Today, we visited the University of Nicosia to learn more about crypto block chaining, forecasting, data analytics, and pharmaceuticals. The concepts we learned throughout these lectures helped better our understanding to industrial engineering and supply chain management as a whole.

The CEO of the University of Nicosia was the first lecturer, explaining about crypto block chaining. He prefaced by explaining how this was the original main focus of the University of Nicosia, as they were the first University to offer this as a major and now lead some of the most precious schools such as MIT and Stanford. He explained that cryptocurrency and blockchain are extremely important to business practices. Blockchain offers the first centralized information database that has a trusted third party and no single point of failure. This allows for fully transparent business transactions and public knowledge of the company, which is sometimes not the best practice. Furthermore, being distributed on a base such as Bitcoin, transactions can be global and at any time during the day. This does not comply with the banking system, which is good in a sense if you need a payment to go through instantaneously. Overall, I believe blockchain has a lot of improvements to make before it is fully integrated into society such as improving their speeds and protecting more of the privacy of the business. Many businesses will shy away until most of their information can be made private therefore, this is an important improvement that needs to be made. This lecture was not incredibly appealing as it seemed like a strung-out idea.

Next, we learned about forecasting from a professor that was a very nice man. Forecasting is done by identifying patterns and relationships that are then extrapolated to create evidence-based predictions. For forecasting, simplification is key as it has been shown many times throughout the years. Three large forecasting seminars showed that the least complicated models often did better than the highly sophisticated models. Another thing to note is that this professor was not afraid to admit he was wrong within his field and explained that he has been wrong plenty of times before. With this being said he also asked the next professor if he got good sleep, as he arrived very late to the lecture. Although professor was great, I was not passionate about forecasting.

Finally, we learned about data statistics and machine learning. The general idea of data statistics is the art of converting information into structured information anyone can read about. The general algorithm of data science is to be descriptive, diagnostic, predictive, and prescriptive. Furthermore, this professor went into machine learning, the art of training a computer by feeding it data. Then the computer would be able to infer the next idea. This was fascinating as it had to do with AI and basically a dumbed-down version of how a computer learns. I would love to know more about this subject, specifically the AI portion.

We concluded our day visiting the pharmaceutical school. We went through three different stations. First, we viewed how pills were made through compression and then how they were tested. Next, we learned about gas spectrophotometry and its ability to distinguish chemical compositions of extremely complex solutions. Finally, we entered a protein synthesis lab, where we watched scorpion venoms become ligates and then spun them into proteins. This was invigorating and fascinating to watch these three parts of the lab, and then see it in real hand the next day. Overall, today we learned a lot about manufacturing, supply chain, and industrial engineering- thus being a good change of pace from the cultural visits.