Generalized Reasoning and Adaptive Intelligence (GRAIL) Lab

Are you interested in building the next generation of AI systems while gaining research experience that is highly valued by industry and Academia? The GRAIL Lab is looking for motivated students to join COMP 696C. 

Please note: COMP 696C is available only to currently enrolled CSUN students.


Potential Research Areas with Career Benefits

• Machine Learning & Deep Learning
  Build a strong foundation in modern AI algorithms and predictive modeling for careers as AI/ML Engineers, Data Scientists, and AI Researchers.

• Computer Vision
  Develop intelligent vision systems for image and video understanding, with applications in autonomous systems, robotics, healthcare, and AI startups.

• Industrial Visual Anomaly Detection
  Design AI systems that automatically detect defects and unusual patterns in manufacturing and quality inspection. This research is highly relevant to Industry 4.0 and is an area of growing interest among leading technology companies, including Amazon.

• Video Analytics for Crime Detection & Surveillance Intelligence
  Develop intelligent video understanding systems for public safety, security technologies, and large-scale surveillance applications.

• Traffic Scene Understanding, Accident Risk Prediction, and Spatiotemporal Anomaly Detection
  Apply AI to intelligent transportation systems, autonomous driving, smart cities, and safety-critical decision-making.

• GeoAI & Agricultural Intelligence Systems
  Build AI solutions using computer vision and geospatial data for precision agriculture, environmental monitoring, and sustainable smart farming.

Students will gain experience in the following areas through their research: 

Machine Learning• Deep Neural Networks • Vision Transformers (ViT) • Multimodal AI • Self-Supervised Learning • Vision Language Models•  Generative AI • Edge AI • Spatiotemporal Modeling • Real-world AI Systems • Responsible AI for Safety-Critical Applications

@Students: If you have any other exciting proposals, feel free to share them with me (rashida dot hasan at csun dot edu)