This research project is going to determine the effectiveness of social chatbot. Autistic users are individuals that have challenges in communicating verbally or socially with surrounding people. This is because autistic individuals tend to talk about particular topics that only they are interested in, which is sometimes difficult for others to keep up. However, a chatbot can more likely continue with the conversation, even when the autistic individual keeps on talking about the same topic. The hypothesis is that the autistic user will converse more consistently with the robot in comparison to a human therapist.

Across California, groundwater in aquifers, or underground water reservoirs, has been depleting at a very high rate. This is primarily due to the over-pumping of groundwater from aquifers for irrigation and municipal use. Such depletion has lasting and negative effects on both human and wildlife populations. This research project will investigate the causes and rate of groundwater depletion, and will provide possible solutions to mitigate this issue.

Despite the many growing pollution issues that our world is facing, environmental sustainability has been avoided and overlooked in most companies for reasons largely unknown. Countless companies have already attempted to integrate environmental sustainability into their products, but only a few have succeeded. This research project will conduct interviews with eco-friendly companies to reveal the challenges that many companies face with sustainability. With that information, the findings will work to convince or encourage other companies to do the same.

About one in three people will be diagnosed with cancer at some point in their lives (“Cancer Statistics,” 2018). Yet, the mutation that caused the tumor’s formation may differ from one patient to another. My research focuses on how extrachromosomal DNA in biofluids can serve as biomarkers in cancer. Sequencing the mutation from ecDNA is a less-invasive detection method with high accuracy in its diagnosis. This project hopes to summarize past research and provide insight into where this new field is headed to next.

This research project will study the connection between the gut microbiome alterations and contributing proteins, such as Tau and beta-amyloid, alpha-synuclein, and Huntingtin, analyzing their specific structure and function in Alzheimer’s, Parkinson’s, and Huntington’s diseases respectively. Previous studies have shown a possible relationship between gut microbiome bacteria and the eventual aggregating and misfolding of proteins. Abnormal misfolded proteins interrupt intercellular communication and secrete toxins, and this action typically triggers the onset of those diseases. This project will utilize BLAST to inspect similarities between the molecular structures of these proteins. Results will provide a better understanding of each disease and potentially come up with an idea of how to combat all these neurodegenerative diseases.

The San Francisquito Creek of East Palo Alto flooded 20 years ago, costing millions of dollars in damage costs. The most common method of flood management is building levees or walls to prevent the water from escaping the creek. However, many city or state government programs ignore factors such as climate change and unintended consequences such as flooding upstream of the newly build levees. Instead, they only focus on cost-efficiency and functionality. Using an array of historical flood data and putting it into a statistical simulation, all these important factors will be accounted for to produce a damage cost. Based on this, it is expected to deduce how the levees should be constructed in order to minimize the chance of failure in flood management.

The Paris climate agreement, created in 2016 by the UNFCCC, created a goal to reduce global emissions by 80% by 2050. The U.K. and Canada are developed countries expected to lead these efforts. Both countries have released climate action plans to combat climate change. This research project will aim to determine their actions' effectiveness in combating climate change by measuring the reduction in annual emissions of greenhouse gases in CO2 equivalent.

Recent work in the computer science field of music information retrieval (MIR) has demonstrated the ability of machine learning to analyze and automatically generate musical phrases, lyrics, and accompaniments. The goal of this research project is to implement techniques in an optimized, web-accessible interface. By providing initial direction for the music, the machine learning model(s) would generate and respond with a full 3min song around that prompt.

This project will focus on whether the testing of water will lessen the contamination of coastlines, specifically in Pilar Point Harbor in Half Moon Bay, in order to pinpoint and reduce the consequences of pollution at surf breaks. The project will analyze data on both water quality (quantitative) and where it appears to be coming from (qualitative) and analyze data.

This research project focuses on the effectiveness of the Autism Superpower Glasses on blind individuals. A team at Stanford University developed the Autism Superpower Glass, which is a wearable technology that uses artificial intelligence and machine learning to help children with autism recognize facial emotions. The goal of this project is to determine how successful the glasses are on a different population with different needs. Potentially, the research and data collected could make the Autism Superpower Glasses accessible to the blind population.