. Not only do they provide new genetic evidence supporting existing archaeological data of the north-to-south migration toward South America, they also have discovered migrations in the opposite direction along the Atlantic coast – for the first time. Among the key findings, they also have discovered evidence of Neanderthal ancestry within the genomes of ancient individuals from South America. Neanderthals ranged across Eurasia during the Lower and Middle Paleolithic. The Americas were the last continent to be inhabited by humans.

New brain learning mechanism calls for revision of long-held neuroscience hypothesis

In an article published today in Scientific Reports (https://www.nature.com/articles/s41598-022-10466-8), researchers from Bar-Ilan University in Israel reveal that the brain learns completely differently than has been assumed since the 20th century. The new experimental observations suggest that learning is mainly performed in neuronal dendritic trees, where the trunk and branches of the tree modify their strength, as opposed to modifying solely the strength of the synapses (dendritic leaves), as was previously thought. These observations also indicate that the neuron is actually a much more complex, dynamic and computational element than a binary element that can fire or not. Just one single neuron can realize deep learning algorithms, which previously required an artificial complex network consisting of thousands of connected neurons and synapses. The new demonstration of efficient learning on dendritic trees calls for new approaches in brain research, as well as for the generation

Novel Tag Provides First Detailed Look into Goliath Grouper Behavior

A study is the first to reveal detailed behavior of massive goliath groupers. Until now, no studies have documented their fine-scale behavior. What is known about them has been learned from divers, underwater video footage, and observing them in captivity. Using a multi-sensor tag with a three axis accelerometer, gyroscope and magnetometer as well as a temperature, pressure and light sensor, a video camera and a hydrophone, researchers show how this species navigates through complex artificial reef environments, maintain themselves in high current areas, and how much time they spend in different cracks and crevices – none of which would be possible without the tag.

COVID, CAMERAS and AI: the story of a pandemic drone

As the COVID-19 death toll mounts and the world hangs its hopes on effective vaccines, what else can we do to save lives in this pandemic? In UniSA’s case, design world-first technology that combines engineering, drones, cameras, and artificial intelligence to monitor people’s vital health signs remotely.

In 2020 the University of South Australia joined forces with the world’s oldest commercial drone manufacturer, Draganfly Inc, to develop technology which remotely detects the key symptoms of COVID-19 – breathing and heart rates, temperature, and blood oxygen levels.

Within months, the technology had moved from drones to security cameras and kiosks, scanning vital health signs in 15 seconds and adding social distancing software to the mix.

In September 2020, Alabama State University became the first higher education institution in the world to use the technology to spot COVID-19 symptoms in its staff and students and enforce social distancing, ensuring they had one of the l

New machine learning theory that can be applied to fusion energy raises questions about the very nature of science

A novel computer algorithm, or set of rules, that accurately predicts the orbits of planets in the solar system could be adapted to better predict and control the behavior of the plasma that fuels fusion facilities designed to harvest on Earth the fusion energy that powers the sun and stars.

5G Wireless May Lead to Inaccurate Weather Forecasts

Upcoming 5G wireless networks that will provide faster cell phone service may lead to inaccurate weather forecasts, according to a Rutgers study on a controversial issue that has created anxiety among meteorologists.

Rutgers Expert Can Discuss Artificial Intelligence and Art

New Brunswick, N.J. (June 1, 2020) – Rutgers University–New Brunswick Professor Ahmed Elgammal is available for interviews on the future of art and creativity in the age of artificial intelligence (A.I.). “As artificial intelligence becomes an increasing part of our…

ALGORITHMIC AUTOS

Connected and automated vehicles use technology such as sensors, cameras and advanced control algorithms to adjust their operation to changing conditions with little or no input from drivers. A research group at the University of Delaware optimized vehicle dynamics and powertrain operation using connectivity and automation, while developing and testing a control framework that reduced travel time and energy use in a connected and automated vehicle.

Algorithm tracker monitors Reddit rankings of COVID-19 posts

Since 2016, Cornell University assistant professor of communication J. Nathan Matias has tracked the algorithms on Reddit, a massive network of forums where people share content and news, and which claims to have more users than Twitter. As the coronavirus pandemic exploded, Matias began using the tool – called the COVID-19 Algo-Tracker – to monitor Reddit’s virus-related posts and threads, both to inform people about the mechanisms behind the information they’re receiving and to create a large, publicly available dataset for future research.

A Faster Way To Replace Inaccurate Information On Social Networks

Researchers have demonstrated a new model of how competing pieces of information spread in online social networks and the Internet of Things. The findings may be used to disseminate accurate information more quickly, displacing false information on anything from computer security to public health.

UCI and Disney Research scientists develop AI-enhanced video compression model

Irvine, Calif., Feb. 18, 2020 – A new artificial intelligence-enhanced video compression model developed by computer scientists at the University of California, Irvine and Disney Research has demonstrated that deep learning can compete against established video compression technology. Unveiling their work in December at the Conference on Neural Information Processing Systems in Vancouver, British Columbia, the UCI/Disney Research team members showed that their compressor – while still in an early phase – yielded less distortion and significantly smaller bits-per-pixel rates than classical coding-decoding algorithms such as H.

Weizmann Scientists Devise New Algorithm that Predicts Gestational Diabetes

Using machine learning to analyze data on nearly 600,000 pregnancies, researchers devised an algorithm that identified nine parameters – out of more than 2,000 analyzed – that can predict which women are at risk of gestational diabetes. The parameters can identify risk early in – even before – pregnancy, enabling early intervention.

Machine Learning Leads to Novel Way to Track Tremor Severity in Parkinson’s Patients

Physical exams only provide a snapshot of a Parkinson’s patient’s daily tremor experience. Scientists have developed algorithms that, combined with wearable sensors, can continuously monitor patients and estimate total Parkinsonian tremor as they perform a variety of free body movements in their natural settings. This new method holds great potential for providing a full spectrum of patients’ tremors and medication response, providing clinicians with key information to effectively manage and treat their patients with this disorder.