1999: Eric graduates Stuyvesant Highschool and begins attending Brown University. At the time, he foolishly assumes that his affiliation with Brown will be limited to a mere four years.

2003: Eric graduates from Brown University with an Bachelor of Science in Applied Math/CS. In a shrewd attempt to avoid joining the workforce, or even pay for a U-Haul, he elects to remain at Brown and begins living with 9 of his yet-to-graduate friends. He also starts working for professor John Savage, securing his status in Brown’s directory as a “Class F Employee”.

2004: Eric is accepted to Brown’s PhD program and elects to continue working under Professor Savage as a computer science graduate student. Upon renewing his Brown Student ID, he immediately remarks on its absurdly distant expiration date: 06/01/10.

2006: Eric fulfills the requirements for a Masters of Computer Science and is admitted to PhD candidacy. Although he is awarded his Masters, he chooses to sleep in and skip the degree ceremony.

2008: Eric boldly relocates to New York City while continuing to work toward his PhD. The majority of his research-related discussions now take place between him and the cat.

2009: Eric’s proposed thesis, “Reliable Computing at the Nanoscale”, is approved! Completion of his third Brown University degree appears imminent.

2010: 9 agonizing months and 150 harrowing pages later, Eric sends out a finalized draft of his thesis to his thesis committee and schedules his defense for March 5th. He also relocates to Providence for his final semester in order to begin work with Professor Michael Black. He is enthusiastic about his new research area and extremely enthusiastic that he will not be re-renewing his student ID.

So there you have it. I’m back in Providence (at least for the semester), and I can now officially assert that my tenure as a Brown student has “spanned three decades”. I’m also looking forward to resumed blog posting (plus, the frickin’ olympics just started up again!)

The temptation, I suppose, is to compensate for my post-post deficit by rattling off a list of “personal updates” that account for the intervening 117 days. (Blogging aside: Lists generally lend themselves to blog posts. A blog itself is basically a poorly organized list. Slapping in some sublists creates the illusion of structure.) I will resist this urge, and opting to save these pearls for the impending swarm of summer blogging. (Second blogging aside: overly long posts are a blight on the casual blogger.)

Instead, I simply note that on April 28th my doctoral fate was all but sealed with the successful presentation of my long awaited thesis proposal. This strongly suggests that my thesis defense will take place in the fall, and that the up-and-coming fall semester will be my last at Brown. An extremely timely exit, since a delay of even a few months would permit me to make the dubious claim that “my tenure as a student at Brown spanned 3 decades”. At that point, I assume I’d be a lock for graduate student orator at my graduation ceremony next May, but my preference is still to acquire a PhD in time for my 10 year high school reunion (slated for Thanksgiving weekend).

With the uncertainty of my post-Brown existence drifting closer by the day, the need for a more regular blogging regiment is at an all-time high. Expect more updates shortly.

The most memorable—and as an 18 year old, inspirational—exhibition was the kinetic sculptures of Arthur Ganson (and fortunately for you, it’s still there). As an artistically inclined computer scientist who’s also a pretty good juggler, I’m essentially Ganson’s core demographic. Had Brown’s sculpture class been easier to get into, I think I would have produced similar works, but alas, it was not to be. For now, I continue to attend Brown, diligently focusing on the far less physical world of computer science. To that end, I just came across Arthur Ganson’s TED Talk, which I’ve embedded below.

For right now, I’m not even going to state this theorem, since understanding the theorem requires some background information. I’ll provide some of that background in this post, more next post, and then state the theorem in the third. Regardless, it’s not actually the statement of the PCP Theorem that’s important, it’s the consequences of the theorem. If you understand these consequences, you understand a lot of what theoretical computer science is about. Unfortunately I’ve never seen a plain English explanation of the theorem that is accessible to non-computer scientists. I’m hoping the next few posts will help fill this void.

The PCP Theorem, and complexity theory in general, is concerned with the resources required to solve certain problems. For example, how long does it take to multiply two numbers? Obviously if you do it by hand, it takes longer than if you use a calculator. What’s important, however, is that whether you use a pencil and paper, a calculator, or a super computer, the time it takes depends on the length of the numbers. Suppose you multiply two numbers with n digits each. Using the procedure you learned in elementary school, the amount of time it takes is going to be proportional to n². The same is true for a computer that has been programmed to use the same procedure. As I mentioned once before, faster approaches are known, but these approaches as well can be executed by computers and humans alike.

In computer science (and in other fields too) we often try to identify the fastest procedure, or algorithm, to solve a given problem. Usually algorithms are described by writing a computer program, but this is just a formality. Once a problem has been specified in terms of numbers, or symbols, telling a computer how to solve it isn’t too different from telling a person how to.

You can tell a person to “find Rhode Island on a map”, but you can’t program a computer to do this unless you first specify how the map, and Rhode Island, are represented. If, however, you have a list of cities and the distances between them, you can program a computer to find the shortest route that visits each of the cities. The key is that the problem has been well defined using symbols. In a computer, if you want to something with images (or sounds, smells, etc…), you need to first represent them using combinations of symbols.

So here’s the general story: If you study computer science, you’ll come across with a whole host of nicely specified problems. You’ll learn that a computer can be programmed to solve these problems. Once you get the hang of it, you’ll see that the steps a computer performs when solving these problems are basically the same steps a person would perform. As a result, you’ll understand that it makes sense to study how hard a problem is by determining how many steps it takes to solve, given its length. The main goal of complexity theory is to try to understand why some problems are fundamentally harder to solve than others. So far, this has proved difficult, but complexity theorists have identified many problems that they strongly suspect are hard to solve. In fact, if you could prove that any one of these problems is hard to solve, you would simultaneously prove that all of them are hard to solve, and you would win one million dollars. More on that next time.

