Success at the intersection of technology and finance
Citadel founder and CEO Ken Griffin visits MIT, discusses how technology will continue to transform trading and investing.
Citadel founder and CEO Ken Griffin visits MIT, discusses how technology will continue to transform trading and investing.
The system they developed eliminates a source of bias in simulations, leading to improved algorithms that can boost the performance of applications.
A collaborative research team from the MIT-Takeda Program combined physics and machine learning to characterize rough particle surfaces in pharmaceutical pills and powders.
Senior Amelia Dogan brings together computer science, city planning, and American studies to work for social change.
Widely recognized leader in statistics and machine learning to succeed Munther Dahleh.
MIT ReACT and Innovation Leadership Bootcamp provide valuable opportunities.
MIT researchers exhibit a new advancement in autonomous drone navigation, using brain-inspired liquid neural networks that excel in out-of-distribution scenarios.
With the right building blocks, machine-learning models can more accurately perform tasks like fraud detection or spam filtering.
Associate Professor Tamara Broderick and colleagues build a “taxonomy of trust” to identify where confidence in the results of a data analysis might break down.
Keynote speaker Bror Saxberg SM ’85, PhD ’89 encourages understanding learners and their contexts.
Assistant professor of nuclear science and engineering Haruko Wainwright believes environmental monitoring can empower citizens to make informed decisions about their energy and environment.
New LiGO technique accelerates training of large machine-learning models, reducing the monetary and environmental cost of developing AI applications.
Careful planning of charging station placement could lessen or eliminate the need for new power plants, a new study shows.
Researchers used machine learning to build faster and more efficient hash functions, which are a key component of databases.
MIT researchers trained logic-aware language models to reduce harmful stereotypes like gender and racial biases.