Today, we visited UNIC for the last time. Our schedule was packed with lectures on blockchain and crypto technologies, data forecasting, and machine learning. UNIC offered the first degree program in blockchain technology, and are advisers to the EU Commission and the Central Bank of Europe on the subject. I learned that my perception of the technology was very wrong, and that the major draw of Blockchain is that it is decentralized. Examples of other decentralized things we use today are email, while examples of centralized things are Twitter and Amazon. Once a service is centralized, one person makes decisions regarding what is allowed on the platform. We are finding that the resistance to Blockchain is a repeat of when the internet was first introduced, which was a major form of decentralized information. People resist what is foreign and they have not seen before. 

A possible application of Blockchain is in the healthcare industry. The current system of healthcare databases is very inefficient. At Pitt, a possible Industrial Engineering concentration I am interested in is health systems engineering, which this is reminding me of. There are so many ways our healthcare system can be optimized, and it is likely blockchain will be an important part of this in the next few decades. 

We also had a lecture on supply chain and data forecasting by an expert in the field. Some key roles in data forecasting in supply chain management are demand planning, inventory management, production planning, and transportation and logistics planning. In a supply chain, forecasting can be very beneficial when knowing what to make, how much to make, and when to make it. Having accurate figures for these will cut costs significantly and make the supply chain run smoothly. We learned that data forecasting has a long and ever changing history, with three major developments. The first was statistical forecasting (1959), which uses trends in data to make predictive models. The second is Hybrid (2018) which, as the name suggests, is the hybridization of using multiple types of models together. The third is machine learning (2020), which allows for the use of  hundreds of methods at once to produce the most accurate models. 

Next, Dr. Trihinas gave a lecture on big data management and processing, a very important aspect of supply chain management as well as Industrial Engineering. He states that data is useless until it is converted into “structured information to gain new insights”. No model is 100% accurate, but the goal is to get as close to 100% as possible. We learned more about machine learning, and how it is unique because it had the ability to learn to accomplish certain tasks without being specifically told. This is a very promising and valuable technology in the field of supply chain management because data forecasting is very difficult to do as there are a multitude of moving parts and not everything can be predicted using previous trends. 

After the lectures in UNIC’s main campus, we were transferred to a UNIC lab building. What I found interesting was that, in every company we have visited so far (mostly shipping), the location of Cyprus has been an asset because it is in the crossroads of Europe, Asia and Africa. However, this does not hold true for the pharmaceutical industry. This is due to the fact that this makes it more difficult to attract partners and investors because there are not many in Cyprus, so they have to look abroad.