Machine Learning and AI

Machine Learning and Artificial Intelligence (MLAI) is an interdisciplinary research area within ECE. It focuses on developing intelligent systems and algorithms that can learn from data, adapt to changing environments, and make autonomous decisions.

This includes deep learning and neural networks for solving complex problems, computer vision for interpreting visual data, natural language processing for language understanding and generation, reinforcement learning for sequential decision-making, data mining and pattern recognition for extracting insights from large datasets, machine learning hardware for efficient AI algorithms, ethical AI considerations, human-machine interaction, cybersecurity, and energy-efficient AI solutions.

Researchers in this field aim to advance AI technology, transform industries, and address societal challenges while ensuring responsible and ethical use.

Associated Labs/Centers

  • Laboratory for interpretable Visual Modeling, Computing and Learning (iVMCL)
  • Center for Advanced Electronics through Machine Learning (CAEML)
  • Optical Sensing Lab (OSL)
  • Active Robotics Sensing (AROS)

Primary Faculty

Embedded Machine Learning Club

The Embedded Machine Learning club raises awareness about Machine Learning (ML) by conducting outreach and to advance member knowledge and skills in ML with internal education.
It provides members a hands-on opportunity to gain technical and leadership skills, increase professional development, build career networks, and propel internship search, and provides impactful ML solutions to community partners including research groups and other club organizations in addition to hosting and participating in ML-related competitions.

Learn more
Sensing Success

Sensing Success

A professorship established by John Amein ’84 and his wife Happy supports Professor Michael Kudenov’s research on sensor development that is growing more success for North Carolina agriculture.