SuperUROP: Showcasing students' research work in progress
Undergraduate researchers discussed their projects at a well-attended poster session.
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Engineers program marine robots to take calculated risks
Algorithm could help autonomous underwater vehicles explore risky but scientifically-rewarding environments.
Learning to teach to speed up learning
An algorithm that teaches robot agents how to exchange advice to complete a task helps them learn faster.
Want to squelch fake news? Let the readers take charge
Study shows audience judgments can identify online misinformation.
Converting Wi-Fi signals to electricity with new 2-D materials
Device made from flexible, inexpensive materials could power large-area electronics, wearables, medical devices, and more.
Filling the gaps in a patient’s medical data
Neural network assimilates multiple types of health data to help doctors make decisions with incomplete information.
Julia Lab joins team to speed up drug approval process
Health Analytics Collective uses real-world evidence to modernize health and drug development decisions.
Identifying artificial intelligence “blind spots”
Model identifies instances when autonomous systems have learned from examples that may cause dangerous errors in the real world.
A faster, more efficient cryptocurrency
Design reduces by 99 percent the data users need to join the network and verify transactions.
AI, the law, and our future
MIT “Policy Congress” examines the complex terrain of artificial intelligence regulation.
Democratizing artificial intelligence in health care
Hackathons promote doctor-data scientist collaboration and expanded access to electronic medical-records to improve patient care.
Science as a social practice
PhD student Marion Boulicault believes in an interdisciplinary path forward for science, feminism, and philosophy.
Fortifying the future of cryptography
Vinod Vaikuntanathan aims to improve encryption in a world with growing applications and evolving adversaries.
Democratizing data science
Tool for nonstatisticians automatically generates models that glean insights from complex datasets.
MIT adds computational Earth, atmospheric, and planetary sciences to its PhD offerings
New EAPS thesis field is the most recent to join the computational science and engineering doctoral program within the Center for Computational Engineering.