Data Science, AI & Machine Learning
Data Science, artificial intelligence (AI) and machine learning involve making accurate predictions, data mining, machine learning, and more to guide business decisions. Research areas include: bio inspired control using data from animals, computational biology, computational imaging, cyber security, medical informatics, simulation, and video analytics.
Mark Crovella: Mapping the Internet in a New Age of Privacy
You can’t see it, but when you enter something in the search bar, there is a whole network of connections that happens. We typically don’t think about the internet having a map, but CISE faculty affiliate Mark Crovella, a founding member and faculty of Computing & Data Sciences, likened his work to figuring out what […]
Pregnancy Models Give Birth to New Health Insights
Having a baby is a life-changing decision that often requires a great deal of time and energy to ensure a positive outcome. But the cost of assisted reproductive technologies like artificial insemination or in-vitro fertilization (IVF) and the emotional impacts of infertility can be a lot to bear. To try to improve the chances of […]
Wenchao Li: Building Safe and Trustworthy AI Systems
Artificial intelligence (AI) is everywhere, powering applications such as Spotify music suggestions, facial recognition from your smartphone or the ETA of your Uber. Neural networks are also being explored as controllers in a breadth of safety-critical systems, from piloting drones to detecting anomalies in nuclear power plants to maintaining first responder communication systems. At the […]
IRS Stares Technological Advancement Issues in the Face
Almost every American is used to sharing information with the Internal Revenue Service (IRS), but people were about to become eerily intimate with the agency after they announced the launch of a new website requirement: live video identity verification. The agency partnered with the third-party company ID.me to prevent scammers from benefiting off of the […]
Lighting the Way Forward for Autonomous Vehicles
CISE Faculty Affiliate Ajay Joshi with collaborators at Lightmatter and Harvard University receive $4.8M IARPA grant to develop a new Electro-Photonic Computing (EPiC) system for AI-based navigation in Autonomous Vehicles Anyone who has ever been behind the wheel of a car knows that response time is crucial. The human sensory system needs to be fully engaged in order […]
Machine learning reveals new factor for predicting a stroke survivor’s ability to regain language skills
Despite centuries of study, the human brain remains one of science’s greatest mysteries. Most research focuses on how the brain responds to change, but researchers are beginning to shift from studying the effect of the brain injury to recovery and healing. Neuroscientists and computer scientists at Boston University (BU) teamed up to create a method […]
CISE Faculty Spotlight: Brian Kulis
The powers of machine learning in Amazon Alexa and music generation Every day millions of people look something up online. It’s become a habit, a part of our lives that we take for granted– and we can thank machine learning for that. Machine learning is a type of artificial intelligence that works with computer algorithms. […]
Faculty Spotlight: Alex Olshevsky
Easing the Economic Strain of COVID-19 Lockdowns At the start of the pandemic, CISE Faculty Affiliate Alex Olshevsky (ECE) started developing models to find the best way to lockdown regions to control the spread of the virus. He had previously been working on multi-agent control, which he described as “a collection of robots that want […]
SHF: Small: Architecting the COSMOS:A Combined System of Optical Phase Change Memory and Optical Links
Today’s data-intensive applications that use graph processing, machine learning or privacy-preserving paradigms demand memory sizes on the order of hundreds of GigaBytes and bandwidths on the order of TeraBytes per second. To support the ever-growing memory needs of the applications, Dynamic Random Access Memory (DRAM) systems have evolved over the decades. However, DRAM will not […]
High-Fidelity Self-Learning Tool for Residential Load and Load Flexibility Forecasting
The project will research, develop, and demonstrate technology that enables the modulation of controllable household loads, to provide multiple grid services, including peak capacity management, ramp support, and frequency regulation. We will show how the fusion of data from multiple sources, including communicating thermostats, smart appliances, weather forecasts, utility bills, solar production data, and interval […]