Electrical Engineering Distinguished Lectures

Kristina Johnson

Tuesday, March 10, 2015 - 4:15pm to 5:30pm

Hewlett 201

Will Clean Energy Take Our Economy to the Cleaners?


In 2009 when the Obama-Biden ticket was inaugurated into office, they set out to accomplish the following aspirational goals:

  • Implement an economy-wide cap and trade systems to reduce U.S. Greenhouse Gas Emissions by 83% of 2005 levels by 2050;
  • Save more oil than we import from the Middle East and Venezuela by 2019;
  • Ensure 10% of our electricity comes from renewables in 2012 and 25% by 2025;
  • Put one million Plug-In Hybrid Vehicles on the road by 2015;
  • Create five million jobs by investing $150 bn over ten years to catalyze private efforts to build a clean-energy future.

And in the 2011 State of the Union address, the President put forth a goal to reach 80% clean electricity by 2035. The Office of the Under Secretary for Energy at the US Department of Energy put together a plan to realize these goals, along with the cost of attaining 80% clean electricity by 2035. In this talk, I will summarize this plan, called the "Strategic Technology Energy Plan (STEP)" as well highlight the unique role of run-of-river and pumped storage hydropower in STEP.


Prior to founding Enduring Hydro in 2011, Dr. Johnson served as undersecretary at the Department of Energy in Washington, D.C. from May 2009 until October 2010. Before her appointment as undersecretary, Dr. Johnson was provost and senior vice president for Academic Affairs at the Johns Hopkins...  read more »

Eero Simoncelli

Tuesday, August 20, 2013 - 4:15pm

David Packard Electrical Engineering Building, Room 101, 350 Serra Mall

Recovery of sparse translation-invariant signals with continuous basis pursuit


We consider the problem of decomposing a signal into a linear combination of features, each a continuously translated version of one of a small set of elementary features. Although these constituents are drawn from a continuous family, most current signal decomposition methods rely on a finite dictionary of discrete examples selected from this family (e.g.,a set of shifted copies of a set of basic waveforms), and apply sparse optimization methods to select and solve for the relevant coefficients. Here, we generate a dictionary that includes auxilliary interpolation functions that approximate translates of features via adjustment of their coefficients. We formulate a constrained convex optimization problem, in which the full set of dictionary coefficients represent a linear approximation of the signal, the auxiliary coefficients are constrained so as to onlyrepresent translated features, and sparsity is imposed on the non-auxiliary coefficients using an L1 penalty. The well-known basis pursuit denoising (BP) method may be seen as a special case, in which the auxiliary interpolation functions are omitted, and we thus refer to our methodology ascontinuous basis pursuit (CBP). We develop two implementations of CBP for a onedimensional translationinvariant source, one using a first-order Taylor approximation, and another using a form of trigonometric spline. We examine the tradeoff between sparsity and signal reconstruction accuracy in these methods, demonstrating empirically that trigonometric CBP substantially outperforms Taylor CBP, which in turn offers substantial gains over ordinary BP. In addition, the CBP bases can generally achieve equally good or better approximations with much coarser sampling than BP, leading to a reduction in dictionary dimensionality


Dr. Simoncelli is a Professor of Neural Science, Mathematics, and Psychology at New York University. He began his higher education as a physics major at Harvard, studied mathematics at Cambridge University for a year and a half on a Knox Fellowship , and earned a doctorate in electrical...  read more »

H. Tom Soh

Wednesday, October 9, 2013 (All day)


Cell Sorting and Directed Evolution in Microfluidic Systems


Current techniques in high performance molecular and cellular separations are limited by the inherent coupling among three competing parameters: throughput, purity, and recovery of rare species. Our group utilizes unique advantages of microfluidics technology to decouple these competing parameters by precise and reproducible generation of separation forces that are not accessible in conventional, macroscopic systems. In this seminar, we will first discuss novel high performance electrokinetic, magnetophoretic and acoustophoretic separation systems to purify rare target cells from complex mixtures. Next, we will discuss our recent work in applying the microfluidic separation systems for Rapid Directed Evolution of molecules (RDE). We will provide theoretical and experimental evidence for extremely fast generation of affinity reagents –molecular recognition elements that bind to target molecules with high affinity and specificity. Finally, we will present innovative methods of evolving molecular machines that are capable of performing complex functions, including binding induced conformation change and switching.


Dr. Soh received his B.S. with a double major in Mechanical Engineering and Materials Science with Distinction from Cornell University, and Ph.D. in Electrical Engineering from Stanford University. Prior to joining UCSB in 2003, Dr. Soh served as the technical manager of MEMS Device Research...  read more »