Introduction

Description:

I am a clinical data scientist in Vaccines and Immune Therapies. I lead two projects. The first, DIALOGUE is a chat-based Large Language Model Interface that interprets natural language questions and turns it into SQL code for quick data analysis. The second, DRAFT, automates insertion of tables, listings, and figures into documents, guaranteeing data quality.

Why I chose here:

Astrazeneca is an important company in drug discovery, development, and deployment. I came to learn about the biology, the science, the engineering, and all the data that runs this company. Kubrick Group trained me in a variety of Data Softwares invaluable to the future of the corporate world.

What I learned:

Python, SQL, Langchain, DSPy, LLMs, Data Science, Snowflake, DBT, Databricks, Data Governance, Feature Stores, Power BI, Agile Methodology, AWS.

Description:

I am working on a project to computationally simulate experimental results. Dr. Gokoffski in this lab found that when Retinal Ganglion Cells are crushed and put in an electric field, the axons regrow in the direction of the electric field. We know that a change in internal Calcium causes this axon growth, but it is my job to recreate these circumstances so that the lab does not need to waste time and resources testing every possible parameter of stimulation. Ideally, a computer will be able to accurately simulate these results. 

Why I chose here:

I really liked the concept of learning how to program the brain. NERUON by Yale allows the ability to simulate morphologically accurate neurons by breaking it down to the biophysical and 3D geometrical properties. Then, my lab developed a way to combine that information with electric field simulation, and they can recreate their experimental results. Also, RGCs are in the Central Nervous System, and those axons don't regrow in the body, so there can be profound effects from this study.

What I learned:

Besides new programming tactics and more about the languages of NEURON, python, and MATLAB, I learned a lot about how Yale and others created this network of databases, software, and global research to simulate and remember parts of the infinitely complex brain.

Description:

I shadowed at the Cleveland Clinic in Las Vegas. My tasks were simple, to sit in with the doctors at this Neurodegeneration-focused hospital and do a few online tasks for the organization, but what I learned was invaluable.

Why I chose here:

For a few summers prior, I attended journal clubs and other small programs to learn more about how the Cleveland Clinic fights against neurodegenerative diseases, but I really wanted the opportunity to speak with the doctors and witness their interactions with patients. I know now too, that I would rather be on the industry side than the physician side, making devices and other products to help cure or treat these terrible diseases, but I wasn't completely sure going in.

What I learned:

I learned the extent of how terrible neurodegenerative diseases are for the patient and the entire support network. I can talk about how these weeks truly influenced my outlook on life, even, but more importantly, I learned how devices are used to treat and improve patient's lives. I think progress is slow, but every new device will change many lives. Devices like Deep Brain Stimulation in particular get me excited about the intersection between Computational Neuroscience and Biomedical Engineering.

Description:

Virtually, I did research on how dysbiosis in the gut microbiome affects the health of the elderly. This cumulated in a research grant for future interns to use.

Why I chose here:

Personally, I have a sensitivity to highly inflammatory foods, meaning if I eat certain foods, I get migraines. I was particularly interested in this topic because it involves the gut-brain connection that combines my interests in neuroscience and how the body deals with food. 

What I learned:

Food is everything in the body. In the United States, we often look the other way with the thousands of chemicals and preservatives and bad things we put in our bodies that are banned in other countries. We live to comparable ages, but often the quality of life leads to more gut dysbiosis and frankly a lower quality of life that can be prevented by eating healthier throughout life. 

Description:

This company creates haptic devices for neuro-diverse populations to help them interpret emotion. I was on the machine learning team that used a convolutional neural network to distinguish different emotions and then buzz the haptic device differently for each emotion.

Why I chose here:

I really liked the concept of the product, and I just took the AI class at USC. I wanted to apply my skills and learn more about the USC start up.

What I learned:

I learned new programming skills in Conda, python, and pandas and how startups work with USC students running it all.

Description:

I interned from Los Angeles virtually for this Barcelona based company. They were using an inadequate Mechanical Engineering system to run their nanotechnology reactor, and I helped them switch over to a Programmable Logic Controller to run and debug their system.

Why I chose here:

USC had a program to intern abroad, and it was a great opportunity during the first full COVID semester. I thought the job to switch a nanotechnology reactor over to a different system was a good application of the coding I was learning in school.

What I learned:

I learned about how PLC programming works, but more interestingly, I learned how to program a device thousands of miles away. I found and used a simulation to create the environment of the reactor, and I used that to program to program the Controller that they would then test in their lab.

Description:

This lab did electrophysiology research in rat brains to analyze spatial directionality between the Hippocampus and Anterior Cingulate Cortex. I did MATLAB analysis and helped build the implants.

Why I chose here:

I was interested in devices that invasively recorded the brain in live animals. I also knew I would learn a lot about coding and how labs ran. 

What I learned:

I learned MATLAB and statistical analysis, but more importantly, this was my first experience with electrophysiology devices. I couldn't believe that technology was at the point of recording and stimulating the brain. This job started my love for technology for the body and brain.