The Cornell Learning Machines Seminar is a semi-monthly seminar held at the Cornell Tech campus in New York City. The seminar focuses on machine learning and related areas, including Natural Language Processing, Vision, and Robotics.
Thursdays, 3:35pm - 4:25 EST in Gates 122 and streaming via Zoom.
Virtual lecture series on topics across machine learning in medicine, featuring extensive Q & A and panel discussions.
Fridays, 12:15 p.m. ET in Gates 122 and streaming via Zoom. Please note we will broadcast some seminars from Cornell Tech.
Happening every Friday from 4-4:30 PM via Zoom, the forum is for Cornell faculty and staff (e.g., research operational support staff) who are interested in the EMPIRE AI’s current status and future plans.
Registration for the series is required, which will then provide the Zoom link info.
Experience an evening dedicated to the transformative work at Cornell Tech, where we are developing impactful ventures and groundbreaking research, while engaging in conversations that define the future of AI. Enjoy short presentations from our graduate students and researchers, highlighting projects that tackle pressing issues and spark thought-provoking conversations around technology and its real-world applications.
The Cornell Learning Machines Seminar is a semi-monthly seminar held at the Cornell Tech campus in New York City. The seminar focuses on machine learning and related areas, including Natural Language Processing, Vision, and Robotics.
Virtual lecture series on topics across machine learning in medicine, featuring extensive Q & A and panel discussions.
Happening every Friday from 4-4:30 PM via Zoom, the forum is for Cornell faculty and staff (e.g., research operational support staff) who are interested in the EMPIRE AI’s current status and future plans.
Registration for the series is required, which will then provide the Zoom link info.
The Cornell Learning Machines Seminar is a semi-monthly seminar held at the Cornell Tech campus in New York City. The seminar focuses on machine learning and related areas, including Natural Language Processing, Vision, and Robotics.
