Research Associate in Germany

• Developed and implemented AI-based perception and multimodal systems for real-world environments
• Built, trained, and evaluated Machine Learning and Deep Learning models using Python, PyTorch, TensorFlow, and OpenCV
• Worked with Vision-Language Models (VLMs), Large Language Models (LLMs), transformer-based architectures, and multimodal AI systems
• Applied LoRA-based fine-tuning techniques and experimented with diffusion models for generative and multimodal AI applications
• Developed multimodal perception pipelines using camera, LiDAR, and sensor data
• Designed end-to-end workflows for data processing, model training, evaluation, benchmarking, and robustness analysis
• Utilized HuggingFace Transformers and modern Deep Learning frameworks for AI experimentation and deployment workflows
• Applied GPU-accelerated computing, CUDA-based processing, ONNX, and TensorRT optimization for efficient inference and large-scale model training
• Collaborated with industry partners including Valeo and REHAU on applied AI and intelligent system projects
• Developed scalable AI architectures and prototype software solutions for automation and perception tasks

• Conducted advanced machine learning methods on large-scale inequality datasets for forecasting, clustering and feature importance to assess impacts on growth
• Integrated multi-source inequality datasets into a unified panel; applied reproducible preprocessing pipelines including variable harmonization, outlier treatment, normalization, and multiple-imputation methods
• Published four papers in international peer-reviewed journals

• Developed a React-based research platform with interactive 3D/AR product visualization workflows.
• Implemented interaction tracking and usage analytics to measure user behavior and feature engagement within a research platform.
• Deployed the research platform and integrated a R Shiny analytical dashboard, enabling researchers to interactively explore meta-analysis results within a unified platform.

Part-time position in a federally funded research project

• Implemented data/feature pipelines and automated validation/reporting for multi-million-row insurance datasets.
• Built production-grade image processing to detect fabric defects; delivered maintainable, well-tested Python code and concise reports.

• IT consulting, coaching, and implementation with a focus on AI

• Introduced an integrated approach for structural damage detection across concrete, steel, and glass using advanced technologies such as LiDAR and thermal imaging. Highlighted cross-material interactions to enhance diagnostics and enable predictive maintenance.

• Developed an NLP-based medical note simplifier that transforms complex clinical instructions into plain, child-level English. Applied prompt engineering with Flan-T5 transformer models to extract patient-relevant actions and rephrase them into clear to-do items. Built dual Flask and Tornado backends with a printable web interface.

• Research multimodal AI systems integrating image, text, and structured data.
• Build end-to-end AI pipelines for data processing, model training, and evaluation.
• Develop and test computer vision and image recognition solutions using deep learning.

• Development of NLP and LLM POCs for use in manufacturing companies
• Application of advanced machine learning algorithms to analyze production data and develop customized data pipelines for quality assurance
• Design and management of the IAO foundational seminar on AI in industry, including practical training modules

• Project planning, execution, and management
• Analysis and documentation of technical data
• Conducting and evaluating various quasi-static and dynamic experiments
• Representing the institute at international conferences
• Participation in DFG research projects: Sustainable and Energy-Efficient Aviation (Se2a) – development of an FEM-based simulation framework to analyze the static and dynamic behavior of fiber-reinforced composite materials
• Participation in DFG research projects: Global-local thermomechanical analysis of fracture in polycrystalline silicon shells using a phase-field approach – development of an FEM-based simulation framework for homogenizing damage development in photovoltaic cells
• Successfully completed projects by thoroughly answering the key research questions and achieving the defined project objectives
• Teaching in finite element applications & fiber-reinforced lightweight structures (tutorial sessions and exam preparation)
• Supervision of several student projects and master's theses (development of topics and provision of technical support)

• Implemented stereo camera calibration and applied incremental Structure from Motion (SfM) algorithms to build a detailed 3D model of a forklift for an AR-enabled Smart Forklift project
• Developed OpenCV-based preprocessing that improved data accuracy by 20% and enhanced the analysis of industrial videos

• Developed ASR and TSR-based speech processing pipelines on AWS, enabling efficient feature extraction and scalable deployment for speech and text analytics.
• Built a Multimodal Speech Emotion Recognition system combining NLP and deep learning (audio + text), achieving 98% accuracy and supporting real-time, cloud-based inference.
• Designed and optimized end-to-end model training and evaluation workflows using AWS services (S3, EC2, Lambda) to ensure performance, reliability, and reproducibility.
• Created and deployed interactive, user-friendly dashboards for data visualization and insight generation, supporting research teams and management in data-driven decision-making.

• Performed qualitative and quantitative analysis of extracted findings, categorizing themes, evaluating methodologies, and assessing study quality and reliability.
• Produced research reports and evidence summaries communicating key trends, gaps, and opportunities to academic advisors or cross-functional teams.
• Presented findings through well-structured visualizations, tables, and narrative summaries to support decision-making and guide future research directions.

• Sample preparation according to VDI 3866 and VDI 3492
• Conducting analyses according to VDI 3492
• Quality assurance and compliance with safety standards
• Documentation and report writing