First Month
The first four weeks of this Caltech Stem class have been interesting, to say the least. Much of the material we went into have been all over the place with various objectives. We started off with teamwork exercises, watching college students present their research, replicating one for ourselves, writing a concept map, and going to Caltech to meet Dr. Hassibi.
We had two, teamwork workshops for the first two weeks. One of which was the dominoes problem where each student was given two dominoes and we were instructed to get three dominoes per person by exchanging dominoes for chips and chips for dominoes. Instructions were very vague other than that everyone must have a domino to "survive" a round. We struggled in the first few attempts but through several days of discussion and trial & error, we were able to find a way to accomplish our goal. Some key underlying goals of this exercise were the importance of leadership, communication, and open-mindedness.
Soon after Matthew, Jeffrey and I were given 6 dices and the task to reason how many polar bears there were and how many of them were fishing. Each time we gave reasoning backed with evidence; we were then thrown with several other questions that seem impossible to infer. This entire activity is extremely vague but vague with a purpose. While there was no answer to the series of questions, it taught us that, much like with research, all claims must be supported with concrete evidence and reasoning for them to be valid.
After getting introduced to what research may be like, the Caltech Stem class split into their respective subjects. Me, being in the Machine Learning group, and my peers were given the task to create a "Battlebot" with Cubelets, small cube-shaped modules that could connect to each other, that would eventually compete with the Algorithm group's robot. We encountered multiple issues such as connectivity problems. Throughout our project, we documented each step in a research paper format. By the end of the experiments, every student was able to effectively run researches and write papers about them. Below is a video that gives a brief explanation of what Cubelets are.
We have done a lot to understand how to think like a scientist and were eager to meet our professors. However, we needed to get a tenacious grasp on machine learning key concepts. We split and assigned our group of 6 people to 6 different topics: K-means clustering, linear regression, logistic regression, decision trees, neural nets, and naive Bayes classification. I was given neural networks which is a method of machine learning where there are layers of nodes that are dependent on each other, passing information downline until an expected/unexpected result is returned. Below is a series of videos that explain neural networks.
On Thursday, the machine learning team went to Moore Laboratory at Caltech to meet with Dr. Babak Hassibi, a renown electrical engineering professor researching in communications, signal processing, and control. Unfortunately, our meeting was 30 minutes long and consisted of introductions from each student, it was still humbling to meet with our professor.
A month has passed with the rest of the school year left. We at the Caltech Stem program are incredibly grateful for this opportunity and eager to learn as much as we can!
Comments
Post a Comment