Data Science Expert & AI Strategist|Python & Dashboard Developer|Biomedical Research|Generative AI|Computer Vision|Azure|AWS|Product Development
Aktualisiert am 22.04.2024
Profil
Freiberufler / Selbstständiger
Remote-Arbeit
Verfügbar ab: 01.07.2024
Verfügbar zu: 100%
davon vor Ort: 60%
Data Scientist
AI Strategy
Product Development
AI Product Development
Python
Dashboard Development
Advanced Analytics
Biomedical Data Science
NLP
AWS
Azure
SQL
NoSQL
Knowledge Graph
Computer Vision
LLM
Prompt Engineering
ETL
Digital Health Innovation
Data Governance
RAG
Langchain
llama index
English
Native Language
German
Fluent
Spanish
Grundkenntnisse

Einsatzorte

Einsatzorte

Deutschland, Schweiz, Österreich
möglich

Projekte

Projekte

2 years 5 months
2021-08 - 2023-12

Digital Execution Strategy Development

Head of Digital Lab, CD&O Team Leadership Strategic Planning Agile Methodologies ...
Head of Digital Lab, CD&O

Digital Execution Strategy Development

  • Coached an international team of eight, internal, digital entrepreneurs within the Digital Transformation CoE. Created processes for empowered decision making. 
  • Up-skilled team on design thinking methodologies, including design thinking facilitation and qualitative user research methods. 
  • Developed digital transformation execution strategy, based on data, people, cloud infrastructure, and budget, alongwith coaching methodologies,  problem statement development, executive buy-in, and sponsorship.


Digital Transformation in Medical Writing

  • Performed process mapping, qualitative analysis of internal processes, resulting in business use case descriptions. 
  • Used ChatGPT to lead medical writers to do PoC on different uses cases including document generation, redaction, and translation. 
  • Performed market scouting, leading to short list of vendors and the development of Request for Proposal (RfP) process to decrease time to market by several weeks.


Lay Document Generation Using RAG System

  • Advised Data Scientist and Medical writer on best practices for development of LLM prompts and prompt chaining along with large pdf document ingestion and vector embeddings. 
  • This resulted in a RAG system, which enables medical writers to interactively and semi-automatically create lay summaries of clinical trials, based upon the clinical trial protocol.


Analytics Landing Page

  • Served as the Product Owner for the analytics landing page, incorporating a recommendation engine and utilizing Large Language Models for enhanced question answering and cognitive search capabilities across dozens of operational dashboards. 
  • Created a roadmap for adhoc visualizations of operational data using LLMs, bespoke data models, and OpenAPI specifications.

Team Leadership Strategic Planning Agile Methodologies Digital Strategy Project Management Qualitative User Research Technical Leadership Cross-Functional Collaboration Coaching LLM Prompt Prototyping Generative AI ChatGPT Prompt Chaining llama index Azure Cognitive Services Product Ownership Innovative Thinking Data Visualization LLM Utilization LLMs OpenAPI AWS Jira Confluence git
Boehringer-Ingelheim
2 years 7 months
2019-01 - 2021-07

Clinical Data Catalogue

Senior Data Scientist Collaborative Problem Solving Interdisciplinary Communication Qualitative User Research ...
Senior Data Scientist

Clinical Data Catalogue

  • Responsible for the development Data Science aspects of a clinical data catalogue, integrating clinicaltrials.gov and in-house data for seamless access and aggregation of clinical trial information. 
  • Focused on semantic search capabilities, I developed advanced NLP pipelines and graph data models within a knowledge graph for visualization of unstructured data. 
  • My role extended to facilitating the product team?s ownership, addressing technical and business challenges, and aligning with internal stakeholders to ensure data governance compliance.


Interdisciplinary Hackathon Creating a Gamification of NLP Annotation in a Web App

  • Led an interdisciplinary hackathon project focused on gamifying NLP annotation for entity relationship models. Responsibilities included desk research, knowledge resource creation for software developers, UX researchers, and external vendors, and guiding data scientists through NLP pipelines. 
  • Managed the development of a game that allowed biomedical researchers to validate NLP entity linking models in a gamified approach, enhancing knowledge dissemination in knowledge graphs, gamification, and NLP modeling.


Conceptualization of Bespoke Knowledge Management System Including PoC

  • Led the conceptualization of a bespoke knowledge management system, conducting extensive qualitative user research with over 60 company personnel to determine value proposition and feature set. 
  • Collaborated with key stakeholders in design sprints to test features, and developed prototypes using open-source NLP algorithms for advanced question answering and topic modeling. 
  • Recognized by the board of governors for innovation, and worked with in-house IT for further project development.


