As AI gains prevalence in more areas of society, it is becoming much more advanced and capable of rapidly changing many historically consistent or slow-to-evolve aspects of society, including business, economics, military strategy, entertainment. As AI capability continues to increase, how will AI affect business even further than it already has in the near future? To answer this question, I will be doing research as well as conducting interviews of professionals who work in fields related to AI to incorporate expert opinions into my research.

My mentor will provide data sets of electrocardiograms that his company has collected. Using knowledge of machine learning that I will gain through background research, I will create an AI algorithm that will "learn" the relationship between an electrocardiogram and the heart rate. Essentially, I will feed my algorithm sets of electrocardiograms with corresponding heart rates, and the algorithm will find a relationship between them. When fully trained, my algorithm will provide an accurate heart rate for any electrocardiogram that I give it.

Utilizing machine learning, computers can now be taught to generate real images. This project uses a general adversarial network (GAN) to generate images. A GAN is composed of two neural networks: one plays the painter and one the judge. The painter uses responses from the judge to improve its painting, eventually generating life-like images. However, getting a GAN to work as intended in this regard is notoriously difficult; one goal of the project is to improve the training process.

This project will explore whether graph theory can be used to control chirality and model the genesis of chirality, a molecule not superimposable on its mirror image. This will be determined by observing isomorphism, or whether they are corresponding or similar in form, in CoCalc. Also, the project will explore whether properties of nanosystems calculated in Quantum Espresso (i.e., magnetization, thermodynamics, and band structures) can be predicted through graph theory. Finally, there will be an investigation on whether graph theory can mathematically describe the growth mechanisms in graphene.

We will be creating a computer simulation that models how populations of mosquitoes are affected by certain vector control methods such as Wolbachia. This simulation will model a variety of methods and their effectiveness in various conditions and environments. The simulation will be interactive, with the ability to add factors in the process.

Despite​​ ​​numerous​​ ​​attempts​​ ​​at​​ ​​preventing​​ ​​suicide,​​ ​​high​​-achievement​​ ​​communities​​ ​​are​ ​still​​ ​​struggling​​ ​​to​​ ​​design​ ​programs​​ ​​that​​ ​​are​​ ​​effective​​ ​​at​​ ​​preventing​​ ​​these​​ ​​deaths.​​ This​​ ​​problem​​ ​​has​ ​negatively​​ ​​impacted​​ ​​both​​ ​​​individuals​ and communities at large, since​​ ​​people​​ ​​are​​ ​​still​​ ​​suffering​​ ​​with​​ ​​mental​​ ​​health​ ​issues​​ ​​and​​ ​​don’t​​ ​​know​​ ​​where​​ ​​to​​ ​seek​ ​affordable​​ ​​counseling​​ ​​and​​ ​​mental​​ ​​health​​ ​​services.​​ ​​Perhaps​​ ​​exploring​ ​past​​ ​​suicide​​ ​​data,​​ ​​and​​ ​​the​​ ​​mental​​ ​​health​ ​programs​​ ​​in​​ ​​those​​ ​​impacted​​ ​​communities​, can​​ ​​point the way to​​ ​​a​​ ​​possible​ ​remedy​​ ​​for​​ ​​this​​ ​​problem.

We will examine how properties of graphene change as we dope them with pairs of metals. We are using Quantum Espresso to simulate how the particles interact with each other. We will also compare these changes in properties to other experiments to see how this can be used as a semiconductor or for other purposes.