Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
systems. The fast growth, practical achievements and the overall success of modern approaches to AI guarantees that machine learning AI approaches will prevail as a generic computing paradigm, and will find
-
include: 1. Identify a novel co-design methodology along with the structural templates that could be used to drive the further design process of collocated teamwork analytics with critical educational
-
I supervise computational projects in electron microscopy imaging for investigating materials at atomic resolution. Some projects centre on analysing experimental data acquired by experimental
-
theoretical colleagues. All research takes place within our dynamic particle physics research group with academics and postdocs, as well as graduate and undergraduate students. Some work will be purely
-
such as prompt injection, adversarial medical-image manipulation, poisoned clinical records, unsafe AI-agent actions, membership inference, privacy leakage, and manipulation of AI-generated clinical
-
PatchSentinel-X: Transformer-Based Security Patch Intelligence for Vulnerability Lifecycle Assurance
prototype A prototype that can support secure code review by producing patch trust scores and review recommendations. Required knowledge Essential Python programming, Machine learning fundamentals, Deep
-
known as Team COMPAS -- includes a number of amazing undergraduate and graduate students, postdocs, alumni, and other fantastic collaborators. Please contact me if you are interested in joining our group
-
the area of end-to-end modular autonomous driving using computer vison and deep learning methods. This includes developing an efficient and interpretable image processing, vision-based perception and
-
Using the Project-1 hiPSC platform, this project builds AI pipelines to learn disease-relevant representations from cellular images, fused with multi-omics. Models will classify diagnosis and predict
-
. This would provide thousands of diverse example images with corresponding body part locations. These data would be used to train a deep learning model 5, 7 . The model’s high-quality body part predictions may