Development of Bioinformatics Pipelines for Genome Assembly Algorithms

  • Led a cross-functional team of developers and scientists in creating validation and innovative bioinformatics pipelines on AWS cloud services. 
  • The project focused on the development of ultra-fast de novo genome assembly algorithms, leveraging cloud computing for enhanced computational efficiency and accuracy. 
  • Utilized AWS CDK and orchestrated various AWS services to streamline the bioinformatics pipeline.

Collaborative Problem Solving Interdisciplinary Communication Qualitative User Research SCRUM Leadership Data Modeling Exploratory Data Analysis Semantic Search Algorithm Development Biomedical Ontologies NLP Graph Database Management Entity Recognition BERT Transformer Model CI/CD Python Jupyter Notebooks Docker OpenShift SPARQL SQL Stardog PostgreSQL spaCy Jira Confluence git Jenkins Team Leadership Interdisciplinary Collaboration Vendor Relationship Management Knowledge Dissemination Data Visualization Game Design Entity Relationship Modeling Knowledge Graph Utilization TensorFlow User Research Stakeholder Engagement Innovative Thinking Design Thinking Collaborative Problem Solving Question Answering Topic Modeling Prototyping User-Centered Design Elasticsearch Project Management Cross-Functional Collaboration Bioinformatics Genome Assembly Pipeline Development Cloud Computing AWS Batch AWS IAM AWS Step Functions AWS ECS AWS CodePipeline AWS CDK
BI X GmbH
1 year
2018-01 - 2018-12

Bespoke Drug Discovery and Market Intelligence Web App

Data Scientist SCRUM Leadership Team Collaboration Qualitative User Research ...
Data Scientist

Bespoke Drug Discovery and Market Intelligence Web App

  • Led the Data Science development of a web application for drug discovery and market intelligence, focusing on complex ETL processes, advanced NLP for entity recognition, and the development of an advanced search feature utilizing biomedical ontologies. 
  • Actively participated in user interviews alongside UX researchers, providing expertise on biomedical subject matter to inform user-centric design.


Data Science Hackathon Utilizing Generative AI to Generate Novel Medicinal Molecules

  • Led a hackathon project focusing on utilizing generative AI to create novel medicinal molecules. 
  • Responsibilities included conducting desk research, creating knowledge resources for non-biomedical data scientists, and leveraging advanced AI models for molecule generation and property estimation. 
  • Collaborated closely with the Medicinal Chemistry Department to align efforts and co-create a new digital initiative.

SCRUM Leadership Team Collaboration Qualitative User Research Interdisciplinary Communication Stakeholder Engagement ETL NLP CI/CD Biomedical Data Processing Search Algorithm Development Postgres Neo4j Python TensorFlow OpenShift Docker Jupyter Notebooks Jira Confluence git Jenkins Collaborative Problem Solving Interdisciplinary Communication Innovative Thinking Project Management Data Visualization Generative AI Modeling Molecular Property Estimation Biomedical Data Analysis t-SNE Vector Embeddings
BI X GmbH
1 year 9 months
2016-04 - 2017-12

Curation and Reporting of high-dimensional and heterogeneous NGS and Biomedical Imaging Datasets

Research Scientist, Radiogenomics Interdisciplinary Collaboration Interdisciplinary Communication Innovative Problem Solving ...
Research Scientist, Radiogenomics

Curation and Reporting of high-dimensional and heterogeneous NGS and Biomedical Imaging Datasets

  • Collaborating with the Radiology, Nuclear Medicine, Bioinformatics, and the Oncology departments to collect, aggregate and analyze high-dimensional and heterogeneous datasets stemming from an observational clinical trial in hepatocellular carcinoma patients. 
  • I created workflows for curating NGS data sets with multiple online databases. 
  • I extracted radiomics features from multi-dimensional imaging data sets and used heatmaps, hierarchical clustering methods, and protein interaction networks to visualizeand report  insights on the project.


Clinical Reporting Strategy of Genetic Variations

  • Curating genetic variations of individual patients with online databases and scientific publications. 
  • The aggregation algorithms were containerized for interoperability, and were used for creation of genetic variation reports to help oncologists decide about alternative therapy options for patients not responding to the standard of care.


Using Parallel Coordinates to Visualize Hidden Layers in Feed Forward Neural Networks

  • Conceptualized an innovative visualisation approach for understanding how feedforward neural networks can be visualized with parallel coordinates, and advised Master's student to develop interactive web app. 
  • This approach belongs to the category of explainable AI, and allowed for visualization of hidden layers and separability of classes in hidden layers, leading to an intuitive approach to hyper-parameter tuning.


