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Welcome to the WAVES Lab at Michigan State University

The WAVES lab conducts fundamental and applied research in the general areas of multidimensional signal processing, machine learning, information theory, computer vision, communications and networking. Recent WAVES lab projects include contributions in the following application areas:

Applications

  1. Autonomous and connected vehicles
  2. Mobility and transportation services
  3. Recommendation systems
  4. Environmental and multi-spectral imaging BIGDATA
  5. Visual data super-resolution
  6. Social networks
  7. Sensor networks
  8. Visual data compression, coding and communication
  9. Internet and wireless/mobile network video streaming

The WAVES lab develops its solutions based on sound theoretical foundations rooted in a wide range of fundamental disciplines, including signal processing, information theory, machine learning, graph and network theory, estimation theory, and related disciplines. Recent analytical frameworks that have been driving our research includes:

Analytical Tools

  1. Deep learning
  2. Data and sensor fusion
  3. Manifold and dictionary learning
  4. Sparse coding and compressed sensing
  5. Tensor/matrix decomposition, factorization and low-rank minimization
  6. Graph- and network-based signal processing and coding

Since the early stages of its inception, the WAVES lab has been addressing research problems that are emerging from the convergence of technology areas, including wireless/mobile networks, the Internet, and a variety of scientific and social applications. WAVES lab research areas and related applications have evolved over the years to include a broad and diverse examples such as self-driving cars, mobile/transportation services, Internet-of-Things (IoT), social networks, BIGDATA, cloud computing and video streaming.

 
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WAVES Lab, Electrical and Computer Engineering Department, Michigan State University