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For Jacqueline Deprey (B.S. ’20, computer science; B.S. ’20, operations management and business analytics), a personal loss and a passion for problem-solving inspired Perpetua, a digital toolkit designed to simplify estate settlement.
From her first coding experience in high school, Jacqueline Deprey (B.S. ’20, computer science; B.S. ’20, operations management and business analytics) has always been drawn to the problem-solving power of computing. “I don't know that...read more
He will collaborate with the University of Melbourne on artificial intelligence risks, national security and policy development.
As artificial intelligence becomes more widely used in national security, government operations and other critical areas, questions about its safety and reliability are drawing increased attention. University of Maryland computer science Professor William Regli (Ph.D...read more
A glass wall can look like an open path to a robot. Reflections and transparency can fool its sensors, leaving it with a faulty map—and a route that could end in a collision. University of...read more
Eric Gilerson’s single-author paper explores a method for performing exact arithmetic within language models.
When asked to multiply two numbers, a language model may predict the answer based on patterns in its training data rather than perform the calculation directly. University of Maryland undergraduate Eric Gilerson is investigating a...read more
Huang develops methods to reduce data demands and address hardware errors in scientific computing and artificial intelligence systems.
As scientific facilities and artificial intelligence systems process growing amounts of data, researchers must contend not only with computing speed but also with the cost of moving and storing information and the possibility of hardware...read more
The four-year initiative will use AI and automation to support remotely accessible biomanufacturing experiments, with Liu co-leading the lab's data and AI systems.
Biomanufacturing underpins products ranging from vaccines to cancer therapies, but developing those products can require experiments that are time-consuming, costly and difficult to reproduce. A new University of Maryland-led project is bringing together artificial intelligence,...read more
The projects aim to predict hospital readmissions in high-risk heart failure patients and establish reliable methods for evaluating the safety and performance of AI-enabled medical imaging systems.
University of Maryland computer scientist Heng Huang is part of two new federally funded projects aimed at improving the use of artificial intelligence in healthcare: a four-year, $1.2 million award to develop a wearable device...read more
Watch someone pour almonds into a bowl, and the action is easy to follow: a container moves, tilts and releases its contents. Teaching a robot to do the same can require costly demonstrations specifying how...read more
Upcoming Events
Talk
10.20.2026 13:00 to 15:30
PhD Defense: The Anatomy of Trust in Foundation Models: Representations, Reasoning, and Alignment
Atoosa Malemir Chegini
PhD Defense: The Anatomy of Trust in Foundation Models: Representations, Reasoning, and Alignment
Atoosa Malemir Chegini
Talk
10.21.2026 15:30 to 16:30
Characterizing and Mitigating Performance Variability in Accelerator-Rich Systems
Matt Sinclair
University of Wisconsin-Madison
IRB 4105
Characterizing and Mitigating Performance Variability in Accelerator-Rich Systems
Matt Sinclair
University of Wisconsin-Madison
Event
Talk
10.23.2026 10:00 to 11:00
Specifications, Tests, and Audits: the Building Blocks of First-Year CS in an Agentic Era
Kathi Fisler
Brown University
IRB 1116 or Zoom https://umd.zoom.us/j/99365998212?pwd=CEJUNoBeooaDkYchGXoRdmGyCMESLM.1
Specifications, Tests, and Audits: the Building Blocks of First-Year CS in an Agentic Era
Kathi Fisler
Brown University
Talk
10.23.2026 11:00 to 12:00
From Pixels to Physics: Learning to Reason, Act, and Explore
Jia-Bin Huang
IRB 2107 or Zoom https://umd.zoom.us/j/91267609044?pwd=g4uLkhpH4T8d2Gln0HXg6s4qaxzpbj.1
From Pixels to Physics: Learning to Reason, Act, and Explore
Jia-Bin Huang
Event
Event
Talk
11.02.2026 10:00 to 12:00
MS Defense: Structured World Models: Predict, Remember, Act
Tan Dat Dao
CS Department, University of Maryland
MS Defense: Structured World Models: Predict, Remember, Act
Tan Dat Dao
CS Department, University of Maryland
Talk
11.06.2026 10:00 to 11:00
What We Leave Behind: Delegating Sensemaking in the Age of Generative AI
Niklas Elmqvist
Aarhus University
IRB 4105
What We Leave Behind: Delegating Sensemaking in the Age of Generative AI
Niklas Elmqvist
Aarhus University
Event
10.20.2026 13:00 to 15:30
PhD Defense: The Anatomy of Trust in Foundation Models: Representations, Reasoning, and Alignment
PhD Defense: The Anatomy of Trust in Foundation Models: Representations, Reasoning, and Alignment
10.21.2026 15:30 to 16:30
Characterizing and Mitigating Performance Variability in Accelerator-Rich Systems
IRB 4105
Characterizing and Mitigating Performance Variability in Accelerator-Rich Systems
10.23.2026 10:00 to 11:00
Specifications, Tests, and Audits: the Building Blocks of First-Year CS in an Agentic Era
IRB 1116 or Zoom https://umd.zoom.us/j/99365998212?pwd=CEJUNoBeooaDkYchGXoRdmGyCMESLM.1
Specifications, Tests, and Audits: the Building Blocks of First-Year CS in an Agentic Era
10.23.2026 11:00 to 12:00
From Pixels to Physics: Learning to Reason, Act, and Explore
IRB 2107 or Zoom https://umd.zoom.us/j/91267609044?pwd=g4uLkhpH4T8d2Gln0HXg6s4qaxzpbj.1
From Pixels to Physics: Learning to Reason, Act, and Explore
10.27.2026 14:00 to 15:00
Formal Methods for Safe and Interpretable Reinforcement Learning
CSI 2120 or https://umd.zoom.us/j/93960331973?pwd=tVQ7gtFucJEkSYna38zePzkPpHm3J7.1
Formal Methods for Safe and Interpretable Reinforcement Learning