My name is Andrew Polican and I'm going to be Junior at Arizona State University next semester.

I'm studying Computer Systems Engineering and am loving it so far. As far as hobbies go, I'm pretty into programming, table tennis, and reading. Also, sending emails to Nigerian scammers, but that's a long story.

Day 0

As I'm writing this, I have been checked into the dorm for 5 hours and have not seen any other researchers. I'm secretly starting to wonder if this is all an incredibly elaborate practical joke and my friends are laughing at me behind a two way mirror. Or perhaps there was some sort of Internet of Things party that I wasn't invited to. To pass the time I've been listening to podcasts and walking around campus, but then it started raining so I've just kind of been stuck here. Room's smaller than I expected but it is a dorm so I can't really complain. Put away most of my stuff and set up my desk which happens to be awkwardly close to a bed so the chair is basically pinned against the front of the desk.

Day 7

Heard a lot of talks this week. I think every faculty mentor gave a talk about their research or something that we needed to know for ours. It is quite a bit of information to take in, but I've been enjoying it a lot. I feel as if I've learned more in the past week than in my entire previous semester.

The first talk was by Molly O'Neil on what academic and instustrial research are like and how they are conducted. What I mostly got from the talk is that research is a very active process. Seems like researchers have to constantly keep up with each other's work and always look out for new solutions for their problems. I honestly find the idea quite appealing. It does look like it would be a lot of work, but I think that would be ok as long as the problems were sufficiently interesting.

The next talk was by Dr. Metsis regarding Data Mining. He described how to use a machine learning tool called Weka to perform different data mining tasks and demonstrated they different ways that algorithms worked. He also described the process of cross validation and the pros and cons of alternative software such as Matlab and Octave.

Dr. Ngu then gave a talk about IoT and it's place in the development of the Internet. Turns out, IoT originally referred to the ability for us to track physical objects using RFID tags, but it grew past that with the creation of BTE, Wifi, smartphones, ect. She talked about how disruptive IoT is and could potentially be in the future and all the different domains that could be improved and influenced by it. That also comes with many concerns such as privacy, infrastructure, security, and usability.

Dr. Gao spoke to us about database work and its role in data mining. Databases were one of the original uses for computers and are only growing in usage. The massive amount of data that we have now necessitates consideration for how to store it as well as how to mine it for useful patterns and trends. Data mining is a relatively new field so there is abundant opportunity for research in that field. Its newness also means that many of the tools needed do not exist so many must be written from scratch in C++.

Dr. Lu spoke about how machine learning is going to influence the future, such as self driving cars, computer vision, ect. She also went over many different algorithms that are used for extracting relevant features in data and how those can be applied.

Finally Dr. Zare spoke about his work in Bioinformatics. Namely his research in using machine learning to predict the progress of AML and MDS via the expression of certain groups of genes. Of particular interest was his description of Principal Component Analysis. I know that it's not exactly the main part of the research, but I thought that it was very interesting how he was able to extract only the relevant information out of a data set with so many dimensions.