Computer Engineering

The research focus of the Computer Engineering group at Yale University is on reliable and secure architectures and computing platforms. Research projects are led by faculty members in Electrical Engineering, in collaboration with Computer Science and other Yale departments.

Current strengths of the group include: Computer Architecture, Hardware Security, FPGA, Integrated Circuits, VLSI, Sensors and Sensor Networks.

These strengths form a unique set of expertise that allows the Yale Computer Engineering group to tackle a variety of timely and acclaimed research projects.

  • Many-core processor architectures
  • System-on-Chip or Smartphone architectures
  • Secure hardware-software architectures
  • Sensor networks for monitoring and security
  • Data center architecture and security 

The "Computer Systems Lab" is an interdisciplinary laboratory with faculty from both Electrical Engineering and Computer Science that have a shared research interest in computer systems.

Research Summaries for EE Computer Engineering Area by Faculty:

Rajit Manohar: The theory, automation, design and implementation of asynchronous (clockless/self-timed) circuits, architectures, and systems.

Jakub Szefer: Secure hardware-software architectures for servers and mobile devices; Many-core processor architectures with security features, Hardware trust evidence; Design for security and energy efficiency; Security architecture verification; Cloud computing security; Data center security.

Wenjun Hu: Design, prototyping, and empirical measurements and analysis of networked systems - data communication, network architectures, wireless and mobile networking, information theory applied to network and system design, smartphone based visual communications, multimedia communication, and MIMO systems.

Priyadarshini Panda: Neuromorphic Computing: spanning energy-efficient design methodologies for deep learning networks, novel supervised/unsupervised learning algorithms for spiking neural networks and developing neural architectures for new computing scenarios (such as lifelong learning, generative models, stochastic networks, adversarial attacks etc.).