Development of interactive webapp for visualization of images, no-code creation of neural network architecture, training, and hyper-parameter optimization

  • Conceptualized an innovative workflow tool to visualize large imaging data sets, interactively create neural convolutional auto-encoder architectures, train neural networks, visualize latent representation, and perform batch processing for hyper-parameter tuning. 
  • I advised a Master's student to develop the corresponding, interactive web app. 
  • This is an important tool for no-code development of transfer learning techniques for convolutional neural networks and un-supervised clustering and classification of imaging datasets.


Utilizing Biological Interaction Networks to Aggregate NGS and Molecular Imaging Data, defining highly disrupted pathways

  • Conceptualized a technique to map molecular imaging and NGS data sets to KEGG protein-protein interaction networks, and advised a doctoral student to implement the technique. 
  • This led to a reduction of the dimensionality of the NGS and imaging features, and allowed for introspection of the indicated molecular pathways, which overlapped in a small cohort of patients. 
  • This represents a novel technique for combining disparate biomedical data sets and pathway analysis.

Interdisciplinary Collaboration Interdisciplinary Communication Innovative Problem Solving Machine Learning Spectral Clustering Data Visualization Data Engineering Exploratory Data Analysis Python DICOM Tensorflow Seaborn Bioinformatics Exploratory Data Analysis Data Modeling REST API Docker Cloud Computing Coaching Collaborative Problem Solving Neural Networks API Development TensorFlow Convolutional Neural Networks Transfer Learning Clustering Biological Network Visualization Network Path Analysis KEGG Cytoscape
Applied Bioinformatics Group, Center for Bioinformatics, Eberhard Karls University Tübingen
6 years 1 month
2010-03 - 2016-03

Development of Gaussian Mixture Modeling Pipeline for Tumor Microenvironment Analysis

Research Fellow, Oncology Analytical Thinking Problem-Solving Interdisciplinary Research ...
Research Fellow, Oncology
Development of Gaussian Mixture Modeling Pipeline for Tumor Microenvironment Analysis
  • Conceived and co-developed a novel Gaussian mixture modeling (GMM) pipeline integrating 18F-FDG PET and diffusion-weighted MRI (DW-MRI) data. 
  • The project aimed to segment the tumor microenvironment into distinct tissue compartments and monitor their evolution over time. 
  • Successfully demonstrated the pipeline's ability to segment tumor tissue accurately and establish a linear correlation between ADC and 18F-FDG values, suggesting its potential for advancing disease outcome assessment into precision medicine.


Multi-parametric MRI Tumor Tissue Segmentation Study

  • This study introduced an unsupervised segmentation method using multi-parametric MRI to quantify diverse tumor tissue types. 
  • The study involved comparing this novel approach with existing segmentation techniques and validating the results against histological samples. 
  • Findings indicated that the new method accurately quantified the fractional populations of necrotic, peri-necrotic, and viable tumor tissues, aligning closely with histological analyses. 
  • The implications of this research may significantly improve cancer treatment planning and improve MRI-guided tumor biopsies


Spatial Characterization of Intratumoural Heterogeneity via PET-MRI and Machine Learning

  • This project unveiled a cutting-edge approach to characterize intratumoural heterogeneity spatially through phenotype-specific, multi-view learning classifiers using dynamic PET and multiparametric MRI data. 
  • The research demonstrated the classifiers' capability to quantify phenotypic changes from targeted therapies in colon cancer models and align with tumour histology in patients with liver metastases from colorectal cancer. 
  • The application of this novel method in both preclinical and clinical settings underscores its significance in enhancing precision oncology.

Analytical Thinking Problem-Solving Interdisciplinary Research Scientific Communication Project Management Data Analysis Gaussian Mixture Modeling PET/MRI Data Integration Precision Medicine Research Image Processing Histopathology Machine Learning MATLAB Positron Emission Tomography (PET) Magnetic Resonance Imaging (MRI) Critical Analysis Innovative Problem Solving Cross-Disciplinary Collaboration Data Interpretation Research Funding Acquisition MRI Image Segmentation Unsupervised Learning Algorithms Histological Data Validation Cancer Treatment Planning Biopsy Procedure Enhancement Histopahtology Magnetic Resonance Imaginge (MRI) Machine Learning Application Interdisciplinary Collaboration Innovative Problem-Solving Scientific Research Communication Multimodal Imaging Analysis Machine Learning Classifier Development Phenotypic Analysis Dynamic PET-MRI Integration Biostatistics
Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen

Aus- und Weiterbildung

Aus- und Weiterbildung

1 year 6 months
2022-01 - 2023-06

1-on-1 Management Coaching

Consulting Impact, Daniel Zacher
Consulting Impact, Daniel Zacher
1 month
2022-06 - 2022-06

