AI ML Research

My research interests in AI/ML have focused on applying the technologies and software to applications in cyber-physical systems, digital twins, cybersecurity verification, and intelligent mechanical design. My research has largely used existing AI/ML methods and using them effectively in novel ways to solve difficult problems in various domains. Nevertheless, I am interested in the fundamental concepts underlying the methods and developing computational implementations from scratch, as, for example, in new Recurrent Neural Network implementations from scratch, not entirely relying on popular AI/ML packages.

From the computational point of view, my other major interests are in the end-to-end scalability of AI/ML solutions, especially in relation to novel hardware architectures, down-to-the-metal considerations, hardware-software interplay and codesign, and holistic scalability of workflows. Of particular interest are new AI/ML problems that are characterized by volumes and velocities massively higher than what typical desktop-based and cluster-based solutions address.

While reaping the benefits of well known and tested methods, my inclination is to keep an eye towards basic insights, unique combinations, and new techniques.

Overview

Projects

• Deep CYBERIA
  • CNN: Sensor detection
  • RNN: Sensor time-series
• CYVET
  • NLP: CyBERT over BERT
  • NLP: Claim detection
  • CNN: Document classification
  • CNN: Product detection
• Digital Twin Framework
  • RNN: Anomaly detection
• DeepEx
  • CNN: Material image classification
  • VAE: Molecular Dynamics
• Intelligent Design
  • RL: Steering
• Energy Management
  • RL: Dynamic learning and adaptation
• Kensor
  • Critical Facility Monitoring
  • Novel Markov modeling

Software

• Python
• Jupyter
• numpy/no-numpy
• CUDA
• CUDNN
• MPI
• Tensorflow (2/Keras)
• PyTorch

Organization

• Sponsors: Various, across multiple projects
  • US Department of Energy (DOE)
  • US Department of Defense (DoD)
  • Oak Ridge National Laboratory-Directed Research and Development (LDRD)
  • Industry

Publications

Listed under the AI/ML category under Publications At-a-glance