Data Science & Machine Learning Consulting

Delivering Powerful Machine Learning Solutions for Real-World Impact

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Raphael Kirchgaessner

Portland, OR 97225 · (503) 206-2762 · exitare@exitare.de

As a biomedical PhD researcher at OHSU with a passion for advancing healthcare solutions through data science, machine learning, and bioinformatics, I bring a unique blend of scientific rigor and technical expertise. With hands-on experience in deep learning, spatial omics, and cloud computing, I specialize in solving complex biological problems and translating insights into impactful, actionable strategies for my clients.

Driven by a commitment to innovation and continuous improvement, I offer consulting services that are tailored to empower organizations in biotech, healthcare, and beyond. Whether you’re looking to implement advanced machine learning models, improve data processing workflows, or gain insights from complex datasets, I provide a partnership grounded in deep technical knowledge and a passion for real-world applications.


Consulting Services

Machine Learning Setup

Get started with robust machine learning pipelines tailored to your needs.

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Model Training Assistance

Receive guidance with data preprocessing, model tuning, and evaluation.

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Cloud Infrastructure

Optimize your data science projects with cloud-based solutions.

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Experience

PhD Researcher in Computational Oncology

Developed and implemented machine learning models to drive innovation in cancer research, creating robust algorithms for data-driven insights in oncology.

  • Specialties: Machine learning models, GNNs, VAEs, embeddings, predictive analytics in biomedical applications.
  • Client Relevance: Expertise in creating machine learning models to uncover novel insights from complex datasets—ideal for clients aiming to advance data-driven solutions in precision medicine, healthcare, and beyond.
September 2019 - Present

Consultant and Mentor

Provide tailored mentorship in Angular, Python, Machine Learning, and Data Science to clients and students of diverse backgrounds.

  • Client Relevance: Customized, one-on-one guidance to boost technical skills and confidence, helping clients meet specific project needs and learning goals.
August 2022 - Present

CEO & Founder

Co-founded a tech company providing machine learning solutions for musicians and producers. Led product development and managed cloud infrastructure.

  • Specialties: Full-stack app development, Azure infrastructure management, batch processing solutions.
  • Client Relevance: Experience in scalable app and ML service delivery, aligning technical solutions with creative industry needs.
January 2021 - Present

CEO & Founder

Launched a consulting firm specializing in data science and IT solutions, offering clients data-driven strategies and training services.

  • Specialties: Strategic consulting, data science, custom training sessions.
  • Client Relevance: Proven success in executing marketing strategies and delivering tailored training for improved client operations.
May 2022 - Present

Education

Oregon Health & Science University

Doctor of Philosophy (PhD), Biomedical Engineering

As a PhD candidate, I developed advanced computational models to enhance cancer research, focusing on methods that deliver actionable insights from complex biological data. Leveraging Variational Autoencoders (VAE), Autoencoders (AE), and Graph Neural Networks (GNN), I created data embeddings to optimize analysis and interpretation, significantly improving prediction accuracy and data processing efficiency.

  • Key Achievement: Led and collaborated on multiple projects utilizing ML models to uncover novel insights in cancer biology.
  • Impact: Innovations from this research could drive advancements in vector databases and protein imputation, with impactful applications in cancer treatment and patient survival.
September 2019 - 2025

University of Applied Sciences Karlsruhe

Bachelor of Science, Business Information Systems

Thesis: Developed a geolocation framework to streamline customer acquisition processes for businesses.

  • Final Grade: 2.1 (Equivalent to Excellent)
September 2013 - September 2017

Skills & Expertise

Frameworks & Tools
  • Angular
  • Node.js
  • Ionic
  • TensorFlow
  • PyTorch
  • MLFlow
  • SnakeMake
Programming Languages
  • TypeScript
  • C#
  • Python
Cloud & Database Expertise
  • Proficient in Azure cloud services
  • Skilled in both SQL and NoSQL databases
Professional & Research Skills
  • Strong scientific writing and communication abilities
  • Skilled in solving complex problems and designing innovative solutions
  • Extensive research experience with a focus on translating insights into actionable outcomes
  • Extensive experience in designing and implementing complex API server architectures, with a focus on scalability and efficiency.

Research & Publications

My research in computational biology focuses on using machine learning techniques to extract meaningful insights from complex biological data. Below are some key projects and publications that showcase my expertise in the field.

Computational Pipeline to Identify Gene Signatures Defining Cancer Subtypes

Ekansh Mittal, Vatsal Parikh, Raphael Kirchgaessner

Developed a novel computational pipeline for identifying gene signatures in cancer subtypes, demonstrating the power of data-driven approaches in oncology research.

Imputing Single-Cell Protein Abundance in Multiplex Tissue Imaging

Raphael Kirchgaessner, Cameron Watson, Allison Creason, Kaya Keutler, Jeremy Goecks

Innovative approach to impute protein abundance in tissue imaging, advancing the analysis of complex biological systems and enhancing data interpretation in biomedical research.

Tumor model to tumor treatment: Applying deep learning approaches to map multimodal data from cancer model systems to patients

Brian Karlberg, Raphael Kirchgaessner, Jeremy R. Jacobson, Kyle Ellrott, Sara J. Gosline

Novel VAE-based strategy for correcting platform effects in cancer drug response data, enhancing cross-model prediction accuracy and advancing the translatability of proteogenomic studies for improved insights into cancer biology and patient treatment strategies.


Portfolio

Below are some of the products and projects I've developed, highlighting my expertise in machine learning, application development, and biomedical research. Each project reflects my commitment to innovation and solving complex challenges through technology.

Divey

A dive buoyancy calculator app leveraging AI to enhance diving safety and convenience. Available on iOS and Android.

View Project

Story Time: Paramithi

A storytelling app for children and parents featuring multi-language story starters. Available on iOS and Android.

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Origin Audio

An online tool for batch audio slicing with a free tier, designed for simple, secure audio processing.

View Project

Contact Me

Interested in working together? Let’s discuss how I can help your project succeed.