Research

What Are We Trying To Achieve?

As feature-size scaling and “Moore’s Law” in CMOS circuits further slow down, attention is shifting to computing by non-von Neumann, non-CMOS, and non-Boolean computing models.

Our goal is to develop disruptive new computing paradigms and machines that will allow for lasting breakthroughs and open new application domains in the next 5-20 years.

What’s Our Secret Sauce?

We use a radical interdisciplinary approach and apply tools from computer science, computer engineering, physics, biology, complex systems science, and cognitive science to the study and the design of next generation computing models and architectures.

The core of teuscher.:Lab is the unique, diverse, and highly interdisciplinary team. Together, we are more then he sum of our parts. The success of our research also heavily relies on our sponsors and on many local, national, and international collaborations.

Our Core Expertise

  • Non-classical computation
  • Biomolecular and neuromorphic computation
  • Machine learning and optimization techniques.
  • Computation with random systems
  • Intrinsic computation
  • Non-linear dynamical systems
  • Complex and adaptive systems and networks
  • Large-scale simulations

Computing Education

We are committed to educate a new generation of students to make a difference for today’s and tomorrow’s society that depends on increasingly pervasive and complex computers.

Next Generation Computing Models and Architectures