Homepage of Armando Vieira

Professor, Entrepreneur, Data Analyst and Scientist

  • I’m an Entrepreneur, Physicist, Professor, Machine Learning Analyst & IT consultant. Passionate about Data and Analytics, Physics and Artificial Intelligence.
  • Fanatic R user and Python advocate for big data analysis. Focused in extracting value hidden in the data.
  • Deeply engaged  in applying Deep Learning to challenging problems: one of the pioneers in the field with this publication in 2000 and a more recent one on multimodal learning with Stacked Auto-Encoders.
  • Co-Founder and CTO of dataAI and Data Scientist at Redzebra-analytics.
  • In my spare time I’m a writer, cooker and “provocateur” of minds.
  • See my Linkedin profile and my Github repository for more details.

  • My researh

    Armando Vieira

    After my PhD at University of Coimbra, I spent a year in Grenoble, France, as a Postdoc. Then I decided to do something new.
    From 1998 to 2000 I worked on the Portuguese Nuclear Reactor at Sacavém, studying neutron diffusion and radiation protection.

    Since 1998 I fell in love with Artificial Neural Networks (ANN) and Machine Learning. I applied these techniques to any problems that I could put my hands on: from physics to economics or even deep oil discovery. We were able to successful apply ANN to several Rutherfod  BackScattering (RBS) spectra analysis of thin films and revolutionize the field of real-time RBS.

    In 2003, I was able to propose a new algorithm to train Neural Networks for classification problems and apply it to complex tasks, namely financial distress prediction of private French companies.

    In 2004 I took a Sabbatical leave at Los Alamos National Laboratory to engage in the study of Complex Network Analysis.  A topic that I eventually resume early in 2011 and in which I have a keen interest, especially in its applications to recommendation systems and correlated credit events (dominó bankruptcies). Early 2011 Tiago and I were the first portuguese team to be accepted at Seedcamp London, the biggest entrepreneurship meeting in Europe.

  • My Passions

    Data analysis, algorithms, machine learning, social networks, complexity.

  • My Education

    I had the privilege to take my degree of Physics, in 1990, at one of the best Portuguese engineering schools, Instituto Superior Técnico, in the beautiful city of Lisbon.
    In 1993 I took the master degree in Plasma Physics to study the hot plasma of the ISTOK tokamak using function parametrization. I moved to Coimbra in 1993 for my PhD in Theoretical Physics. Though I didn’t love the city, I got fascinated by the personality and character of Professor Carlos Fiolhais. The thesis was on fission of metallic clusters – building blocks of nanotechnology.

  • Teaching

    Beside being a full professor of physics at ISEP, I lectured on several international post-graduated degrees, like master in Bioinformatics in University Pompeu Fabra in Barcelona and at a MBA on real estate in ISEG, Lisbon.
  • My new project EDUKE.me

    O meu novo projecto Eduke.meUm exemplo de um curso que temos disponível:

    cloud para startups eduke.me




What’s wrong with AI approach?

There have been tremendous advances in AI and lots of buzz around the possibility of the singularity coming soon acclaimed by scientists like Kurzweil. Inspired by the success of Deep learning, the new kid in town that took the field by storm winning almost all machine learning...

Is Deep Learning capable to solve the AI puzzle?

Deep Learning is the buzz word of the moment. But can it revolutionize artificial intelligence as some suggests? There is good reason to be excited about deep learning, a sophisticated “machine learning” algorithm that far exceeds many of its predecessors in its abilities to...

Machine Learning for business is much more than number crunching

“We have build a marvelous model using Deep Learning!”. Sure, but what does it means when heading for production?  Does the data is as clean at it should? Is it available? At what cost? What are legal and privacy implications? How will customers react? Will decisions...

Early Steps of deep learning

I’m very thankful to Jurgen Schimdhuber for having cited my work on HLVQ on its excellent review as one of the predecessors of Deep Learning. It was published in 2003.

The Business side of Deep Learning

I’m very happy that any area of machine learning (aka, statistical inference and decision-making) is beginning to make impact on real-world problems. I’m also overall happy with the rebranding associated with the usage of the term “deep learning” instead...

Deep Learning: a revolution on the making

Deep Learning is here to stay. This is not another clever way to train machines in big data, it’s a revolution. Recent advances in deep learning methods have led to a widespread enthusiasm among pattern recognition and machine learning communities. Inspired by the depth...

Sensitivity analysis for Ad exchange

I’ve created a sensitivity analysis function using Sovan Lek  who developed the approach in the mid-1990s. The ‘Lek-profile method’ is described briefly in Lek et al. 19962 and in more detail in Gevrey M, Dimopoulos I, Lek S. 2003. Review and comparison of methods to study the...

Big data culture: It’s Not Just About Numbers

Today’s conversational buzz around big data analytics tends to hover around three general themes: technology, techniques, and the imagined future of a society in which big data plays a significant role in everyday life. Typically missing from the buzz are in-depth discussions...

Machine learning for SEO

Machine learning is going to be playing a bigger  role in SEO, and so I think it is important that we have a basic understanding of how it works.   Intro Machine learning is appropriate to use when there is a problem that does not have an exact answer (i.e. there isn’t...