Aisha Walcott, TA for new undergraduate robotics class 6.188, Robotics: Science and Systems I viewing the work of Ricky Nguyen (foreground) and Aaron Tan (background) as they fine tune their robot “Wilson”. Spring, 2005.
Consistent with this mission and vision, we began a variety of initiatives, among them:
Curriculum:
Under the direction of Professor Tomás Lozáno-Pérez, a group of colleagues is looking into restructuring and renovating our SB and M.Eng curricula. The goals are to: add flexibility; emphasize the foundations of EECS (devices and circuits, communications, control, signal processing, optimization, algorithms, theoretical computer science, computer systems and architecture, artificial intelligence, robotics, electrodynamics and energy systems, bioelectrical engineering, computational biology, and others that may be identified); encourage greater depth in the SB program; introduce more hands-on experiences; and increase the integration of life sciences and quantum concepts throughout the curriculum.
In relation to the life sciences, the situation EECS faces at this time is similar to situations faced in the past, e.g., when solid-state physics entered our curriculum in the ‘60s in response to the development of the transistor and the semiconductor integrated circuit, when the field of computer science was created in the ‘60s, or when math strongly influenced our curriculum in the ‘50s in response to innovations in communications and information theory. There is already a significant range of bio/medical research activities within EECS, and these are helping us identify the knowledge and skills EECS graduates need to succeed and contribute in this emerging landscape.
Similarly, we believe the “nano” domain is important to the future of the Department and the field. Our future EECS SB and M.Eng graduates will need to be comfortable practicing the profession and innovating in an engineering environment whose behavior is dictated by nanometer dimensions. Promising new research fields such as quantum information and quantum computation are examples of quantum-based applications that might become practical, or might stimulate practical applications, in the not-too distant future.