Casual Inference Workshop

Harvard Medical School
Harvard Medical School
6 months
2022-01 - 2022-06

Executive Education

Harvard Medical School
Harvard Medical School
1 month
2019-11 - 2019-11

Leading International Teams Successfully

Haufe Akademie
Haufe Akademie
1 month
2019-11 - 2019-11

Plotly Dashboard Workshop

Plotly
Plotly
6 years 1 month
2010-03 - 2016-03

Doctorate in Molecular Imaging

Dr. sc. hum., Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen
Dr. sc. hum.
Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen
3 months
2015-10 - 2015-12

Machine Learning

Coursera online course, Stanford University
Coursera online course, Stanford University
2 years 5 months
2007-10 - 2010-02

Masters in Biomedical Engineering

M.Sc., Rheinisch-Westfälische Technische Hochschule (RWTH), Aachen
M.Sc.
Rheinisch-Westfälische Technische Hochschule (RWTH), Aachen
4 years 9 months
2002-09 - 2007-05

Bachelors in Physics and Mathematics

B.Sc., Midwestern State University (MWSU), Texas, USA, Received competitive Scholarship from Midwestern State University
B.Sc.
Midwestern State University (MWSU), Texas, USA, Received competitive Scholarship from Midwestern State University

Kompetenzen

Kompetenzen

Top-Skills

Data Scientist AI Strategy Product Development AI Product Development Python Dashboard Development Advanced Analytics Biomedical Data Science NLP AWS Azure SQL NoSQL Knowledge Graph Computer Vision LLM Prompt Engineering ETL Digital Health Innovation Data Governance RAG Langchain llama index

Produkte / Standards / Erfahrungen / Methoden

Personal Statement

  • "I am an innovator at heart, leading through action and empowering teams with the tools and mindset to harness AI effectively. Leadership for me is built on meaningful collaboration, nurturing a culture of growth and agile innovation. 
  • Whether leading a team or working solo, I am your reliable partner, and will empower your organization to navigate the next wave of digital transformation.?


Technologies

  • Cloud Platforms: Extensive experience with AWS (including EC2, SageMaker, Lambda, S3, ECS,?), Azure Cognitive Services, and Red Hat OpenShift.
  • Data Management: Skilled in SQL and NoSQL technologies with experience in SPARQL
  • Dashboard Technologies: Proficient in Streamlit and Dash Machine Learning and AI: Experienced with Transformer Models in NLP, utilizing LLM technologies from OpenAI, Langchain, and llama index


Professional Development

08/2021 - 12/2023:

Role: Head of Digital Lab

Customer: Boehringer-Ingelheim, CD&O


Tasks:

  • Develop and Implement Digital Innovation Strategy for Clinical Development and Operations (CD&O)
  • Up-skill and coach global, self-organized, and empowered team of internal entrepreneurs
  • Leverage qualitative research methods to understand business needs in a user-centric manner, and proactively scout for potential solutions
  • Product Owner for in-house developed software, enabling teams by example with a technical roadmap, utilizing LLMs to bootstrap advanced search capabilities, Question-Answering and self-service data-visualization utilizing OpenAPI specifications


01/2021 ? 05/2021:

Role: Interim Head of Data Science

Customer: BI X GmbH


Tasks:

  • Responsible for staffing of new initiatives and internal hiring
  • Collaboratively coaching digital Product Owners with BI X leadership team
  • Coordinate strategy with Global Head of Data Science


01/2018 ? 07/2021:

Role: (Senior) Data Scientist

Customer: BI X GmbH


Tasks:

  • Empower product team to take ownership by removing technical and business impediments before they impacted development
  • Implemented data models, search, and ETL pipelines
  • Developed bespoke next-generation sequencing pipeline on AWS for shortand long-read sequencing for benchmarking and drug target discovery
  • Staffing initiatives and mentoring junior members of the product team
  • Product Owner for self-driven concept from ideation to Fast Forward Top 10, resulting in project with internal IT for select business cases


04/2016 ? 12/2017:

Role: Research Scientist, Radiogenomics

Customer: Applied Bioinformatics Group, Center for Bioinformatics, Eberhard Karls University Tübingen


Tasks:

  • Coordinate with BMBF research collaborators to identify and implement best practices for collection, processing, and transfer of sensitive clinical data
  • Implement and validate Auto-Encoder Neural Networks in Tensorflow on CPU cluster for analysis of radiology and multi-omics data
  • Utilize Python for data wrangling and visualization of biomedical imaging and multi-omics data
  • Curation of NoSQL databases and containerization in Docker with REST API as back-end for automated machine learning and clinical reporting pipelines of multi-omics testing in cancer patients
  • Mentoring of Bachelor, Master, and PhD candidates


03/2010 ? 03/2016:

Role: Research Fellow, Oncology

Customer: Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen


Tasks:

