ElectroEuro: A Virtual Coin that Enables the Exchange of Green Energy, Driving a Cleaner and Decarbonized Europe


In 2017, General Electric (GE), one of the largest American companies that specializes in oil and gas, healthcare, aviation and software development, and Eurelectric, the union of the electric industry in Europe, partnered to create an Ecomagination Challenge hackathon. Ecomagination refers to “GE’s growth strategy to enhance resource productivity and reduce environmental impact at a global scale through commercial solutions for our customers and through our own operations”. The focus was on building digital solutions to help decarbonize energy and transportation in Europe, and the hackathon was held in Berlin between June 12-13, where over 100 participants from around the world came together to compete on solving the two challenges presented: Electrification and Advanced Manufacturing.


For the Electrification challenge, the target was to come up with solutions where things are powered by electricity. Sample solutions span: renewable energy resource siting, electric heating and conversion to heat pumps analysis, electric vehicle charger siting and renewable energy integration. For the Advanced Manufacturing challenge, the goal was to optimize existing manufacturing processes. Sample solutions consist of: forecasting manufacturing delays based on parts complexity, detecting delay drifts, and optimizing critical production rescheduling. Both challenges sought solutions that drive the de-carbonization of Europe and the platform for both challenges was Predix, the industrial Internet of Things (IoT) platform.Predix is GE’s  software platform for the collection and analysis of data from industrial machines.


Our team competed in Electrification, which was considered to be the greater of both challenges.



Ira Blekhman, from GE Digital in Israel decided to promote the challenge and posted a notice about this on the Facebook page of FemTech, a community in Israel for women in technology with over 1000 members. Talia Kohen was the founder and CEO of FemTech, and when she saw the advertisement she immediately thought about Sheryl Sandberg’s words: What would you do if you were not afraid,” and decided to join her first competitive hackathon and serve as the CEO of her team! Talia is a masters student at Bar Ilan University in Computer Science (and Cornell alumnus), and was a finalist for the Anita Borg Scholarship. Talia was also a Microsoft Woman of Excellence and a Google Outstander. She hopes to one day serve as the CEO of her own startup.



The formation of her team was a bit unorthodox. Before she formally selected the other members of her team, Ran Koretzki, a graduate student at the Technion in Computer Science in Israel asked to join her, and they were the original core of the team: truly a Cornell-Technion alliance. Ran, whose technical experience includes summer internships with both Google and Facebook, served as the team’s CTO and developed most of the solution’s technical architecture.




Talia then added Idan Nesher, a UX designer to the team, knowing that the key to winning is a compelling presentation. As much as architecting an energy bank and virtual currency system would win the hearts of the judges, the presentation would need to be at the same professional level.  Idan studied product design at the Avni institute in Tel Aviv, and subsequently moved to Berlin and started to work as a freelance designer. He dove fast into the user experience design (UX) world, believing that UX will be the future of all products since it is centered about innovation.


She added two other developers to the team who would be able to do front-end development in order to have a live demo ready to show at the hackathon, since seeing is believing: Haim Bender and Isaack Rasmussen. Haim, like Ran and Idan, came from Israel.  He studied Math and Computer Science at Tel Aviv University. Isaack, the only non-Israeli on the team is a software developer with more than a decade of experience, originally from Africa and now residing in Denmark.


Talia was privileged to have been mentored by another masters student at Bar Ilan, Micah Shlain, who taught her the principles of software development, and it was through this process that she was able to guide her team from idea to design to implementation.


We designed a  decentralized virtual currency known as the ElectroEuro for trading energies through an energy bank in Europe, driving a low carbon economy.  The use of the greener energies would promote decarbonization, and the monetization would make it accessible and practical. The concept was to unite Europe through electricity like the Euro. This currency is similar to BitCoin in that it is universal and there is a finite quantity of it. The transaction of energy is carried out through it, and it can be bought through goods that do not promote carbonization.


The energy bank consists of eight sources of energy ranked by the green-factor and stability, respectively.  The price of the energy is based on two metrics: 1) the distance to transport the energy (a fixed price), and 2) the quantity.  A market is generated based on the surplus of energy per country and per energy source. Machine learning is used to predict consumption, production, and cost, through a set of sensors that detect features for each type of energy. For example, a set of sensors detects weather and this goes into the prediction of the availability of solar energy. The other features include: location, cost of operation, availability, difficulty of harnessing, volume, waste, risk, failures, pollution, volume, and cost of production.  There then is an intricate bidding process performed on an interval where green and stable energies are promoted. The machine learning, which is the core logic of the system, is implemented on Predix, and the rest is still in the design phase.


This solution offers significant technological benefits: hybridization, mobility, decentralization, big data optimality, and efficiency. Hybridization is achieved through combining different energy sources. Mobility is realized through creating a mechanism that allows one to obtain energy through a nearest neighbor EU country rather than through OPEC.  Decentralization is in place because of the virtual currency, and it causes a free market to be generated. Big data optimality is materialized through a large sensor network which generates ample data for analysis. Lastly, efficiency is achieved through the big data that is collected that allows for replacing or moving resources throughout a network.


