I am Raphael Kirchgaessner, a PhD student currently enrolled in the Biomedical Department of OHSU. I am dedicated and self motivated to always improve myself in any possible way.
The only person you are truly competing against is yourself
In my role as a graduate student at OHSU, I concentrated on the development and implementation of advanced computational models for cancer research. My work primarily involved constructing novel algorithms to extract deeper biological insights from cancer data. I extensively utilized advanced neural networks, including Variational Autoencoders (VAE), Autoencoders (AE), and Graph Neural Networks (GNN), to generate new data embeddings. These embeddings were crucial for optimizing the processing and interpretation of clinical data, significantly enhancing the accuracy and efficiency of our research.
One key project involved evaluating whether it is possible to train a model to recognize specific cancer subtypes using only summed and aggregated embeddings derived from image, text, RNA, and mutation data. This research demonstrated the potential of using machine learning models to gain new biological insights into patients' responses to therapy, protein expression imputation, and the development of heterogeneous GNN networks. Additionally, this technology shows promise for use in vector databases, with potential applications in improving cancer treatment and extending patient survival. My contributions have driven innovation in the application of machine learning techniques in oncology, significantly impacting the methodological approach to cancer research at OHSU.
As a mentor on Wyzant, Inc., I offer professional services to individuals seeking guidance in Angular, Python, Machine Learning, C#, and German. I catered to students with a wide range of proficiency levels, ranging from high school to university-level.
If you are interested in getting in touch reach out anytime
I co-founded Origin Audio LLC with a colleague, where I oversee day-to-day operations and lead all software development efforts.
Origin Audio LLC specializes in delivering batch machine learning services specifically designed for musicians and producers.
My key responsibilities include:
I founded AnoBrain in May 2022, a consulting firm that provides specialized services in Data Science and IT solutions.
My responsibilities included:
As a teaching assistant, my responsibilities included conducting support sessions for first to third-year students. These sessions primarily focused on programming classes, but were not limited to them. Furthermore, I played an active role in the development of new software that was intended to be utilized by students as an example during their classes.
During my six-month internship in the DTSE department at Deutsche Telekom, I was part of the program and project management team. My duties included the reporting of project statuses and progress, as well as organizing various projects throughout the organization.
In my role as a graduate student at OHSU, I concentrated on the development and implementation of advanced computational models for cancer research. My work primarily involved constructing novel algorithms to extract deeper biological insights from cancer data. I extensively utilized advanced neural networks, including Variational Autoencoders (VAE), Autoencoders (AE), and Graph Neural Networks (GNN), to generate new data embeddings. These embeddings were crucial for optimizing the processing and interpretation of clinical data, significantly enhancing the accuracy and efficiency of our research.
One key project involved evaluating whether it is possible to train a model to recognize specific cancer subtypes using only summed and aggregated embeddings derived from image, text, RNA, and mutation data. This research demonstrated the potential of using machine learning models to gain new biological insights into patients' responses to therapy, protein expression imputation, and the development of heterogeneous GNN networks. Additionally, this technology shows promise for use in vector databases, with potential applications in improving cancer treatment and extending patient survival. My contributions have driven innovation in the application of machine learning techniques in oncology, significantly impacting the methodological approach to cancer research at OHSU.
Thesis Title: Application of a geolocation framework for customer aquisition
Grade: 1.3
Beyond my academic work, I find joy in various activities. I love playing soccer, hiking, and exercising. Spending quality time with loved ones is also important to me. Recently, I’ve taken on bike riding as a new challenge. Bike camping adds an extra thrill, combining my love for hiking and backpacking. This mix of activities keeps me active and helps me explore new terrains.
I’m an enthusiastic learner, always eager to expand my knowledge. I’m passionate about IT and Machine Learning advancements. History and space exploration fascinate me as well. I’m constantly seeking new insights in these areas. I apply what I learn to both research and personal projects.