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AI-Driven Design and Optimization of Chipless RFID and mmWave Systems

Ein Mann steht lächelnd unter einem großen, grünen Luftschiff, das an der Decke schwebt. Die Umgebung ist hell und freundlich, mit Vorhängen im Hintergrund. Das Bild vermittelt ein Gefühl von Innovation und Freude an der Technik.
Ein schwarzer, ovaler Behälter mit mehreren senkrechten Fächern auf der Oberseite, der auf drei Beinen steht. Der Behälter hat an den Seiten zwei kleine Klappen oder Stützen. Der Hintergrund zeigt einen Holzfußboden.
Das Bild zeigt eine grüne Leiterplatte mit verschiedenen elektronischen Komponenten. Darauf befinden sich ein USB-Anschluss, mehrere Chips und Anschlüsse. Eine rote Platine ist oben angebracht. Der Text auf der Platine weist darauf hin, dass sie zur Evaluierung gedacht ist.
Die Abbildung zeigt eine rote Leiterplatte mit verschiedenen elektronischen Komponenten. Dazu gehören Schaltkreise, Knöpfe und Anschlussbuchsen. Die Platine scheint für Entwicklungen oder Tests in der Elektronik vorgesehen zu sein.

Ongoing Projects:

1. Autonomous Mobility Platform (Modular E-Wheelchair & Blimp System)

Designed and implemented a compact, modular, multi-domain embedded sensor and control platform for both ground (E-Wheelchair) and aerial (Blimp/Zeppelin) autonomous applications, focusing on reliability, lightweight design, and reusability.

  • Platform Development: Engineered a high-fidelity embedded system to process essential kinematic data (orientation, velocity, acceleration) for real-time stabilization and control across both land and air mobility domains.
  • Multi-Modal Localization: Integrated GPS for global positioning and path planning, and utilized a barometric pressure sensor for precise altitude control (aerial) and elevation/gradient estimation (ground).
  • Robust Environment Sensing: Developed a comprehensive, multi-sensor suite for real-time Obstacle Detection & Avoidance, integrating mmWave radar, ultrasonic sensors, and Lidar to achieve high-precision proximity measurements critical for safe navigation.
  • Telemetry & Data Acquisition: Established a low-power, long-range wireless communication link (LoRa) to transmit aggregated, processed sensor data to a remote operator or control unit, ensuring reliable telemetry.

2. AI-Driven Chipless RFID Tag Design and Optimization

Pioneered an innovative, AI-driven workflow to accelerate the design and optimization of Chipless RFID tags by replacing traditional, time-consuming electromagnetic (EM) simulations with highly efficient predictive models.

  • Automation Pipeline: Developed a Python-based automation script to control EM simulation software (e.g., CST Studio Suite), creating an efficient pipeline that rapidly generated a large, high-quality dataset of diverse RFID tag designs and their corresponding spectral responses.
  • AI Emulation Model: Trained Artificial Intelligence (AI) models (e.g., neural networks) using the simulated data to accurately emulate the physical tag's performance and predict its spectral signature/scattering parameters (S-parameters).
  • Value and Impact: Reduced the design iteration time from hours to seconds by leveraging the AI model's predictive capability, allowing for near real-time optimization and significantly accelerating the overall RFID design cycle.

3. AI-Driven Design and Optimization of mmWave Systems

Spearheaded the development and application of AI-driven methodologies for the advanced design and performance optimization of high-frequency millimeter-wave (mmWave) systems, including antenna arrays and reconfigurable structures.

  • Antenna Array Optimization: Developed AI-enhanced design frameworks to significantly improve critical performance metrics—including directivity, gain, and reflection coefficient S11 for complex mmWave antenna arrays.
  • Intelligent Beam Steering: Implemented AI techniques to enable intelligent beam steering and dynamic phase shifting, providing adaptive and high-performance radiation pattern control essential for 5G/6G applications.
  • RIS/IRS Investigation: Conducted focused research on AI-optimized Reconfigurable Intelligent Surface (RIS/IRS) structures to achieve highly dynamic and granular control over the electromagnetic wave propagation environment and radiation patterns.