Senior Algorithm Developer - PlanQK

Quantum Computing & AI Platform Development

Contributed to the PlanQK (Platform and Ecosystem for Quantum-assisted Artificial Intelligence) project, focusing on the intersection of quantum computing and artificial intelligence for practical business applications.

Project Highlights

Algorithm Development & Optimization

• Development in the PlanQK Quantum Computing project ecosystem
• Designed data structures and pipeline for automated shift planning
• Automatic shift planning using genetic algorithms and Quadratic Unconstrained Binary Optimization (QUBO)
• Research and implementation of quantum-enhanced optimization algorithms

Technical Leadership & Development

• Software development in Java and Python
• Served as Scrum Master for data and development teams
• DevOps implementation with AWS (Lambda, S3, Cognito, GitHub Actions)
• Integration of quantum computing concepts with classical optimization techniques

Business Impact

• Created scalable solutions for complex scheduling problems
• Successfully bridged quantum research concepts with practical business applications
• Contributed to Germany’s national quantum computing initiative

This role provided valuable experience working with emerging quantum computing technology while applying my mathematical background to solve real-world optimization challenges in a rapidly evolving field.

Head of IT Management

Leading IT Management at TUM

As Head of IT Management at TUM, I lead strategic IT initiatives across the institution. My role combines technical expertise with organizational leadership.

Key Responsibilities

Team Leadership & Management

• Professional and disciplinary management of 25 IT professionals
• Budgeting, recruiting, and strategic team organization
• Introduction of agile methodologies (Scrum) for data and software projects
• Implementation of OKRs (Objectives and Key Results) for measuring IT initiatives

Strategic Projects & Digital Transformation

• Leadership of the TUM SAP S/4HANA transformation project with approximately 100 participants
• Development of the TUM AI strategy in collaboration with the CIO
• Strategic alignment with focus on digital transformation and data-driven decision making
• Advising the CIO on data infrastructure and technology trends

Technical Infrastructure & Architecture

• Designed and implemented data integration strategies to connect various university systems
• System architecture design and implementation for efficient data processing
• Implementation of cloud services (Docker and Kubernetes on Azure and On-Premise)
• Roadmap creation for IT projects and data infrastructure initiatives

This role demonstrates the integration of deep technical knowledge with effective management in complex university IT operations.

Senior Data Scientist & Full Stack Developer

End-to-End Machine Learning System Development

Led a complex data engineering project, delivering a comprehensive machine learning solution from conception to deployment with strict security and performance requirements.

Technical Achievements

Machine Learning & Data Engineering

• Development of a machine learning solution with complex algorithms and statistical modeling
• Implementation of data analysis, data engineering, and visualization solutions
• Built an end-to-end machine learning system with production-grade architecture
• Set up PostgreSQL database architecture with optimized schema and multiple replicas

Technology Stack & Infrastructure

• Python Ecosystem: scikit-learn, TensorFlow, pandas, polars, and Dash
• AWS Services: Lambda, Athena, EC2, SageMaker, ECS, EKS, ElastiCache
• DevOps: GitHub Actions for CI/CD and test automation
• Database: AWS RDS PostgreSQL with multiple replicas and analytics dashboard
• Monitoring: Comprehensive logging and performance monitoring

Project Management & Delivery

• Taking on project responsibility for complex and sensitive data requirements
• Prioritization of tasks and on-time delivery of data infrastructure
• Implementation of GDPR-compliant data processing workflows
• Close collaboration with stakeholders to ensure business requirements were met

This project demonstrated my ability to architect complete machine learning solutions while maintaining high standards for data security and system reliability of data security and system reliability.

Guest Lecturer for Machine Learning

Academic Teaching & Knowledge Transfer

Developed and delivered a comprehensive machine learning curriculum focused on healthcare applications, transferring industry expertise to students.

Academic Contributions

Curriculum Development

• Teaching data transformation principles and the data value chain
• Fundamentals of machine learning, including Random Forest and Support Vector Machines
• Introduction to Neural Networks and Deep Learning architectures
• Convolutional Neural Networks and Recurrent Neural Networks for image processing and sequence analysis

Advanced Topics & Practical Applications

• Big Data concepts: MapReduce paradigm and Data Warehouse architectures
• Practical applications with visualization and prototyping in Jupyter Notebooks
• Real-world case studies from healthcare data analytics
• Integration of theoretical concepts with practical implementation

Ethics & Professional Standards

• Ethical aspects and data protection in the application of AI in healthcare
• GDPR compliance in data science projects
• Responsible AI development and deployment practices
• Industry best practices for healthcare data handling

Professional Recognition

Academic Opportunity

• Received an offer for Full Professorship (W2) in Data Science in Healthcare
• Opportunity declined to pursue industry leadership roles
• Recognition of expertise in both academic and practical applications

This teaching experience allowed me to formalize my knowledge while contributing to the academic community and preparing students for careers in data science and healthcare technology.

Vice President Engineering

Engineering Leadership in Healthcare Technology

Advanced to VP Engineering to lead the development organization. Successfully managed a 35-person engineering team while driving architectural transformation in healthcare AI.

