Interview
Interview

Interview

Algorithms Alternative energy Artificial Intelligence Batteries Climate change Computer science and technology Electrical engineering and computer science (EECS) Energy Energy storage Faculty Interview Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Pollution Research School of Engineering Sustainability Sustainable computing

3 Questions: How AI could optimize the power grid

While the growing energy demands of AI are worrying, some techniques can also help make power grids cleaner and more efficient.

Artificial Intelligence Bacteria Biology Electrical engineering and computer science (EECS) Evolution Faculty Genetics Interview machine learning Microbes MIT Schwarzman College of Computing School of Engineering School of Science

3 Questions: Using computation to study the world’s best single-celled chemists

Assistant Professor Yunha Hwang utilizes microbial genomes to examine the language of biology. Her appointment reflects MIT’s commitment to exploring the intersection of genetics research and AI.

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) Algorithms Animals Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Ecology Electrical engineering and computer science (EECS) Environment Graduate, postdoctoral Interview machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Pollution Research School of Engineering Students Sustainability

3 Questions: How AI is helping us monitor and support vulnerable ecosystems

MIT PhD student and CSAIL researcher Justin Kay describes his work combining AI and computer vision systems to monitor the ecosystems that support our planet.

Algorithms Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Interview Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research School of Engineering

3 Questions: The pros and cons of synthetic data in AI

Artificially created data offer benefits from cost savings to privacy preservation, but their limitations require careful planning and evaluation, Kalyan Veeramachaneni says.

Artificial Intelligence Broad Institute Cells CRISPR Data DNA Electrical engineering and computer science (EECS) Faculty Genomics Health sciences and technology IDSS Interview machine learning MIT Schwarzman College of Computing Proteins School of Engineering

3 Questions: On biology and medicine’s “data revolution”

Professor Caroline Uhler discusses her work at the Schmidt Center, thorny problems in math, and the ongoing quest to understand some of the most complex interactions in biology.

Artificial Intelligence Data Health Care Institute for Medical Engineering and Science (IMES) Interview Medicine Research School of Engineering Staff

3 Questions: How to help students recognize potential bias in their AI datasets

Courses on developing AI models for health care need to focus more on identifying and addressing bias, says Leo Anthony Celi.

Alumni/ae Analytics Artificial Intelligence Books and authors Business and management Data Education, teaching, academics Faculty Health Care Interview machine learning Medicine MIT Sloan School of Management MITx Office of Open Learning Provost Research

Q&A: A roadmap for revolutionizing health care through data-driven innovation

A new book coauthored by MIT’s Dimitris Bertsimas explores how analytics is driving decisions and outcomes in health care.

Artificial Intelligence Chemical engineering Ethics Interview Photography School of Engineering

3 Questions: Visualizing research in the age of AI

Felice Frankel discusses the implications of generative AI when communicating science visually.

Artificial Intelligence Chemical engineering Ethics Interview Photography School of Engineering

3 Questions: Visualizing research in the age of AI

Felice Frankel discusses the implications of generative AI when communicating science visually.

Artificial Intelligence Chemical engineering Ethics Interview Photography School of Engineering

3 Questions: Visualizing research in the age of AI

Felice Frankel discusses the implications of generative AI when communicating science visually.