Expanding existing public transportation infrastructure (particularly trains and subways) is often very expensive. Thanks to global warming and rising gas prices, these expenditures are increasingly worth while, but you can get even more bang for you buck when you simultaneously consider how relatively cheap technology can make existing public transportation work much better. Google Transit is just one example.

My favorite example is using GPS to track the locations of buses. This allows travelers to check bus/train locations, as well as expected arrival times, on the web or their phone. It also would allow transit systems to display the expected weight times at stops. Taking a bus or subway late at night, or in bad weather, is a lot more pleasant when you can time your departure so you don’t have to wait at a stop for 15 minutes.

Earlier this semester, some grad students and I boldly attempted to make this GPS-enabled future a reality. We submitted a proposal, as part of Brown’s initiative to curb carbon emissions, to get money to put GPS-enabled cellphones on select Providence buses. We would have used the GPS data, in conjunction with software my friends had already written, to display bus locations on the web and/or smart phones. We also would have allowed students to use text-messaging to find out what bus they should take to get somewhere, and when they should leave to catch said bus. In fact, we even pointed out that our highly-location specific services would be perfect for generating ad revenue to offset the cost of the GPS. Sadly Brown rejected our proposal, saying that our idea was too “business-like” (which I took to mean, “too well thought out and practical”).

In my home town of NYC, I’ve heard plenty of people complain about the high cost of expanding the subway system. I’ve also heard plenty of people complain that taking buses in outer boroughs sucks. I’ve never, however, heard anyone suggest, that NYC make the bus system better by 1) allowing people to know where buses are or 2) allowing buses to know where trains are, so they can time their arrivals and departures better. At the very least, why not put train information online? Does the MTA honestly not know where it’s trains are at any given time? Isn’t this information already on a computer somewhere?

Once the MTA put train location data online, websites such as hopstop would leap at the opportunity to integrate this data with their existing services. Even if they currently don’t know where their trains are, cell phone service is coming to subway platforms, so service providers will soon be able to use cell phone signals to provide this data. In short, what the MTA really needs is a computer science consultant.

I took a bunch of programming classes in high school, but when I got to Brown, I decided to avoid computer science. I had liked learning about algorithms, the fastest ways to solve problems, how computers worked, but I hadn’t always liked the personality of my fellow students. Basically, a lot of them were big nerds, and I could never get behind their enthusiasm for mastering Linux commands.

As a freshman at Brown, I took a logic class where I learned that certain easy to state problems are uncomputable, meaning no systematic set of instructions can be used to solve them. More importantly, I learned that many people study the science of computation without actually writing programmings. The next year I decided to give computer science another shot, and one of my TAs (my buddy Kevin) invited me to join his group independent study project on computational complexity. After that, I was sold.

I have never taken Adderall, but I have many friends who have. Molly Young’s essay (which is short, you should read it!) mostly describes her own experience with an Adderall-induced super work ethic. As Molly mentions (and Matt affirms), her experience is far from universal, but it is certainly representative.

It’s tough to find actual usage statistics, but Adderall XR (extended release) is currently Shire Pharmaceuticals best-seller, accounting for over $1 billion in annual revenue (for reference, 30 pills cost about $100). What’s more, Shire’s exclusive rights to the drug expire next year, so prices are likely to fall (although if Shire has its way, they’ll soon be a new ADHD drug of choice).

Having heard so much fuss made over sports related drug use, I was surprised to hear Randy proclaim Adderall use ethically acceptable. One questioner—Molly I believe— felt the same way. As she put it, “Marion Jones had to return all the prize money she earned while taking steroids. Should I be stripped of all the A’s I received for papers written on Adderall?”

Randy was quick to draw a distinction between sports, which are by definition competitive, and higher education, which is supposed to be about bettering oneself. Under this arguably idealistic view of higher education, taking Adderall unnecessarily does not force others to do the same. Simply harming oneself, Randy explained, is not unethical.

Most in the audience agreed that some students find college much more competitive than Randy’s answer acknowledged. At Brown, I doubt students are genuinely forced to take Adderall just to keep up, but I also wouldn’t be surprised to find a few students who thought they needed it for that reason. Also, even in a noncompetitive student body, widespread Adderall use has an impact on person’s college experience. This may not be a negative impact, but ethical or not, we need to start asking ourselves how many people we’re comfortable with taking Adderall.

If we’re not ok with performance enhancing drugs in sports (although Malcolm Gladwell thinks we should reconsider), it’s seems odd for us to be ok with them in everday life. And what about Adderall use on the job? Surely a fresh generation of Adderall enthusiasts aren’t going to give it up just because they’ve graduated. Should we be worried?

I personally am terrible at sitting at a desk and focusing on work. Still, I don’t see myself taking Adderall anytime soon to enhance my attention. I have been told that a well-known, long-lived, and particularly prolific mathematician, Paul Erdos, took amphetamenes later in life specifically to do math. I’ve also never heard anyone question the value of his work because of it. In the 20th century, Erdos was a rarity, but in the brave new world of tomorrow, there’s going to be a lot more folks at the top of their field who’s productivity and personality are directly dependent on the pills they’ve committed to taking.

One structure under threat was the Peter Green House. At 142 Angell Street it lay directly in the Walk’s path. Fortunately the house narrowly escaped in the nick of time, moving about 450 feet over the course of a week. That’s over 0.005 mph, breakneck speed for a 140 year old house.
You can see a time-lapsed video of the move here.

With the Peter Green House safe and sound at the corner of Angell and Brown, it the UEL Garden will likely be the Walk’s next victim. I’m told that on September 9th the garden will removed. Don’t worry though, it will be rebuilt soon after, no doubt redesigned by some well paid garden consultant. Goooooooooooo Progress!