  • Coordination of BMBF financed research projects with cooperation partners from academia and industry with the goal of developing a holistic systems model of cancer therapy
  • Planning of experiments and coordination of laboratory staff to stay within confines of budget for collaborative research projects
  • Development and validation of a novel machine learning pipeline to predict tumor growth based on longitudinal PET and MR imaging
  • Integration and analysis of large, multi-dimensional and diversely formatted datasets
  • Mentoring of Bachelor and Master students
  • Organization of workshops and international scientific conferences

Programmiersprachen

Python
Proficient
C++
Proficient
MATLAB
Proficient

Einsatzorte

Einsatzorte

Deutschland, Schweiz, Österreich
möglich

Projekte

Projekte

2 years 5 months
2021-08 - 2023-12

Digital Execution Strategy Development

Head of Digital Lab, CD&O Team Leadership Strategic Planning Agile Methodologies ...
Head of Digital Lab, CD&O

Digital Execution Strategy Development

  • Coached an international team of eight, internal, digital entrepreneurs within the Digital Transformation CoE. Created processes for empowered decision making. 
  • Up-skilled team on design thinking methodologies, including design thinking facilitation and qualitative user research methods. 
  • Developed digital transformation execution strategy, based on data, people, cloud infrastructure, and budget, alongwith coaching methodologies,  problem statement development, executive buy-in, and sponsorship.


Digital Transformation in Medical Writing

  • Performed process mapping, qualitative analysis of internal processes, resulting in business use case descriptions. 
  • Used ChatGPT to lead medical writers to do PoC on different uses cases including document generation, redaction, and translation. 
  • Performed market scouting, leading to short list of vendors and the development of Request for Proposal (RfP) process to decrease time to market by several weeks.


Lay Document Generation Using RAG System

  • Advised Data Scientist and Medical writer on best practices for development of LLM prompts and prompt chaining along with large pdf document ingestion and vector embeddings. 
  • This resulted in a RAG system, which enables medical writers to interactively and semi-automatically create lay summaries of clinical trials, based upon the clinical trial protocol.


Analytics Landing Page

  • Served as the Product Owner for the analytics landing page, incorporating a recommendation engine and utilizing Large Language Models for enhanced question answering and cognitive search capabilities across dozens of operational dashboards. 
  • Created a roadmap for adhoc visualizations of operational data using LLMs, bespoke data models, and OpenAPI specifications.

Team Leadership Strategic Planning Agile Methodologies Digital Strategy Project Management Qualitative User Research Technical Leadership Cross-Functional Collaboration Coaching LLM Prompt Prototyping Generative AI ChatGPT Prompt Chaining llama index Azure Cognitive Services Product Ownership Innovative Thinking Data Visualization LLM Utilization LLMs OpenAPI AWS Jira Confluence git
Boehringer-Ingelheim
2 years 7 months
2019-01 - 2021-07

Clinical Data Catalogue

Senior Data Scientist Collaborative Problem Solving Interdisciplinary Communication Qualitative User Research ...
Senior Data Scientist

Clinical Data Catalogue

  • Responsible for the development Data Science aspects of a clinical data catalogue, integrating clinicaltrials.gov and in-house data for seamless access and aggregation of clinical trial information. 
  • Focused on semantic search capabilities, I developed advanced NLP pipelines and graph data models within a knowledge graph for visualization of unstructured data. 
  • My role extended to facilitating the product team?s ownership, addressing technical and business challenges, and aligning with internal stakeholders to ensure data governance compliance.


Interdisciplinary Hackathon Creating a Gamification of NLP Annotation in a Web App

  • Led an interdisciplinary hackathon project focused on gamifying NLP annotation for entity relationship models. Responsibilities included desk research, knowledge resource creation for software developers, UX researchers, and external vendors, and guiding data scientists through NLP pipelines. 
  • Managed the development of a game that allowed biomedical researchers to validate NLP entity linking models in a gamified approach, enhancing knowledge dissemination in knowledge graphs, gamification, and NLP modeling.


Conceptualization of Bespoke Knowledge Management System Including PoC

  • Led the conceptualization of a bespoke knowledge management system, conducting extensive qualitative user research with over 60 company personnel to determine value proposition and feature set. 
  • Collaborated with key stakeholders in design sprints to test features, and developed prototypes using open-source NLP algorithms for advanced question answering and topic modeling. 
  • Recognized by the board of governors for innovation, and worked with in-house IT for further project development.


Development of Bioinformatics Pipelines for Genome Assembly Algorithms

  • Led a cross-functional team of developers and scientists in creating validation and innovative bioinformatics pipelines on AWS cloud services. 
  • The project focused on the development of ultra-fast de novo genome assembly algorithms, leveraging cloud computing for enhanced computational efficiency and accuracy. 
  • Utilized AWS CDK and orchestrated various AWS services to streamline the bioinformatics pipeline.