Additionally, it offers political and economic benefits: makes green energy cheap, generates a free market, promotes production driven by revenue, and promotes autonomy for individual countries. The green energy is more affordable, because there is a concerted effort to make it easier for both the producer and the consumer. For the consumer this means: lowering the price of green energy, creating flexible trading rules, and allowing for delayed payments. For the supplier this entails: forgiving debts, issuing small loans and imposing penalties for trading polluting energies. A free market is generated because there is less reliance on OPEC. Additionally, unlike OPEC, where production is heavily driven by politics rather than by being centered around revenue, this configuration is less politically driven and more idealistic. Lasty, countries are more autonomous than under OPEC. OPEC regulated countries very strictly: it penalized countries that under-produced by limiting their negotiation power, and fined countries that overproduced.  Every country individually was inclined to cheat by discounting its prices and exceeding quotas.


We presented a pitch at the Hackathon on a boat to a panel of judges, and several hours later, near the conference venue for Minds + Machines (which was walking distance from the boat) we found out that we won first place, in Electrification, which is 10K Euro for the team! Everyone was surprised and delighted at the same time. We also found out that we won 3K for second place in the category of Predix development.




We further won up to 10K for travel expenses to Portugal for the Eurelectric conference to present our winning solution.  This project was slated to be a one-off, but GE is interested in continuing to support it to see it validated and developed.

The reign and modern challenges of the Message Passing Interface (MPI): A discussion with Dr. Torsten Hoefler.

A few years ago, while I was a graduate student in Greece, I was preparing  slides for my talk at the SIAM Parallel Processing 2012 conference. While showing my slides to one of my colleagues, one of his comments was: “All good, but why do you guys doing numerical linear algebra and parallel computing always use the Message Passing Interface to communicate between the processors?”. Having read* the book review of Beresford Parlett in [1], I did have the wit to imitate Marvin Minsky and reply “Is there any other way?”. Nowadays, this question is even more interesting, and my answer would certainly be longer (perhaps too long!). Execution of programs in distributed computing environments requires communication between the processors. It is then natural to consider by what protocols and guidelines should the processors communicate with each other? This is the question to which the Message Passing Interface (MPI) has been the answer for more than 25 years.

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Convolutional Neural Networks (CNNs): An Illustrated Explanation

Artificial Neural Networks (ANNs) are used everyday for tackling a broad spectrum of prediction and classification problems, and for scaling up applications which would otherwise require intractable amounts of data. ML has been witnessing a “Neural Revolution”1 since the mid 2000s, as ANNs found application in tools and technologies such as search engines, automatic translation, or video classification. Though structurally diverse, Convolutional Neural Networks (CNNs) stand out for their ubiquity of use, expanding the ANN domain of applicability from feature vectors to variable-length inputs.

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CHI 2016: Global, Diverse, Good

What can a 1000 scientists achieve when they invest one hour doing voluntary work?

At the heart of Silicon Valley, the CHI 2016 conference broke through new ceilings. CHI (pronounced kai) is the most prestigious international conference in the field of human-computer interaction (HCI). It attracts researchers, designers, engineers, and artists who want to (re)shape technology and media to enhance people’s quality of life. This year, the conference took place in San Jose, USA. Over 3,800 participants from 52 countries presented their work in various media formats, including keynote presentations, media installations, interactive demos, and posters.

In the opening keynote, Dayo Olopade, a Nigerian-American journalist and author, portrayed the challenges she faced moving from the USA to Nairobi, and how the demographics and culture of different countries are unique and should be taken into account in the design of new digital tools. Dayo took the audience on a voyage to Africa where she slowly dissolved the western lense allowing them to see the chaotic, desperate Africa reveal its unconventional systems as an efficient act of “kanju”, a term which refers to the creativity that comes out of African difficulties. Continue reading

R software and tools for everyday use

Long, long time ago … I started with Octave and Matlab.They were amazing and allowed me to solve a lot of interesting problems in my research. I loved the command window of Octave, but I needed the productivity an IDE gives when developing complex calculations. None of the available IDE’s for Octave were not as powerful as the Matlab IDE. The problem was that Matlab was not GNU and buying a license was very expensive. Then, I found R and I realized that none Octave neither Matlab were the tool I needed for my research. I needed advanced project and file management through repositories, fast data manipulation, an easy way to export my calculations, a creative way of authoring reports and a powerful IDE that let me access my beloved command window. Now R gives me all I need and is an important part of my everyday toolbox. For those who does not known R, I must say that R is a well known programming language that is widely used on mathematics, economy, biology… Its main benefits includes the ability to work easily with statistics and data manipulation. R is very popular on academics and research, is GNU, very powerful and have a lot of packages that allows do magical things in a few clicks or with a few commands.

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