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Ordóñez-Román is an expert in computer vision, natural language processing and machine learning
Hu specializes in interpretable machine learning, automated machine learning, and network analytics
The grant funds joint graph neural network research with the University of St. Thomas
Ogilvie was promoted after working as a postdoctoral researcher in computational biology
NSF backs Rice CS-led search for ‘rules of life’ in microbiomes Wednesday, Aug. 4, 2021
Treangen, Nakhleh and team receive a five-year, $2.8 million grant
Vardi wins award for social and professional responsibility Monday, Aug. 2, 2021
Rice CS professor honored with tech society’s Norbert Wiener Award
Rice CS faculty Unhelkar partners with the TMC for AI collaboration Thursday, Jul. 22, 2021
Vaibhav Unhelkar’s TMC research project receives seed grant via Rice’s ENRICH program
Six new faculty members join Rice Computer Science Wednesday, Jul. 21, 2021
New hires include experts in artificial intelligence, machine learning, computational biology, and ethics in computing
Treangen Lab awarded CDC grant for real-time SARS-CoV-2 variant tracking Tuesday, Jul. 20, 2021
The project will custom fit widely-adopted Harvest software in order to further COVID-19 research
Nakhleh and team seek details of cancer’s evolutionary tree Monday, Jul. 19, 2021
Rice computer scientist, engineering dean Luay Nakhleh earns NSF support for single-cell genome study
Vicente Ordóñez joins Rice CS with CAREER Award Wednesday, Jul. 14, 2021
NSF aids machine-learning effort to recognize complex visual concepts in images
RAMBO speeds searches on huge DNA databases Monday, Jun. 28, 2021
Rice CS team's new method cuts indexing times from weeks to hours, search times from hours to minutes
Building a Career in Data Science Wednesday, Jun. 23, 2021
Learn about in-demand careers in data science, career growth, and the increasing demand for data scientists.
Kavraki Lab nominated for best paper in cognitive robotics at ICRA 2021 Friday, Jun. 11, 2021
Kavraki, Shrivastava and team presented SPARK and FLAME, experience-based frameworks for sampling-based planning