Collaborative Problem Solving Interdisciplinary Communication Qualitative User Research SCRUM Leadership Data Modeling Exploratory Data Analysis Semantic Search Algorithm Development Biomedical Ontologies NLP Graph Database Management Entity Recognition BERT Transformer Model CI/CD Python Jupyter Notebooks Docker OpenShift SPARQL SQL Stardog PostgreSQL spaCy Jira Confluence git Jenkins Team Leadership Interdisciplinary Collaboration Vendor Relationship Management Knowledge Dissemination Data Visualization Game Design Entity Relationship Modeling Knowledge Graph Utilization TensorFlow User Research Stakeholder Engagement Innovative Thinking Design Thinking Collaborative Problem Solving Question Answering Topic Modeling Prototyping User-Centered Design Elasticsearch Project Management Cross-Functional Collaboration Bioinformatics Genome Assembly Pipeline Development Cloud Computing AWS Batch AWS IAM AWS Step Functions AWS ECS AWS CodePipeline AWS CDK
BI X GmbH
1 year
2018-01 - 2018-12

Bespoke Drug Discovery and Market Intelligence Web App

Data Scientist SCRUM Leadership Team Collaboration Qualitative User Research ...
Data Scientist

Bespoke Drug Discovery and Market Intelligence Web App

  • Led the Data Science development of a web application for drug discovery and market intelligence, focusing on complex ETL processes, advanced NLP for entity recognition, and the development of an advanced search feature utilizing biomedical ontologies. 
  • Actively participated in user interviews alongside UX researchers, providing expertise on biomedical subject matter to inform user-centric design.


Data Science Hackathon Utilizing Generative AI to Generate Novel Medicinal Molecules

  • Led a hackathon project focusing on utilizing generative AI to create novel medicinal molecules. 
  • Responsibilities included conducting desk research, creating knowledge resources for non-biomedical data scientists, and leveraging advanced AI models for molecule generation and property estimation. 
  • Collaborated closely with the Medicinal Chemistry Department to align efforts and co-create a new digital initiative.

SCRUM Leadership Team Collaboration Qualitative User Research Interdisciplinary Communication Stakeholder Engagement ETL NLP CI/CD Biomedical Data Processing Search Algorithm Development Postgres Neo4j Python TensorFlow OpenShift Docker Jupyter Notebooks Jira Confluence git Jenkins Collaborative Problem Solving Interdisciplinary Communication Innovative Thinking Project Management Data Visualization Generative AI Modeling Molecular Property Estimation Biomedical Data Analysis t-SNE Vector Embeddings
BI X GmbH
1 year 9 months
2016-04 - 2017-12

Curation and Reporting of high-dimensional and heterogeneous NGS and Biomedical Imaging Datasets

Research Scientist, Radiogenomics Interdisciplinary Collaboration Interdisciplinary Communication Innovative Problem Solving ...
Research Scientist, Radiogenomics

Curation and Reporting of high-dimensional and heterogeneous NGS and Biomedical Imaging Datasets

  • Collaborating with the Radiology, Nuclear Medicine, Bioinformatics, and the Oncology departments to collect, aggregate and analyze high-dimensional and heterogeneous datasets stemming from an observational clinical trial in hepatocellular carcinoma patients. 
  • I created workflows for curating NGS data sets with multiple online databases. 
  • I extracted radiomics features from multi-dimensional imaging data sets and used heatmaps, hierarchical clustering methods, and protein interaction networks to visualizeand report  insights on the project.


Clinical Reporting Strategy of Genetic Variations

  • Curating genetic variations of individual patients with online databases and scientific publications. 
  • The aggregation algorithms were containerized for interoperability, and were used for creation of genetic variation reports to help oncologists decide about alternative therapy options for patients not responding to the standard of care.


Using Parallel Coordinates to Visualize Hidden Layers in Feed Forward Neural Networks

  • Conceptualized an innovative visualisation approach for understanding how feedforward neural networks can be visualized with parallel coordinates, and advised Master's student to develop interactive web app. 
  • This approach belongs to the category of explainable AI, and allowed for visualization of hidden layers and separability of classes in hidden layers, leading to an intuitive approach to hyper-parameter tuning.


Development of interactive webapp for visualization of images, no-code creation of neural network architecture, training, and hyper-parameter optimization

  • Conceptualized an innovative workflow tool to visualize large imaging data sets, interactively create neural convolutional auto-encoder architectures, train neural networks, visualize latent representation, and perform batch processing for hyper-parameter tuning. 
  • I advised a Master's student to develop the corresponding, interactive web app. 
  • This is an important tool for no-code development of transfer learning techniques for convolutional neural networks and un-supervised clustering and classification of imaging datasets.