Leadership & Organizational Impact

Team Leadership at Scale

• Professional and disciplinary management of the Development Department with 35 FTEs
• Budgeting, recruiting, and comprehensive team organization
• Agile transformation of software development processes across multiple teams
• Implementation of career development programs and technical mentorship

Strategic Technical Leadership

• Migration from monolith to microservices architecture (Java / TypeScript)
• Designed data flow and integration strategies for healthcare data sources
• Overall responsibility for development projects and data architecture
• Roadmap creation and OKR definition for product development

Innovation & Technical Excellence

Healthcare AI & Data Systems

• Development of ontology-based medical graph database (TUM Data Innovation Lab collaboration)
• Implementation of cloud services (Docker and Kubernetes on AWS and On-Premise)
• Certified development processes according to ISO 13485 medical device standards
• Advanced data processing pipelines for medical imaging and structured reporting

Industry Partnerships & Compliance

• Technical partner management with Siemens Healthineers and GE Healthcare
• Ensuring GDPR compliance and medical data protection standards
• Leading cross-functional initiatives with regulatory and clinical teams

This role combined significant management responsibility with technical leadership in healthcare technology.

Principal Software Engineer

Healthcare AI Development & Technical Leadership

Progressed through multiple technical roles while leading complex AI projects in healthcare, demonstrating strong technical capabilities and growing leadership responsibilities.

AI & Machine Learning Innovation

Healthcare AI Development

• Development of software for structured reporting in radiology and pathology
• Implementation of AI-optimized data workflows to increase efficiency of medical activities
• Leadership of the KI-Beta project: AI-based analysis of clinical images on prostate datasets
• ImageREPORT: Advanced system for automated analysis of medical images and structured reporting

Research & Development Partnerships

• Responsible for TUM Data Innovation Lab: Cooperation project to build an ontology-based medical graph database
• Collaboration with AWS on automated diagnosis and reporting of Covid-19 patients
• PlanQK project: Platform for quantum computing in artificial intelligence
• Support in technical partner management with Siemens Healthineers and GE Healthcare

Technical Expertise & Implementation

Full-Stack Development & Infrastructure

• Quantum computing, machine learning, data science, and web development
• Programming in TensorFlow, React, TypeScript, JavaScript, WebAssembly, Python
• Advanced data processing with NumPy, SciPy, Pandas, and scikit-learn
• Cloud-native architecture design and implementation

Innovation Impact

• Bridged academic research with practical healthcare applications
• Contributed to medical device software under strict regulatory requirements
• Worked on integrating quantum computing concepts in healthcare AI

This role marked the transition from individual contributor to technical leader, applying deep AI/ML expertise to healthcare challenges.

Senior Software Engineer - Horváth & Partner

Data Analytics & Optimization Solutions

Contributed to the Steering Lab (Data Science Department) at a management consulting firm, developing analytics applications for strategic business optimization.

Technical Development & Innovation

Advanced Analytics Platform

• Development of data analysis application for optimization and visualization
• Application for combinatorial optimization and data visualization
• Data processing pipeline using Flask, pandas, NumPy, and SQL
• Creation of interactive dashboards for complex business metrics

Technology Stack & Architecture

• Backend: Flask framework for robust API development
• Data Processing: pandas, NumPy for high-performance data manipulation
• Database: SQL optimization for large-scale data queries
• Frontend: Angular for responsive user interfaces
• Deployment: Docker containerization for consistent deployment across environments

Knowledge Transfer & Collaboration

Technical Leadership & Mentoring

• Guidance for software developers on advanced data processing techniques
• Knowledge transfer of best practices in data pipeline architecture
• Collaboration with consulting teams to translate business requirements into technical solutions
• Documentation and training materials for internal development teams

Business Impact

• Enabled consultants to process and analyze large datasets more efficiently
• Reduced time-to-insight for client engagements through automated analytics
• Improved data visualization capabilities for client presentations
• Contributed to the firm’s digital transformation initiatives

This engagement involved adapting to new business domains while working in a consulting environment.

Postdoctoral Researcher

Advanced Mathematical Research & Software Development

Continued academic research as a postdoctoral researcher while transitioning expertise toward practical applications in software development and data science.

Research Focus

Discretization in Geometry and Dynamics

• Member of SFB Transregio 109 (Collaborative Research Center)
• Advanced research in computational geometry and dynamic systems
• Development of novel algorithms for geometric discretization problems
• Collaboration with international research teams

Mathematical Innovation

• Continued work on non-standard analysis applications
• Geometric algorithm development and optimization
• Theoretical foundations for computational geometry software
• Publication of research findings in peer-reviewed journals

Transition to Industry Applications

Software Development Leadership

• Continued leadership of CindyJS: Open Source Project for mathematical visualization
• Bridge between academic research and practical software applications
• Development of mathematical software for educational and research purposes
• Mentoring of PhD students and research assistants

Industry Preparation

• Application of mathematical research to real-world problems
• Development of skills in practical software development
• Preparation for transition to industry roles in data science and software engineering

This role represented a crucial transition period, allowing me to complete my academic research while developing the practical skills that would define my subsequent industry career in data science and technology leadership.