news 2020

Carnegie Mellon method foregoes expensive scanners, camera setups, studios Normally, it takes pricey equipment and expertise to create an accurate 3D reconstruction of someone's face that's realistic and doesn't look creepy. Now, Carnegie Mellon University researchers have pulled off the feat using video recorded on an ordinary smartphone.

Traditional methods for predicting interactions between proteins and other molecules rely on complex supercomputer simulations. Instead, a group of researchers from EPFL and USI developed a new artificial intelligence system that analyzes the 3D structure of protein surfaces. The new method MaSIF (Molecular Surface Interaction Fingerprinting) is a collaboration between the EPFL Protein Design & Immunoengineering lab (headed by Prof. Bruno Correia) and the group of Michael Bronstein , professor at USI and Imperial College of London, and head of research in Graph Learning at Twitter.

By Birgit Baustädter Oswin Aichholzer does basic research - he doesn't invent, he discovers. The theoretical computer scientist is on the trail of basic mathematical rules which he can model and teach the computer. Oswin Aichholzer is wearing a light blue pullover, has a headset on, and is sitting in front of the computer.

A Covid-19 taskforce examines a map of the virus' spread. PHOTO CREDIT: Carlos Barria Reuters Experts offer Insights on mapping and forecasting virus cases during Stanford HAI's COVID-19 and AI Conference. Estimating unreported COVID-19 infections with viral-genome data. Automating contract-tracing with Bluetooth technology. Analyzing Twitter for mental-health impacts.

Researchers have designed a machine learning method that can predict battery health with 10x higher accuracy than current industry standard, which could aid in the development of safer and more reliable batteries for electric vehicles and consumer electronics. The researchers, from Cambridge and Newcastle Universities, have designed a new way to monitor batteries by sending electrical pulses into them and measuring the response.

The Neue Zürcher Zeitung recently published a paper on the ethical challenges of digitisation written by Peter Seele, economist, philosopher and professor of business ethics at USI Faculty of Communication, Culture and Society and Dirk Helbing, professor of Computational Social Science at ETH Zurich.

Life science companies use Paradigm4's unique database management system to uncover new insights into human health. As technologies like single-cell genomic sequencing, enhanced biomedical imaging, and medical "internet of things" devices proliferate, key discoveries about human health are increasingly found within vast troves of complex life science and health data.

FACULTY Q&A A federal court has cleared the way for academic researchers, computer scientists and journalists to continue work that investigates online company practices for racial, gender or other discrimination. The ruling means that those who research online companies no longer have to fear prosecution for the work they do to hold tech companies accountable for their practices, said Christian Sandvig , the H Marshall McLuhan Collegiate Professor of Digital Media, professor of information and director of the Center for Ethics, Society, and Computing at the University of Michigan.

Researchers combine power of wearable device and big data analytics to track spread and early signs of infection—including among healthcare workers T o better understand early signs of coronavirus and the virus' spread, physicians around the country and data scientists at UC San Diego are working together to use a wearable device to monitor more than 12,000 people, including thousands of healthcare workers.

The MedCo system aims to facilitate medical research on pathologies - such as cancer and infectious diseases - by enabling secure computations on decentralized data. The unique software has recently been deployed at three Swiss hospitals. MedCo was first released in 2019 as the first operational system to protect sensitive patient data so that it can be used collectively for medical research.

By Christoph Pelzl Researchers at Graz University of Technology have successfully tested a cost-effective and fully automated pollen sensor prototype and are now making their knowledge freely available and usable for everyone. Additional at the end of the text Pollen: essential for the pollination of many plants, but the bane of allergy sufferers.

A new study from a University of Michigan researcher and colleagues at three institutions demonstrates the potential for using existing networks of buried optical fibers as an inexpensive observatory for monitoring and studying earthquakes. The study provides new evidence that the same optical fibers that deliver high-speed internet and HD video to our homes could one day double as seismic sensors.

By Christoph Pelzl The data analyses of Invenium, a spin-off of Graz University of Technology and the Graz Know Center, help companies to better understand the mobility behaviour of people - and not only in times of the corona crisis. There is an enormous amount of scientific potential in anonymized mobile phone data - as Invenium co-founder Michael Cik recognised as early as 2013.

A team of researchers from the COSIC research group at KU Leuven and from the University of Birmingham has discovered that a wide range of car models produced by Toyota, Kia and Hyundai use weak cryptographic keys. This makes it easy to clone the key fob transponder. It is likely that millions of cars are affected.

Pandemic response requires "dull, dirty, dangerous" jobs suited for robots Robots could perform some of the "dull, dirty and dangerous" jobs associated with combating the COVID-19 pandemic, but that would require many new capabilities not currently being funded or developed, an editorial Robotics argues.

FACULTY Q&A Liang Qi , a professor of materials science and engineering at the University of Michigan, answered questions about his group's new paper in npj Computational Materials. What is elastic stiffness' Elastic and glass don't seem to be two words that go together. All solid materials, including glass, have a property called elastic stiffness-also known as elastic modulus.

The disparity likely occurs because such technologies are based on machine learning systems that rely heavily on databases of English as spoken by white Americans. The technology that powers the nation's leading automated speech recognition systems makes twice as many errors when interpreting words spoken by African Americans as when interpreting the same words spoken by whites, according to a new study by researchers at Stanford Engineering.

Using a novel type of cameras, researchers from the University of Zurich have demonstrated a flying robot that can detect and avoid fast-moving objects. A step towards drones that can fly faster in harsh environments, accomplishing more in less time. Drones can do many things, but avoiding obstacles is not their strongest suit yet - especially when they move quickly.

With the help of machine learning, ETH researchers have developed a novel yet low-cost tactile sensor. The sensor measures force distribution at high resolution and with great accuracy, enabling robot arms to grasp sensitive or fragile objects. We humans have no problem picking up fragile or slippery objects with our hands.

A new imaging method combined with machine learning uncovers previously hidden information in micrographs of biological cells to reveal quantitative information of gene expression levels. Researchers from the University of Glasgow's James Watt School of Engineering and School of Computing Science describe in a paper published today how they have used image analysis and machine learning as a tool to directly determine the gene activity in single cells.