Homepage of Armando Vieira

Data Scientist, Entrepreneur and Speaker

I am an experienced Data Scientist, Speaker, Entrepreneur and AI Innovation Advocate.

I founded Lidinwise, a consultant company, to help companies take advantage of the opportunities of Machine Learning to leverage their data and create competitive data driven business. I work with big organizations, and Startups as well, as a strategic advisor and hands-on consultant.

I obtained a PhD in Physics and pioneered research in Deep Neural Networks back in 2000, with several publications in peer-review journals. I have extensive experience in machine learning and AI in international teams as lead data scientist and head of data science. 

More recently, I focus my efforts in helping organizations leverage the capabilities of machine learning and AI to become data driven and efficient. 

In my last book, Business Applications of Deep Learning, I discuss how AI will disrupt almost every business, from Banking to Medicine and the future of data driven organisations. 

I’m also interested in societal aspects and implications of AI and ethical consequences of decisions taken automatically by cognitive algorithms.
Pioneer in Deep Neural Networks with this publication in 2003 (cited in the recent review on Deep Learning by Jurgen Schmidhuber) and a more recent one on Applicationbs of Deep Learning in Biomedicine and Prediction of online user behaviour on an ecommerce site.

My book “Deep Neural Networks: Overview and Business Applications“. A summary in a format of book chapter is available here.

Screenshot 2018-03-04 07.55.32

My TEDx talk 13 March (minute 11):

My new book chapter “Digital Markets Unleashed“, By Springer, August 2017 – on applications of Deep Learning and AI in Banks.

More on my Linkedin profile or Github account.

Armando Vieira

Check my latest work based on conditional Generative Adversarial Neural networks (cGAN) applied to facade generation.

My video presentation on “AI, from a long Winter to a blossoming Spring“.

My presentation at EARL conference, London 2015:

Portfolio of Customers


Humans vs Machines… again

In a recent TED talk Gary Marcus pressed the point that Artificial Intelligence is still very far away from human intelligence — at most at the level of a 8 grade student while in other aspects below a 3 year toddler. He points, correctly, that what machines do is pattern...

Chief Data Scientist Forum – conclusions

I was recently invited to speak at Chief Data Scientist Forum. (See my presentation here). It was a very interesting event to discuss implementation of Data Science into organizations. Data Science brings huge opportunities, but making it work in established organizations is far...

The Art of Data Science

Data science is much of an art as a science. Building a model with top performance in clean datasets with well-defined goals is super cool. But the real test is dealing with the messy world, full of biases, dirty data, and fuzzy or unspecified goals. To survive you need more than...

Ethics in the age of intelligent machines

As machines become more advanced, the implications in business and society will be enormous. The unfold of interaction human-machine is hard to predict but one thing is clear: we will have to teach machines ethics. Teaching human ethics to a non-human entity is the challenge I...

Nassim Taleb Commencement Speech @AUB

Acute and inspirational. This is the type of people that I take lessons from. Speech by Nassim Taleb – Distinguished Professor of Risk Engineering, NYU May 27, 2016: “Dear graduating students, This is the first commencement I have ever attended (I did not attend my...

Why AlphaGo is a milestone but it still not achieved AGI

Congrats Google Deepmind. You did it! Top rank player of Go is no longer a human. Should we rejoice or fear this formidable feat? Is this milestone the start of the end game in the quest for Artificial General Intelligence (AGI)? My short answer is yes and no. First, some...

AlphaGo Part III

What is the problem in reaching AGI? Haven’t machines proved powerful enough to solve all hard problems we through to them: locomotion, playing games, driving cars, translation, even cooking. So, we are already there, aren’t we? No. The problem I see can be stated in...

AlphaGo – Part II

AlphaGo – Part (II) ANN research were confined to a few ghettos, most prominently, Geoffrey Hinton in Toronto, Yann LeCunn in New York, Yoshua Bengio in Montreal and Jurgen Schmidhuber in Losano. They worked hard to solve a fundamental problem in ANNs: how to train deep...

Open Source Libraries for Deep Learning

There are many open source libraries available: Caffe TensorFlow, Theano, and Torch.   Caffe is one of the first deep learning toolkit, started in late 2013, mainly used for convolutional neural network and still actively used. However, it doesn’t support recurrent networks...