Hello
I’m Ahmed — an AI PhD researcher and academic staff member at the Munich Institute of Robotics and Machine Intelligence, Technical University of Munich. I develop brain-inspired AI systems, with proven experience building AI-driven healthcare solutions. My multidisciplinary background spans Machine Learning, Data Science, Digital Systems, and Neuroengineering. I hold an Elite MSc in Neuroengineering from TUM, where I graduated with honours and was awarded the Research Excellence Certificate by the Elite Network of Bavaria, along with two merit-based scholarships. My passion lies in reverse-engineering the brain to create next-generation intelligent machines, advance neural interface technologies, and restore impaired neural functions. I aim to bridge AI and neuroscience to build intelligent systems that drive biomedical innovation and shape the future of healthcare.
- Artificial Intelligence
- Neurotechnology
- Data Science
Elite MSc in Neuroengineering, 2023
Technical University of Munich, with Honours
BSc in Electrical Engineering, 2017
University of Benghazi, GPA: 3.95 out of 4
My Experience
Munich Institute of Robotics and Machine Intelligence – The AI Mission Institute | Neural Interfacing Group.
- Researching brain-inspired approaches to AI and computing for next-generation intelligent systems
- Designing intelligent algorithms integrating machine learning dynamical systems, controltheory, and data science to model and control brain interfacing systems
Department of Diagnostic and Interventional Neuroradiology.
- Developed large-scale data-driven systems to identify neural biomarkers of brain disorders, analyzing over 200 GB of neuroimaging data and 160+ million brain-signal time series. Advanced AI-driven diagnostic tools and personalized treatment for mental and neurological disorders.
- built an energy landscape model that uncovers the brain representation of metacognition in the prefrontal cortex.
- Identified two subcortical regions that influence the emergence of metacognition ability in the brain using unsupervised machine learning.
- Introduced brain information processing pathway of the subcortical-cortical interaction that gives rise to metacognition using information theory and mediation analysis.
Dynamics of Brain Connectivity Lab | The Neuroimaging Center at the Technische Universität München.
- Built unsupervised machine learning algorithms to extract task-relevant features from over 3 million high-dimensional, temporal whole-brain voxel data points across 25+ subjects.
Oxford Machine Learning Summer School - MLx Health
- Completed 43 hours of intensive training and 12 hands-on workshops covering foundational and medical AI. Collaborated on an interdisciplinary team project to implement advanced deep learning models for healthcare AI applications.
Brain and Memory Lab
- Engineered and deployed a real-time brain interfacing system for detecting and modulating memory-related neural biomarkers, achieving over 97% accuracy with less than 20ms latency.
- Delivered 50+ tutorial sessions in Electromagnetic Theory and Digital Communications, improving comprehension and academic performance for 100+ students. Co-supervised four projects applying advanced Signal Processing and Machine Learning methods.
- Managed Drive-Test processes and post-processing data field analysis for the Nokia H+ project, ensuring optimal network performance and quality of 50+ sites.
- Selected among the top 30 university students nationwide to engage in the prestigious R&D department´s annual internship program.
- Engaged in 70+ hours of RF and wireless engineering workshops, communication networks and research skills, and 150+ hours of practical experience in the network optimisation department.
- Completed a 240+ hour internship focused on RF, microwave, and CDMA components, gaining valuable experience through theoretical concepts and hands-on practice.
Skills
Programming
Languages:
Python (fluent), MATLAB, Julia
ML & Data Science: PyTorch, TensorFlow, Transformers (HuggingFace), Scikit-learn, NumPy,
Pandas, SciPy, torchvision, Matplotlib, Seaborn
Software Engineering: Test-Driven Development (TDD; Google Test), Continuous Integration/Continuous Deployment (CI/CD), Git Version Control, API Integration (FastAPI), CMake,
Linux Environments
Computational
Machine Learning & Deep Learning, Large-scale Modelling and high-dimensional Data Analysis, Multimodal signal processing, Dynamical Systems, Numerical Methods, Probability & Statistics, Information Theory
Neurotechnology
fMRI Analysis (FSL, SPM), EEG/EMG Acquisition & Processing, Embedded Systems (ESP32 Microcontroller), Electronics Simulation (Multisim), Hardware Measurement Tools (Open Ephys, Oscilloscope)
Distinction
Elite Network of Bavaria
Research Excellence Certificate
Awarded by the Bavarian State Ministry of Science and the Arts for outstanding research contributions.
Rheinstahl Stipendium
Scholarship Holder
Selected among Germany’s top 50 students nationwide, recognizing academic excellence and exceptional research potential.
Scholarship Holder
Granted for outstanding academic achievements and for advancing research in science and technology.Contact Me
- ahmed.almijbari@tum.de
- +49 163 1952422
- Bahnhofstraße 37, Garmisch-Partenkirchen, Bavaria 82467
- Book an appointment
- DM Me