Not a complete write-off

One thing I profoundly believe is that if you're doing serious work you should never, ever, be afraid of being evaluated. And you should evaluate yourself harshly; for the world is a competitive place and you can always push yourself harder.

Well, maybe not always — having worked alongside Douglas Hofstadter, I confess I am not capable of pushing myself as hard as he does. So, when it comes to a world class genius like Hofstadter, I cowardly throw in the towel, like a boxer who has taken such a beating he is ready to go to a higher place if only the beating will stop…

Yet I have decided to take the day to make a self-evaluation of my academic career at the business school I work for. In the following graphs I will only consider my performance against the Full Professors of the business school. (The data was collected in Dec 15.)

So here we go:

Figure 1. That first bar on the left is me; the other bars are the ten full professors of the school. Having worked for 16 years at the school, I'm placed alongside them right in the middle: above 5 and below 5 full professors.

Figure 2. Number of Masters Students Advised. Again, in this graph and in all the others, the bar at the left represents my work, and the other bars represent the work of the full professors of the school (note the obvious: if the number of Master Students advised is zero; we do not get a bar — hence the empty space). Since the date this data was collected is December 15, it doesn't include the latest students who have defended theses this year; neither for me or for the full professors. Here I stand below 5 full professors, and above 5 of them.

Figure 3. Number of PhDs advised. Here I stand, again, right in the middle. This data, again, does not include the defended thesis of Dr. Rodrigo M. Cunha, which defended in 2016, nor the scheduled thesis from ABD candidate Daniel M. Chada, neither any 2016 data from the full professors.

Figure 4. Journal papers. I only include serious publications — both in this graph and below. That means publications indexed in the most restricted scientometrics database: The Institute of Scientific Information (ISI. If there is an even more rigorous database, I will be all up for it. But hey, while there isn't, this data isn't so bad: it seems I'm in the top-3 when compared with the full professors of the school.

Figure 5. Citations in, again, the most rigorous scientometrics database: ISI. It's very easy to defraud citations, in, say, Google Scholar. Here again the picture isn't so bad: When compared to the full professors, I stand at position 4. (The empty space represent professors with zero ISI citations).

Figure 6. Median impact factor of the journals. One can have a large number of publications in garbage journals, but, when the impact of these journals is considered, you have to make it — it's just not possible to fake it. Here I'm pretty happy: standing at position #2, I am only beaten by the brilliant Dr. Andrade. Definitely in good company.

Figure 7. H-factor in ISI. Again, here I am tied to Dr. Andrade (at least for now…). Good news: I Guess I'm not a complete write-off. I am definitely in good company!

Here are the Journals (ISI only) in which my students from EBAPE have published. Some had put my name on their papers, but I asked them to withdraw it, for I had not contributed significantly to their work. Congrats to them… these are some of the students I'm truly proud of having worked with.

Journal of Air Transport Management
Cognitive Science (2 papers)
PLoS ONE
Frontiers in Human Neuroscience
Transportation Research: Part E
Cognitive Systems Research
New Ideas in Psychology (2 papers)
Physica A

Having looked at this… one must reflect… and though no other professor has had some many students publishing in high-quality journals… the first thing that comes to mind is that I think I could have done better in these usual Academic standards.

But I believe in the Stanford Model: universities should not only train people to the "salary class", but also to the "investment class". "Salary class" students go to work for a nice place, such as BNDES or Petrobras. But they do not create vast new wealth and innovation (on average).

Stanford University is, in large part, working to train "investment class" students. It has produced so many world-class companies that it's hard to keep track of. Here are some from the back of my mind, without consulting anything: Hewlett-Packard, Nike, Yahoo!, Cisco, Snapchat, SUN (originally an acronym for Stanford University Network), Silicon Graphics, Pulse (purchased for $90 million), Instagram, Google, Trulia (bought by Zillow for $3.5 billion in July 2014), Coursera, &tc.

What is going on at Stanford? Don't expect to find an answer from politicians; don't expect to find an answer from journalists; don't expect to find an answer in the ridiculous, pseudo-scientific journals of the "Academy of Management"… Why aren’t people with audacious, ambitious, ideas being laughed at in Stanford? Why are there students who actually get trained for “Investment Class”, not “Salary Class”?

So I have dedicated all these years towards Computational Cognitive Science & Artificial Intelligence (2000 — ), and Cryptocurrency (2010 — ), most of the time being laughed out of the room by other professors who would ask the "WTH? question" — "what does this have to do with a Business School?" How many times have I heard that? I don't know; for I stopped counting 10 years ago.

Here I must personally thank Prof. Bianor Cavalcanti, whom I have asked to meet, ages ago, on a Sunday, then asked him to let me focus my work on the Cognitive Sciences, and he, against all prevailing wisdom and trusting me personally, gave me the go ahead. I will be forever grateful to him and I hope that I will be smart enough to treat those "below me" with the highest standards that he has shown me.

My response to the aforementioned "WTH question" is that this work, even if laughed at and shamed by some, is what brings my research group to visit Google Research, YouTube, Yahoo!, Facebook, Dropbox, Paypal, &tc… Even if one school of business does not understand it, Silicon Valley understands it.

And yes, our little group has created solid wealth, even if, for now, it's unevenly distributed. Whereas the probabilities are stacked against us building a billion-dollar tech giant… just as they are for everyone else… we're just getting started — and from the solid wealth we have created we will create vast wealth.