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Professor Max Shulaker joined the EECS department at MIT as an assistant professor in July 2016. He received his B.S., M.S., and Ph.D. from Stanford University in Electrical Engineering. During his Ph.D., his research on carbon nanotube-based transistors and circuits resulted in the first digital systems built entirely using carbon nanotube FETs (including the first carbon nanotube microprocessor), the first monolithic three-dimensional integrated circuits combining arbitrary vertical stacking of logic and memory, and the highest performance and highly-scaled carbon nanotube transistors to-date.

At MIT, Max is launching an experimental research program aimed at realizing his vision for the next-generation of electronic systems based on transformation nanosystems: leveraging the unique properties of emerging nanotechnologies and nanodevices to create new systems and architectures with enhanced functionality and improved performance. About this, he states: “While investigating new devices or new architectures separately can be beneficial, combining the “right” devices, with the “right” architectures, in the “right” way, results in performance (e.g., speed, energy efficiency) gains which far exceed the sum of their individual benefits, while simultaneously providing a rich set of enhanced functionality for applications that otherwise may not be feasible using traditional technologies.”

Max aims to drive nanosystems to both improve computing at the heart of information technology through new approaches (e.g., new system architectures directly enabled by new nanotechnologies). He plans to leverage the richness of new nanomaterials, new computing and memory technologies, and heterogeneous integration to enable new applications beyond the scope of traditional computing. His ultimate goal is to drive nanosystems from concept to reality, resulting in hardware demonstrations of what future electronic systems might look like: from 3D chips with layers of sensing, memory, and logic densely integrated for on-chip ultra-high bandwidth sensing and processing, to computation finely-immersed in biological systems for disease monitoring and nano-implants.