Shivani Teli

 Being an optical communication engineer, my research interests mainly involve physical layer designs of optical links for smart IoT applications, characterization of the camera optics, and optical transmitters, ray-tracing models for indoor optical links with Zemax OpticStudio, along with Python-based Gaussian Mixture and FFT models for detecting modulation frequencies. I have pioneered the development of all-optical hybrid solutions using multi-level modulation and software-defined radio.

Matlab: Signal processing toolbox; Neural Network toolbox; data generation formats; modulation scheme designs; image processing techniques (gray-scale image analysis; histogram-based thresholding methods; region-of-interest based data analysis); Simulink models for controlling SDR Pluto boards

Zemax OpticStudio: Ray-tracing model and simulations for indoor OWC scenarios; channel impulse response and path loss estimations

Arduino: LED driving circuits and controllers; pixel-based data mapping

Python: Developed a graphic user interface for data analysis; defined Gaussian Mixture model for SNR analysis; developed data capturing and analysis algorithms

Significant results from my M.Sc. and P.hD. research, focusing on the enhanced functionality of OCC links and hybrid VLC-OCC coverage in indoor OWC-based IoT networks, have been published in top-tier Q1 journals, including IEEE Communications Magazine and IEEE Internet of Things Journal.

I am an optical communications researcher with extensive experience in designing, analyzing, and experimentally validating advanced optical wireless communication systems for IoT and smart sensing applications. I worked as a Postdoctoral Researcher and Supervisor Specialist at the Czech Technical University (CTU), where I led research on hybrid all-optical communication links integrated within digital twin–based IoT frameworks. My work spans physical layer design, SDR-based hybrid modulation schemes, optical camera communications (OCC), and secure steganographic optical links. I have developed complete experimental testbeds, optical simulation models using Zemax OpticStudio, and Python-based signal processing and machine learning frameworks to evaluate channel behavior, interference, and positioning accuracy.

Over the course of my research career, including my Ph.D. and M.Sc. work, I have proposed and demonstrated several novel OCC and visible light communication (VLC) techniques, achieving significant improvements in data rate, link range, robustness, and non-line-of-sight performance. My contributions include multilevel modulation schemes, FFT-based frequency detection methods with near-perfect detection accuracy, NN-assisted motion detection systems, and hybrid optical systems combining high- and low-speed data streams. I have authored over 20 peer-reviewed journal and conference publications with more than 400 citations and have experience mentoring graduate and doctoral students in interdisciplinary optical and wireless communication research.

I hold a Ph.D. in Electrical Engineering and Information Technology from the Czech Technical University (CTU), Prague, where my doctoral research focused on CMOS camera-based optical communication systems for IoT applications. During my Ph.D., I specialized in optical system design, camera characterization, modulation and detection techniques, and experimental evaluation of outdoor and indoor optical links under challenging conditions such as turbulence and fog. This work laid a strong foundation in both theoretical modeling and hands-on system implementation.

Prior to this, I earned a Master of Science in Information and Communication Engineering from Pukyong National University, South Korea. As a graduate researcher, I worked on high-speed optical camera communication systems and neural-network-assisted signal processing, achieving significant performance gains using off-the-shelf camera hardware. My academic training across Europe and Asia has provided me with a strong interdisciplinary perspective, combining optics, wireless communications, signal processing, and machine learning.