The mission of the mentor's lab is to study, rethink, model, and design next generation computing models and technologies that we may see on the market in 10-20 years. Researchers in this lab are interested in bold, visionary, and transformational solutions to complex and critical problems in the following areas: biomolecular computation, nanoelectronics, machine learning, complex networks, artificial life, and dynamical systems.
The intern(s) will be able to choose from several projects:
- Project 1: The intern will learn about complex networks and evolutionary algorithms. Complex networks are networks with non-trivial features as not commonly seen in regular or random networks. Examples of complex networks are the neural network of the brain, the airline network, or the electrical grid. The interconnect topology of such networks (or graphs) plays an important role for the network's properties. We will use evolutionary algorithms to evolve complex networks on electronic chips which need to be fast, robust, and cheap. We will then analyze and study the resulting networks.
- Project 2:The intern will learn how to program Graphic Processing Units (GPUs) and how to implement simple algorithms. GPUs are specialized circuits designed to accelerate operations needed to process images. They are increasingly used as accelerators for other general purpose computing tasks. The goal of this project to implement machine algorithms on GPUs.
- Project 3: The intern will focus on machine learning algorithms for emerging devices. The student will use a programming language to implement and test novel machine learning approaches, such as Locally Competitive Algorithms (LCA) or Reservoir Computing (RC). Such algorithms are ideally suited for emerging devices, such as memristors.