MAHER SHEIKHI ABOUMASOUDI
Professional Profile
I currently work with implantable medical devices at the intersection of engineering, clinical practice, product development, and customer needs. With over 10 years of engineering experience across organizations including MED-EL, BMW Group, Arthrex, Fresenius Medical Care, and Charité, I combine technical expertise with hands-on experience in regulated environments such as healthcare and automotive. I am also a published author, having contributed research on an intelligent optimization algorithm for interior lighting design using MATLAB. My focus is on translating emerging technologies — particularly AI and software — into practical, reliable solutions that address real challenges in healthcare and improve patient care.
Work Experience
- Technical point of contact: serve as the link between clinicians and the technical management team, translating clinical requirements into tailored system configurations using proprietary C# software and digital signal processing methods.
- DICOM & imaging: work with DICOM imaging data, performing both automated and manual evaluation of CT scans to support surgical planning and implant fitting.
- LLM tools: apply LLM-supported workflows to streamline clinical inquiry handling, with expert review and validation of every output — direct, hands-on practice in responsible AI adoption.
- System validation: perform real-time functional validation and measurement to confirm system performance before deployment in a zero-margin-for-error setting.
- Feedback to R&D: document clinical findings against safety/quality requirements and channel structured feedback to R&D for product improvement.
- Clinical workshops: deliver technical training and workshops for medical professionals, adapting the same content for surgeons, audiologists, and technical staff.
- Managed system-validation workflows and prepared standards-compliant type-approval test reports to support audit readiness.
- Coordinated validation activities across teams using Scrum and Kanban, aligning work packages with development milestones.
- Programmed and integrated software safety subsystems across vehicle components in a complex systems-engineering environment.
- Developed a Python-based GUI to improve statistical evaluation of surgical-instrument test-bench data.
- Implemented machine-learning approaches for automated error detection, supporting traceability and measurement accuracy.
- Supported early project planning, risk assessment, and documentation-structure development for life-sustaining dialysis devices.
- Facilitated user-story workshops in a Scrum environment, connecting technical development with clinical requirements.
- Set up AI-supported BCI pipelines with Neuropype for real-time processing and validation of neurological datasets (EEG, MEG, EMG).
- Developed Python scripts for biosignal processing and analytical visualization using NumPy, MNE, and scikit-learn.
- Automated specialized metrology testing and visualization platforms with LabVIEW and MATLAB to improve engineering workflows.
Projects & Academic Work
Full-stack medical-imaging web application using the Claude Vision API to analyze brain MRI/CT scans, support tumor classification, and generate structured diagnostic-report drafts.
Modular AI investment-analysis platform combining real-time market data, technical analysis, risk assessment, and explainable reporting.
Analyzed and processed neural recordings in Python to model bio-inspired vision systems and extract visual features.
Built connectome-based whole-brain simulations to study network-wide activity patterns and real-time BCI decoding approaches.
Certificates
- Generative AI for Healthcare, Google Cloud, 03/2026
- Certified Medical Device Consultant (Medizinprodukteberater - §83 MPDG), TÜV, 02/2025
Hobbies
Football, Stand-Up Paddling (SUP), Swimming, Cooking