Utilizing Biological Interaction Networks to Aggregate NGS and Molecular Imaging Data, defining highly disrupted pathways

  • Conceptualized a technique to map molecular imaging and NGS data sets to KEGG protein-protein interaction networks, and advised a doctoral student to implement the technique. 
  • This led to a reduction of the dimensionality of the NGS and imaging features, and allowed for introspection of the indicated molecular pathways, which overlapped in a small cohort of patients. 
  • This represents a novel technique for combining disparate biomedical data sets and pathway analysis.

Interdisciplinary Collaboration Interdisciplinary Communication Innovative Problem Solving Machine Learning Spectral Clustering Data Visualization Data Engineering Exploratory Data Analysis Python DICOM Tensorflow Seaborn Bioinformatics Exploratory Data Analysis Data Modeling REST API Docker Cloud Computing Coaching Collaborative Problem Solving Neural Networks API Development TensorFlow Convolutional Neural Networks Transfer Learning Clustering Biological Network Visualization Network Path Analysis KEGG Cytoscape
Applied Bioinformatics Group, Center for Bioinformatics, Eberhard Karls University Tübingen
6 years 1 month
2010-03 - 2016-03

Development of Gaussian Mixture Modeling Pipeline for Tumor Microenvironment Analysis

Research Fellow, Oncology Analytical Thinking Problem-Solving Interdisciplinary Research ...
Research Fellow, Oncology
Development of Gaussian Mixture Modeling Pipeline for Tumor Microenvironment Analysis
  • Conceived and co-developed a novel Gaussian mixture modeling (GMM) pipeline integrating 18F-FDG PET and diffusion-weighted MRI (DW-MRI) data. 
  • The project aimed to segment the tumor microenvironment into distinct tissue compartments and monitor their evolution over time. 
  • Successfully demonstrated the pipeline's ability to segment tumor tissue accurately and establish a linear correlation between ADC and 18F-FDG values, suggesting its potential for advancing disease outcome assessment into precision medicine.


Multi-parametric MRI Tumor Tissue Segmentation Study

  • This study introduced an unsupervised segmentation method using multi-parametric MRI to quantify diverse tumor tissue types. 
  • The study involved comparing this novel approach with existing segmentation techniques and validating the results against histological samples. 
  • Findings indicated that the new method accurately quantified the fractional populations of necrotic, peri-necrotic, and viable tumor tissues, aligning closely with histological analyses. 
  • The implications of this research may significantly improve cancer treatment planning and improve MRI-guided tumor biopsies


Spatial Characterization of Intratumoural Heterogeneity via PET-MRI and Machine Learning

  • This project unveiled a cutting-edge approach to characterize intratumoural heterogeneity spatially through phenotype-specific, multi-view learning classifiers using dynamic PET and multiparametric MRI data. 
  • The research demonstrated the classifiers' capability to quantify phenotypic changes from targeted therapies in colon cancer models and align with tumour histology in patients with liver metastases from colorectal cancer. 
  • The application of this novel method in both preclinical and clinical settings underscores its significance in enhancing precision oncology.

Analytical Thinking Problem-Solving Interdisciplinary Research Scientific Communication Project Management Data Analysis Gaussian Mixture Modeling PET/MRI Data Integration Precision Medicine Research Image Processing Histopathology Machine Learning MATLAB Positron Emission Tomography (PET) Magnetic Resonance Imaging (MRI) Critical Analysis Innovative Problem Solving Cross-Disciplinary Collaboration Data Interpretation Research Funding Acquisition MRI Image Segmentation Unsupervised Learning Algorithms Histological Data Validation Cancer Treatment Planning Biopsy Procedure Enhancement Histopahtology Magnetic Resonance Imaginge (MRI) Machine Learning Application Interdisciplinary Collaboration Innovative Problem-Solving Scientific Research Communication Multimodal Imaging Analysis Machine Learning Classifier Development Phenotypic Analysis Dynamic PET-MRI Integration Biostatistics
Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen

Aus- und Weiterbildung

Aus- und Weiterbildung

1 year 6 months
2022-01 - 2023-06

1-on-1 Management Coaching

Consulting Impact, Daniel Zacher
Consulting Impact, Daniel Zacher
1 month
2022-06 - 2022-06

Casual Inference Workshop

Harvard Medical School
Harvard Medical School
6 months
2022-01 - 2022-06

Executive Education

Harvard Medical School
Harvard Medical School
1 month
2019-11 - 2019-11

Leading International Teams Successfully

Haufe Akademie
Haufe Akademie
1 month
2019-11 - 2019-11

Plotly Dashboard Workshop

Plotly
Plotly
6 years 1 month
2010-03 - 2016-03

Doctorate in Molecular Imaging

Dr. sc. hum., Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen
Dr. sc. hum.
Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen
3 months
2015-10 - 2015-12

