The
Geometric Reasoning and Artificial Intelligence Laboratory [GRAIL]
is a research lab in the department of Automotive Engineering at the Clemson University's International Center for
Automotive Research [CU-ICAR].
G
RAIL lab is dedicated to establish new computational methods to provide innovative solutions to
manufacturing and material informatics, digital design, prognostics and diagnostics, extended reality,
unmanned aerial vehicles (UAVs), connected autonomous vehicles (CAVs), and human technology symbiosis domains.
Our core competency is in artificial intelligence, machine learning, and geometric reasoning domains.
By combining engineering innovations with methods from machine learning, AI, statistics and optimization,
geometric reasoning, metamodeling, sampling, and applied ontology, we strive to solve important research problems
in the cyber-physical applications specified above.
Additionally, we work collaboratively with researchers in other domains such as material science,
geospatial reasoning, and bio-medical domain to find innovative usage and applications of geometric reasoning and
machine learning methods. GRAIL lab is housed in the modern office space of CU-ICAR.
The lab director is Dr. Rahul Rai.
Geometric Reasoning and Artificial Intelligence Laboratory [GRAIL]
Artificial Intelligence and Machine Learning
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- Probabilistic Graphical Models
- Design of Experiments (DoE)
- Reinforcement Learning
- Graph Grammar
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- Applied Ontology
- Deep Learning
- Optimization
- Search
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Geometric Reasoning
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- Point Cloud Data Processing
- Topology Optimization
- Group Morphology
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- Mesh Processing
- Metamodeling
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Domain Focus
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- Engineering Design
- Cyber-Physical Systems (CPS)
- Human-Technology Symbiosis
- Material Informatics
- Connected and Autonomous Vehicles
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- Manufacturing
- Prognostics and Diagnostics
- Extended Reality
- Generative Design
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Research assistantships are available!!!
GRAIL is looking for exceptional graduate and undergraduate students who have the potential to excel beyond
their basic undergraduate education. A successful student in this area must have a solid background in
mathematics, mechanical engineering, and computer programming. Good communication skills, previous research
experience are a plus. Contact Prof. Rai: rrai [at] clemson.edu