If you are interested in pursuing a PhD within the Web Science and Social Computing Research Group at UPF, first please read carefully the information about our PhD Programme in ICT, particularly with respect to admission requirements.

Option #1: INPhINIT Programme / Deadline: 1 february 2018

"La Caixa" foundation offers an attractive program of scholarships. You can apply to do a PhD at our group through this scholarship, by selecting the ETIC from UPF as the research center where you will do the PhD.

More information and application materials »

Option #2: DTIC Fellowships / Multiple deadlines

Deadlines: January 15th, 2018; March 5th, 2018; April 19th, 2018; June 1st, 2018 - see the calendar for 2018-2019

The DTIC also offers fellowships for PhD students, following the same calendar. Please, before applying through the official form, fill-in this form for expressions of interest. We review expressions of interest on the 1st of every month.

Decisions that are partially or completely based on the analysis of large datasets are becoming more common every day. Data-driven decisions can bring multiple benefits, including increased efficiency and scale. Decisions made by algorithms and based on data also carry an implicit promise of "neutrality." However, this supposed algorithmic neutrality has been brought into question by both researchers and practitioners.

Algorithms are not really "neutral." They embody many design choices, and in the case of data-driven algorithms, include decisions about which datasets to use and how to use them. One particular area of concern are datasets containing patterns of past and present discrimination against disadvantaged groups, such as hiring decisions made in the past and containing subtle or not-so-subtle discriminatory practices against women or minority races, to name just two main concerns. These datasets, when used to train new machine-learning based algorithms, can contribute to deepen and perpetuate these disadvantages. There can be potentially many sources of bias, including platform affordances, written and unwritten norms, different demographics, and external events, among many others.

The study of algorithmic fairness can be understood as two interrelated efforts: first, to detect discriminatory situations and practices, and second, to mitigate discrimination. Detection is necessary for mitigation and hence a number of methodologies and metrics have been proposed to find and measure discrimination. As these methodologies and metrics multiply, comparing across works is becoming increasingly difficult.

We have created a new website, where we would like to collaborate with others to create benchmarks for algorithmic fairness. To start, we have implemented a number of basic and statistics measures in Python, and prepared several example datasets so the same measurements can be extracted across all of them.

We invite you to check the data and code available in this website, and let us know what do you think. We would love to hear your feedback: http://fairness-measures.org/.

Contact e-mail: Meike Zehlike, TU Berlin meike.zehlike@tu-berlin.de.

Meike Zehlike, Carlos Castillo, Francesco Bonchi, Ricardo Baeza-Yates, Sara Hajian, Mohamed Megahed (2017): Fairness Measures: Datasets and software for detecting algorithmic discrimination. http://fairness-measures.org/

Both right-wing (PP, Cs) and social democrats (PSOE) are suggesting to suspend Catalonia's autonomy and replace their government. People don't seem to remember what happens when you replace a government by force.

Well, I do:

  • People die
  • People are injured
  • People go to jail for years; not only their leaders
  • Common people are written into loyal and disloyal lists that determine their options and those of their family
  • Newspapers, radio, television, give you a very homogeneous message, those who deviate go to jail
  • Misterious caches of weapons or money are found in the houses of the disloyal, who then go to jail
  • Those inclined to violence on both sides exercise it in various ways, none of them pleasant
  • Divisions, hatred, and injustice persist for generations

Please, don't follow that path, and don't endorse those who want to follow that path - the end doesn't justify the means.

The PhD Grind (2012) by Philip Guo is a must read if you want to do a PhD in Computer Science. Even if you're already doing one, I definitively recommend it. It's a first-person account of how it was for the author to complete a six-year PhD at Stanford. Basically all of the obstacles that the author had to overcome during his PhD, are things that either happen to all of us, or that I've heard many times from PhD students. Read this. It's a very short free book that articulates well some of the common negative experiences of PhD students -- and what you can learn from those experiences.

If you are already doing your PhD, specially if you're in your last years, read A PhD Is Not Enough (2nd ed, 2011) by Peter J. Feibelman. Again, it's a short book, that focuses on the transition from PhD student to tenure-track professor to tenure. It has tons of great concrete advise and tips.

Finally, a very comprehensive book is The Professor Is In (2015) by Karen Kelsky, which is really a career guide for academics. The author, a former tenured professor and department head, maintains a popular blog on the subject, and professional career counseling/coaching services. Her approach, as she admits openly, has neoliberal tones: this is a competition that you want to win, however, the author also gives a very reasonable justification as to why this is a good mindset to approach some key career steps. The book is a really detailed guide that covers basically every aspect of an academic career, starting with choosing a PhD advisor but going well into valuable tips for those holding a more advanced or tenured, position.

My advise: read all three, starting with the first one which is shorter.

Bonus: slides by José L. Balcázar on doing research, publishing, writing, defending, and applying for grants.

I am currently looking for students interested in pursuing a PhD in Information and Communications Technology at Universitat Pompeu Fabra in Barcelona, under my supervision, starting October 1st, 2017. My topics of interest are social computing, crisis informatics, news, and social media, plus all kinds of computing applications that address issues of social significance.

General information links:

You can apply using the above links. Your application has a higher chance of succeeding if accompanied by a recommendation letter from a potential advisor for your PhD thesis.

If you would like me to be your advisor, please fill this Expression of Interest (by August 4th, 2017) -- DEADLINE PASSED, FOLLOW ON LINKEDIN OR TWITTER FOR THE NEXT ONE.


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