Machine Learning

Coursera online course, Stanford University
Coursera online course, Stanford University
2 years 5 months
2007-10 - 2010-02

Masters in Biomedical Engineering

M.Sc., Rheinisch-Westfälische Technische Hochschule (RWTH), Aachen
M.Sc.
Rheinisch-Westfälische Technische Hochschule (RWTH), Aachen
4 years 9 months
2002-09 - 2007-05

Bachelors in Physics and Mathematics

B.Sc., Midwestern State University (MWSU), Texas, USA, Received competitive Scholarship from Midwestern State University
B.Sc.
Midwestern State University (MWSU), Texas, USA, Received competitive Scholarship from Midwestern State University

Kompetenzen

Kompetenzen

Top-Skills

Data Scientist AI Strategy Product Development AI Product Development Python Dashboard Development Advanced Analytics Biomedical Data Science NLP AWS Azure SQL NoSQL Knowledge Graph Computer Vision LLM Prompt Engineering ETL Digital Health Innovation Data Governance RAG Langchain llama index

Produkte / Standards / Erfahrungen / Methoden

Personal Statement

  • "I am an innovator at heart, leading through action and empowering teams with the tools and mindset to harness AI effectively. Leadership for me is built on meaningful collaboration, nurturing a culture of growth and agile innovation. 
  • Whether leading a team or working solo, I am your reliable partner, and will empower your organization to navigate the next wave of digital transformation.?


Technologies

  • Cloud Platforms: Extensive experience with AWS (including EC2, SageMaker, Lambda, S3, ECS,?), Azure Cognitive Services, and Red Hat OpenShift.
  • Data Management: Skilled in SQL and NoSQL technologies with experience in SPARQL
  • Dashboard Technologies: Proficient in Streamlit and Dash Machine Learning and AI: Experienced with Transformer Models in NLP, utilizing LLM technologies from OpenAI, Langchain, and llama index


Professional Development

08/2021 - 12/2023:

Role: Head of Digital Lab

Customer: Boehringer-Ingelheim, CD&O


Tasks:

  • Develop and Implement Digital Innovation Strategy for Clinical Development and Operations (CD&O)
  • Up-skill and coach global, self-organized, and empowered team of internal entrepreneurs
  • Leverage qualitative research methods to understand business needs in a user-centric manner, and proactively scout for potential solutions
  • Product Owner for in-house developed software, enabling teams by example with a technical roadmap, utilizing LLMs to bootstrap advanced search capabilities, Question-Answering and self-service data-visualization utilizing OpenAPI specifications


01/2021 ? 05/2021:

Role: Interim Head of Data Science

Customer: BI X GmbH


Tasks:

  • Responsible for staffing of new initiatives and internal hiring
  • Collaboratively coaching digital Product Owners with BI X leadership team
  • Coordinate strategy with Global Head of Data Science


01/2018 ? 07/2021:

Role: (Senior) Data Scientist

Customer: BI X GmbH


Tasks:

  • Empower product team to take ownership by removing technical and business impediments before they impacted development
  • Implemented data models, search, and ETL pipelines
  • Developed bespoke next-generation sequencing pipeline on AWS for shortand long-read sequencing for benchmarking and drug target discovery
  • Staffing initiatives and mentoring junior members of the product team
  • Product Owner for self-driven concept from ideation to Fast Forward Top 10, resulting in project with internal IT for select business cases


04/2016 ? 12/2017:

Role: Research Scientist, Radiogenomics

Customer: Applied Bioinformatics Group, Center for Bioinformatics, Eberhard Karls University Tübingen


Tasks:

  • Coordinate with BMBF research collaborators to identify and implement best practices for collection, processing, and transfer of sensitive clinical data
  • Implement and validate Auto-Encoder Neural Networks in Tensorflow on CPU cluster for analysis of radiology and multi-omics data
  • Utilize Python for data wrangling and visualization of biomedical imaging and multi-omics data
  • Curation of NoSQL databases and containerization in Docker with REST API as back-end for automated machine learning and clinical reporting pipelines of multi-omics testing in cancer patients
  • Mentoring of Bachelor, Master, and PhD candidates


03/2010 ? 03/2016:

Role: Research Fellow, Oncology

Customer: Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen


Tasks:

  • Coordination of BMBF financed research projects with cooperation partners from academia and industry with the goal of developing a holistic systems model of cancer therapy
  • Planning of experiments and coordination of laboratory staff to stay within confines of budget for collaborative research projects
  • Development and validation of a novel machine learning pipeline to predict tumor growth based on longitudinal PET and MR imaging
  • Integration and analysis of large, multi-dimensional and diversely formatted datasets
  • Mentoring of Bachelor and Master students
  • Organization of workshops and international scientific conferences

Programmiersprachen

Python
Proficient
C++
Proficient
MATLAB
Proficient

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