Machine Learning

Machine learning plays a central role in building intelligent computing, control and communications systems. Typical applications include computer vision, natural language processing, signal processing, internet of things (IoT), cybersecurity, and robotics. Members of the ECE Department actively engage in the research and development of machine learning algorithms to support an array of electrical engineering applications.

CONTACT
Location: Atwater Kent Laboratories
Phone: 508-831-5231

 

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Headshot of Ziming Zhang

                Ziming Zhang

                Assistant Professor

Vision, Intellegience, and System Lab (VISLab)

The aim of the lab is to engage in the state-of-the-art research into the mathematical foundation of computer vision (CV) and artificial Intelligence (AI), as well as the hardware design and engineering that meets the needs of society. The works from the lab have been published in top conferences (e.g. CVPR, ICCV, NeurIPS, ICLR, IROS, CDC) and top journals (e.g. TPAMI).

Research Areas:

  • Computer Vision
  • Machine Learning
  • Deep Learning
  • Optimization
  • Algorithm
  • Autonomous Driving
  • Time-series Data Analysis
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Headshot of Xinming Huang

                Xinming Huang

                Professor

Embedded Computing Lab

Our research group is focused on the computer vision and deep learning algorithms, efficient hardware architecture designs, and their applications to autonomous driving, robotics, and embedded systems. Our research works have been published regularly in top venues such as CVPR, ICCV, ICRA, IROS, RAL, TPAMI, TNNLS, TMM, TCAS1, etc. Our mission is to build integrate circuits for artificial intelligence.

Research Areas:

  • Autonomous Vehicles
  • Robotics
  • Computer Vision
  • Deep Learning
  • Hardware Architecture
  • Integrated Circuits
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Headshot of Donald Brown

                Donald R. Brown

                Professor

Signal Processing and Information Networking (spinlab)

The signal processing and information networking laboratory (spinlab) was founded in 2002 by Prof. D. Richard Brown III with the purpose of bringing motivated undergraduate and graduate students together to work on fundamental and applied problems in signal processing, communication systems, networking, and machine learning. Spinlab is located on the third floor of the Atwater Kent Laboratories building at Worcester Polytechnic Institute

Research Areas:

  • Signal Processing
  • Communication Systems
  • Networking
  • Machine Learning
  • Inference

 

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Headshot of ​​​​​​​Alexander Wyglinski

                Alexander Wyglinski

                Associate Dean of Graduate                 ​​​​​​​              ​​​​​​​Studies

                ​​​​​​​Professor

Wireless Innovation Lab

The Wireless Innovation Laboratory (WILab) conducts fundamental and applied research in wireless communication systems engineering and vehicular technology. Consisting of over 1500 sq ft of prime research space as well as state-of-the-art software tool and experimentation equipment, this facility focuses on devising new solutions and new knowledge in the areas of cognitive radio, 5G/6G, connected vehicles, software-defined radio, autonomous vehicles, spectrum coexistence, vehicular security, prototype wireless systems, satellite communications, millimeter wave communications, and GPS/GNSS. WILab has been extensively funded via numerous sponsors from both government and industry, including the National Science Foundation, MathWorks, Office of Naval Research, Toyota InfoTechnology Center USA, and the MITRE Corporation.

Research Areas:

  • Cognitive Radio
  • 5G/6G
  • Connected Vehicles
  • Software-defined Radio
  • Autonomous Vehicles
  • GPS/GNSS
  • Spectrum Coexistence
  • Vehicular Security
  • Prototype Wireless Systems
  • Satellite Communications
  • Millimeter Wave Communications

 

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botang

                Bo Tang

                Associate Professor

Computational Intelligence and Learning Systems (CILS) Lab

The Computational Intelligence and Learning Systems (CILS) Lab conducts research in bio-inspired artificial intelligence (AI), AI security, edge AI, and their applications in Cyber-Physical Systems (e.g., wireless networks, autonomous vehicles (underwater/ground), and power systems). Our works have been published in top-tier conferences and journals such as ICML, IEEE Trans. on Neural Networks and Learning Systems (TNNLS), IEEE Trans. on Cybernetics, IEEE Wireless Communication Magazine, etc.

Research Areas:

  •  Machine Learning
  • Signal Processing
  • Cyber-Physical Systems
  • Communication Systems
  • Big Data Analysis
  • Autonomous Vehicles