Teaching


This it the front page for the classes I teach, have taught or will teach. If you are interested in taking one of my classes I am looking forward to working with you. If you have any questions feel free to stop by my office in 276 Levine/GRW or send me an email. You might also find useful to read my thoughts about engineering education further down in this page. The classes for which material can be found in this site are the following (also accessible through the navigation menu on the left):

  1. Optimal Design of Wireless Networks. Offered in Spring 2010, 2011. Next offered in Spring 2012.
  2. Stochastic Systems Analysis and Simulation. Offered in Fall 2009, 2010. Next offered in Fall 2011.

I also organize the Penn Seminar on Communications and Networking. These seminars are held every semester and consist of between 6 to 8 talks. Depending on the semester the talks are given by our own students or by invited speakers.

Engineering education: Excitement, challenge and discipline gaps


A puzzling fact of life is the unwillingness of young people to pursue careers in engineering. Engineering connotes curiosity, ingenuity and improvement. Engineers are supposed to be curious to discover new problems, ingenious to solve them and ultimately develop things that improve our society. All of these connotations are strong emotional drivers. Curiosity is deeply embedded in human nature, the thrill of succeeding at solving a problem is certainly worth experiencing and the possibility of helping others is something that, maybe to different extents, we all find gratifying. While accepting that this is an idealistic romanticized conception, it is difficult to contend that it does not reflect reality to a reasonable extent. The question is then, why is it that there is this discipline with three clear routes to personal satisfaction, yet people are reluctant to commit to a career in it. For want of a better name, we refer to this dissociation as the excitement gap.

Since we are talking about gaps, two other gaps that deserve concern are the discipline and challenge gaps. The discipline gap alludes to the compartmental experience offered to college students and the reality of an increasingly hazy separation between disciplines. The challenge gap is temporal in nature and refers to the difference between the difficulty of the material that used to be taught in college and the material that is taught today. Both of these gaps go beyond engineering schools, cutting across the whole education system. In a May 2009 interview, President Obama stated that his "... grandmother never got a college degree... [but] her high-school education was rigorous enough that she could communicate and analyze information in a way that, frankly, a bunch of college kids in many parts of the country can't." He went on to say that we "got to make what’s learned in the high-school and college experience more robust and more effective.''

Closing the gaps

Part of the excitement gap is explained by social attitudes beyond the realm of what we can expect to affect. But another piece of the explanation is the way in which classes are taught in engineering schools. Yes, we have this enticing careers, the path to which goes through four arid years of college. This is somewhat widely accepted. In fact the challenge gap is, to some extent, an effort to reduce the excitement gap. Engineering education is perceived as difficult, therefore, we can broaden its appeal by making it more accessible. I think that the subtle distinction between difficult and arid is key. Classes are not per se difficult, just plain boring.

A rather opposite path is to make classes more difficult so that interesting applications can be covered. It is possible to reduce the three gaps, excitement, challenge and discipline, by creating courses that introduce challenging applications drawn from a variety of disciplines. The premise is that undergraduate students can grapple advanced level material if they can see how a particular piece of theory allows them to understand interesting problems. The approach is to use interesting applications to lead students into complex material. Drawing applications from different disciplines serves to provide multidisciplinary perspectives and to further motivate students by showing that seemingly unrelated problems are, in fact, similar.

An example

An attempt to address these issues is the class on Stochastic Systems Analysis and Simulation whose purpose is to introduce fundamental concepts used in discrete event simulations. The curriculum of the class revolves around applications of stochastic processes to communications, biochemistry, social sciences and economics.

As part of the class we study simulation of chemical reactions in biochemistry, where stochastic effects manifest because the number of molecules inside a cell is small. Interesting particular cases can be covered, e.g., the lac operon, a set of adjacent genes that form an auto-regulatory network to control the metabolism of lactose in some bacteria. Cells can only use glucose to generate energy, but they can reduce lactose to glucose if the latter is unavailable. To do this cells have to produce the enzyme $\beta$-galactosidase, which in itself requires some energy expenditure. Thus, production of $\beta$-galactosidase is only justified when lactose is abundant and glucose scarce. Production of $\beta$-galactosidase is controlled by repressor and promoter proteins. Upstream of the lac operon is a gene coding for a repressor protein that hinders mRNA transcription of $\beta$-galactosidase. When no lactose is present, the repressor binds to the operon thus interfering with mRNA transcription and resulting in low enzyme production. When lactose is present, however, the repressor binds preferentially to lactose therefore not interfering with transcription leading to increased production of $\beta$-galactosidase. The second part of the regulation involves the catabolite activator protein (CAP) that when bound to the operon facilitates mRNA transcription of $\beta$-galactosidase. The amount of CAP present is inversely proportional to the amount of glucose. Hence, enzyme production increases when glucose level decreases. When lactose and glucose are present this control mechanism results in a distinctive diauxie pattern with glucose consumed first and lactose processed after glucose is depleted.

We also study stochastic systems in social sciences covering, e.g., the random algorithm used by Google to rank web pages. Consider a web surfer that visits a page and clicks on any of the page's links at random. She repeats this process forever. What fraction of his time will be spent on a given page? The answer to this question is the rank assigned to the page. This ranking algorithm can be also used to study reputation in social graphs with persons in place of web pages and social connections in place of links. We use this algorithm in class to find the student at the center of the class's social graph. Applications from communication networks, e.g., wireless multiple access channels and economics, e.g., Black-Scholes's model of option pricing roundup the class's curriculum. As can be appreciated, the examples discussed above are quite complex, but chosen so that students can easily understand their relevance.

The class will be offered for the first time in Fall 2009. Outcomes of the experiment forthcoming in December 2009.