Toward a smarter electronic health record
An AI-enhanced system enables doctors to spend less time searching for clinical information and more time treating patients.
Making self-driving cars safer through keener robot perception
PhD student Heng Yang is developing algorithms to help driverless vehicles quickly and accurately assess their surroundings.
Q&A: Dina Katabi on a “smart” home with actual intelligence
MIT professor is designing the next generation of smart wireless devices that will sit in the background, gathering and interpreting data, rather than being worn on the body.
Using adversarial attacks to refine molecular energy predictions
MIT researchers find a new way to quantify the uncertainty in molecular energies predicted by neural networks.
360-degree transparency for construction sites made simple
Jeevan Kalanithi SM ’07 is CEO of OpenSpace, a company founded by three Media Lab graduates using computer vision to benefit the construction industry.
Jordan Harrod: Brain researcher and AI-focused YouTuber
The PhD student uses machine learning as a tool for studying pain and consciousness — and as subject matter for her popular videos.
Smart laser cutter system detects different materials
SensiCut, a smart material-sensing platform for laser cutters, can differentiate between 30 materials commonly found in makerspaces and workshops.
“AI for Impact” lives up to its name
Entrepreneurship class MAS.664 launches businesses with a global reach.
Machine learning discovers new sequences to boost drug delivery
MIT researchers employ machine learning to find powerful peptides that could improve a gene therapy drug for Duchenne muscular dystrophy.
System trains drones to fly around obstacles at high speeds
New algorithm could enable fast, nimble drones for time-critical operations such as search and rescue.
Exact symbolic artificial intelligence for faster, better assessment of AI fairness
Probabilistic programming language allows for fast, error-free answers to hard AI problems, including fairness.
3 Questions: David Kaiser and Julie Shah on social and ethical responsibilities of computing
Advancing the study and practice of thinking responsibly in computing education, research, and implementation.
Lincoln Laboratory convenes top network scientists for Graph Exploitation Symposium
Researchers share progress applying network science to disinformation tracing, Covid-19 modeling, and machine learning.
MIT Schwarzman College of Computing awards named professorships to two faculty members
Dina Katabi and Aleksander Madry receive additional support to pursue their research and develop their careers.
Software to accelerate R&D
The alumni-founded startup Uncountable has developed a digital workbook to help scientists get more out of experimental data.