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His research on large language model vulnerabilities earns a spot in a global AI conference.
Large language models (LLMs)—a type of artificial intelligence (AI) algorithm—are used to power various applications from chatbots to writing assistants. Yet, these models face increasing security risks from prompt hacking—a process where models are coerced...read more
Their innovative work focuses on improving place recognition capabilities, a critical component for accurately identifying the specific locations visited by diverse robots.
Peng Gao , formerly a postdoctoral fellow at the University of Maryland and now at the University of Massachusetts Amherst , received a Best Paper Award in the Agri-Robotics category at the 2023 IEEE/RSJ International...read more
Dinesh Manocha, a co-PI of the challenge, contributes expertise in perception-based machine learning and multi-agent coordination.
A multi-institutional team led by the University of Maryland (UMD) has been selected for the DARPA Triage Challenge , in which participants compete to develop novel methods of detecting injuries, particularly in mass casualty incidents,...read more
Whether it’s managing an office move or handling multiple maintenance requests, J’Vaughn Holmes could be one of the busiest staff members on the University of Maryland campus, yet he juggles his hectic workload with consummate...read more
Her work offers a fresh perspective on traditional planning languages used in robotics.
Angeline Aguinaldo , a computer science Ph.D. student at the University of Maryland, received a Best Paper Award for her research in the field of robotic representation at the 2023 Association for the Advancement of...read more
70 UMD students will be matched with companies for signature micro-internship program.
Break Through Tech’s Sprinternship™ program is designed to help undergraduate women from diverse racial and socioeconomic backgrounds break into careers in tech. This year, Break Through Tech DC is collaborating with 14 organizations to host...read more
Machine learning is responsible for some of the most significant advancements in technology that make use of artificial intelligence today—from the burgeoning industry of self-driving cars to virtual personal assistants, like Amazon’s Alexa and Apple...read more
Human body becomes robot playground in project funded by Arts for All Initiative
A tiny robot glides up a dancer’s arm and travels across her torso, connecting an ancient art form to the technology of the future. Instead of passively watching, the audience for the piece—through their smartphones—helps...read more
Upcoming Events
Talk
12.01.2023 11:00 to 11:55
How Hard Is It for Networks to Run Themselves?
Alan Zaoxing Liu
IRB 0318 or via Zoom: https://umd.zoom.us/j/92721031800?pwd=dGhidU13dzl0cmI2eUM4SzJLNTZrZz09
How Hard Is It for Networks to Run Themselves?
Alan Zaoxing Liu
Event
Talk
12.04.2023 11:00 to 12:00
Achieving Codec Telepresence
Michael Zollhoefer
IRB 3137 or Zoom: https://umd.zoom.us/j/7316339020
Achieving Codec Telepresence
Michael Zollhoefer
Talk
12.08.2023 11:00 to 11:55
Robust AI for Security
Yizheng Chen
IRB 0318 or via Zoom: https://umd.zoom.us/j/92721031800?pwd=dGhidU13dzl0cmI2eUM4SzJLNTZrZz09
Robust AI for Security
Yizheng Chen
Event
Event
11.28.2023 12:00 to 13:00
The realities and illusions of AI
IRB 5137 and Zoom: https://umd.zoom.us/j/92497160817?pwd=bVlVRjdWQTU0STZESFZHdE1TMDVBQT09
The realities and illusions of AI
11.29.2023 11:00 to 12:00
Local Hamiltonian Problem with succinct ground state is MA-Complete
Location: ATL 3100A and Virtual Via Zoom: https://umd.zoom.us/j/96286023374?pwd=YXFHRThodEpvQ01YbWFYc2RNTy9VUT09 Meeting ID: 962 8602 3374 Passcode: 536883
Local Hamiltonian Problem with succinct ground state is MA-Complete
11.30.2023 14:00 to 15:15
Piecemeal knowledge acquisition for computational normative reasoning
IRB 2207 or Zoom: https://umd.zoom.us/j/99896626594?pwd=ODd6TVRyYllnK3lxQUx1YTJnT0o4Zz09
Piecemeal knowledge acquisition for computational normative reasoning
12.01.2023 11:00 to 11:55
How Hard Is It for Networks to Run Themselves?
IRB 0318 or via Zoom: https://umd.zoom.us/j/92721031800?pwd=dGhidU13dzl0cmI2eUM4SzJLNTZrZz09
How Hard Is It for Networks to Run Themselves?
12.04.2023 11:00 to 12:00
Achieving Codec Telepresence
IRB 3137 or Zoom: https://umd.zoom.us/j/7316339020
Achieving Codec Telepresence