This evening, I had a chance to go do some work with the Meaningful Science Consortium. The consortium is a group out of a few Chicago-based Universities that advocates teaching more science in inner-city Chicago schools. My task this afternoon was to grade some of the student projects, which were assigned in advance. For the chemistry project, they were tasked with inventing some kind of board game to help other students learn about the periodic table. For the physics project, they were to design a roller coaster and calculate the requisite numbers (i.e. velocity, kinetic energy, etc). The project that I didn’t grade but was the most excited about with the 9th grade biology project.
Their project was to design a school building in Florida, with certain guidelines (had to be three buildings, you have a predesigned plot of land, etc). Their primary constraint, was to not kill off a specific tortoise species that existed on this plot of land. The tortoise existed in a complex food network. The student’s goal was to place the buildings in such a way as to maintain the ecosystem while still constructing a functional campus. They had to develop an objective along with more “constraints” and “considerations”. Further, there were some additional tasks which are now escaping me. Basically, they couldn’t just drain the swamp and build the school.
My immediate response: Awesome! This is a computer science / operations research problem! Essentially, the students were tasked with writing a linear program; maximize some objective function with respect to (binding) constraints. Even more interestingly, their constraint involved a graph! With node dependencies! This is the kind of program that researchers who work in algorithm design or optimization struggle with every day — how can we design better algorithms and solution concepts for these problems? Even better, this is an interesting and applied problem that includes finding ways to protect the environment with human considerations. Academics sometimes forget the reason that they consider these problems in the first place; focusing on making “the numbers work” and forget about the interesting ways this research can improve the human condition.
I hope stuff like this inspires a new generation of students interesting in questions of optimization, algorithm design, and similar topics. We need more people thinking about these kinds of problems and developing new approaches.
Over the spring break, I’ve really been enjoying watching many of the videos from the TED conference. It would be such an honor to be able to go to that conference some time. I guess I better start writing!
They haven’t posted two talks from this year that I’m looking forward to: Stephen Wolfram and Moot. Wolfram is a scientist, author, and software developer. His talk will probably be interesting and I expect him to put in many plugs for Wolfram Alpha. Moot, on the other hand, is a the kid that started 4chan (NSFW). I have no idea what the hell he is going to talk about. Caturday? Memes? I can’t wait until his talk gets posted.
Anyway, as a bit of a secular humanist, here is the video I’ve enjoyed the most from the 2010 talks:
Just a few quick notes about the blog. First, I added recaptcha to the blog. Hopefully, this will allow me to have comments without getting bombarded with spam. I’m amazed at the amount of automated spam scripts that hit wordpress blogs. Second, there was another bug that wasn’t letting people add comments altogether. This should also be corrected. Finally, I did receive an email in response to my below post on Hans Werner-Gottinger, which should have been posted in the comments. It is from a faculty member at the University of Applied Sciences in Berlin:
Yes, this guy appears to have been quite a serial plagiarist. The book
you mention is not one of the 13 plagiarisms that have been identified
to date, but that does not mean that it is original. One should be very
careful when using materials from people who have been identified as
plagiarists one, and even more so for people who plagiarize more than once.
I don’t really think you can get $150 for the book
If you should find a source for this book, I would be happy to hear of
it. I’ve included a comment at Amazon.
Regards, –
Prof. Dr. Debora Weber-Wulff
So, if any of my readers stumble upon other potential plagiarisms from Gottinger, Professor Weber-Wulff is the one to contact. In the meantime, I’ll just hold on to this book and at least use it’s citations to direct me to other resources.
“Economies of Network Industries by Hans Gottinger – i think this guy was uncovered as a fraud last year, but great visual explanations nonetheless. netonomics. i was particularly interested in it during undergrad but i deemed it had no future. prospects for you look good? how do you apply it?”
I used this book in an independent study I did in my undergraduate days (pre 2007) and had no clue this guy was a fraud! More interestingly, I did some googling to find out more and stumbled upon this article in Research Policy. Gottinger was a serial plagiarist and even more, he was claiming to be from a Dutch University department that didn’t even exist! Subsequently, Nature published an interesting article on who this guy is. Even after reading the article, I still don’t quite understand who he was. Did he plagiarize everything or just some things? What works are his originals? Is this textbook his original work or was it copied too?
So, what do I do with this book? I could sell it on Amazon for $150.00 (it’s listed at that price, I don’t know if there are buyers). I don’t think I’ll ever be able to use it or cite any of the empirical data in it since this guy is a fraud. What is the academic protocol for this kind of thing?
Yesterday, I finished my semester project for my randomized algorithms course. I started the project almost a month in advance since I knew there was going to be a significant amount of research and reading to do. The original plan was to create a mathematica module for processing Exponential Random Graph simulations. The concept is this:
You have some observed social network, collected from data or in the field. You want to know things about the relationships of people in the network, like, how likely are people to form connections randomly or do they form connections based on other sociological things. For example, if Alice is connected to both Bob and Eve, is there likely going to be a relationship between Bob and Eve? In other words, do they complete the triangle? Standard random graph models can’t test for this but we can use exponential random graphs. The output of the algorithm is a set of values that indicate how strong various network structures are.
My presentation went alright. In the mathematical sciences (engineering, math, etc) proofs are the only method you can use to show something is true. In the applied sciences (communications, sociology, statistics) the only method you can use to prove something is statistical inference. So, explaining inference to engineers is difficult since they don’t encounter it (I think they should!). Explaining math to social scientists is challenging since they’re not familiar with proof techniques (what is the contrapositive again?)
I haven’t finished the paper yet (almost done) and I will post the results here shortly. In the mean time, I’ve compiled some of my thoughts about approaching this topic in the future. This is what I want to study (using computer science theory in other fields) so I am noting this for posterity.
Use more visualizations to explain inference. Mathematicians love proofs and it is ok to use math on your slides. However, when talking about statistical inference, you’re looking at how something observed fits something hypothesized. The best way to do this, I suspect, is to plaster a N(0,1) curve on the slides and point to where things fit.
For social networks stuff, use examples! I used a couple examples in my slides and people found it helpful and interesting. There are so many great visualization tools for social networks, so I should use them more.
Take a course on econometrics. I’m doing this next year. Econometrics is using statistical inference to reach economic conclusions. There has to be some good techniques they use.
Write the slides AFTER you write the paper. In this case, I was so worried about the presentation, I did it before I wrote the paper and ended up rushing the paper. Next time, I’ll flip it and spend time worrying more about visualizations and teaching people than plastering equations on slides.
