Recent News & Accomplishments
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 into abandoning their intended tasks in favor of potentially harmful instructions. University of Maryland computer science major Sander Schulhoff will present a research paper on this issue at the Empirical Methods in Natural Language Processing (EMNLP) 2023 conference, scheduled for December 6 to 10, 2023, in Singapore. His paper, titled... 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 Conference on Intelligent Robots and Systems (IROS), held in Detroit, Michigan, from October 1 to 5, 2023. His paper, titled "Visual, Spatial, Geometric-Preserved Place Recognition for Cross-View and Cross-Modal Collaborative Perception," stood out among 1,700 accepted papers, highlighting its innovative advancements in robotics. In addition to Gao, collaborators on the research... 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, so that medical personnel can respond more quickly, efficiently, and precisely. Dubbed RoboScout DTC, the UMD team will be part of the Systems Competition, one of three competitions in the Triage Challenge, and will focus its efforts on primary triage, in which medical personnel seek to identify and treat those most urgently in need of care. In mass casualty... 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 ease and an engaging sense of humor. As the facilities coordinator for the University of Maryland Institute for Advanced Computer Studies (UMIACS) and the Department of Computer Science, it is Holmes’ responsibility to make sure everything runs smoothly behind the scenes so that faculty, staff and students have the proper space and equipment to get their work done... 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 Artificial Intelligence (AAAI ) Fall Symposium on Unifying Representations for Robot Application Development, held in Arlington, Virginia, from October 25 to 27, 2023. Her paper, titled “ A Categorical Representation Language and Computational System for Knowledge-Based Robotic Task Planning ,” made a notable contribution to AI planning. In addition to Aguinaldo, collaborators on... read more
70 UMD students will be matched with companies for a comprehensive 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 micro-internships for 70 University of Maryland undergraduate students. This January, these Sprinterns will spend three weeks tackling real business challenges while immersed in their host companies’ culture. Employers are gaining access to emerging tech talent and participating in advancing our mission. Meanwhile, student participants build their resumes... read more
He aims to make AI more human-like by teaching it to learn and make decisions as humans do.
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 iPhone’s Siri. However, there is still a long way to go in this field in order to close the divide between humans and machines. Tianyi Zhou, an assistant professor of computer science, is working at the intersection of machine learning and natural language to make AI more human-like by teaching it to learn and make decisions like people do. “... 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 control the movements of the glowing device. “We wanted to use that as a bit of a proxy between us as individuals, and the digital collective on social media,” said Jonathan David Martin, a lecturer in the University of Maryland’s Immersive Media Design major and one of the members of the multidisciplinary team behind DANCExDANCE. The research collaboration was initially... read more
Marina Knittel and Alexander Levine each received the award for the 2023–24 academic year.
The Department of Computer Science at the University of Maryland announced its winners of the Larry S. Davis Doctoral Dissertation Award for 2023-24, an annual honor distinguishing the department's two outstanding doctoral dissertations. This year's recipients are Marina Knittel , who plans to graduate this semester and begin a postdoctoral fellowship at UC San Diego in January, and Alexander Levine (Ph.D. '23, computer science), currently a postdoctoral fellow at the University of Texas at Austin. The award highlights exceptional dissertations noted for their technical depth, significance,... read more
The workshop helped to unite researchers from multiple disciplines to explore the future of technology research and foster collaboration.
General-purpose generative models are the massive, big-data-driven systems powering new and exciting artificial intelligence technology. These systems use large language models, complex algorithms and neural networks to produce original text, audio, synthetic data, images and more. However, the impressive performance of these models comes at a cost. They require significant data, computational power, and storage, creating a barrier to entry, especially for smaller research groups. The hype around large pre-trained models (LPMs)—a deep learning model that is trained on large datasets to... read more