Shehryar Khan

PROFESSIONAL PROFILE Electrical Engineering undergraduate specializing in Photonic Integrated Circuits(PIC's) and Optical Signal Processing, with hands- on research in PIC design, testing and verification. Experienced in implementing digital signal processing and machine learning techniques to optical domain, in both design and processing stage. Additional experience is in the implementation of Machine Learning Techniques, and Neural Networks for Optical Signal Processing Purposes. Previous Projects include designing, simulating and optimizing thermally tuned Mach-Zehnder modulators, Multi-mode Interferometers, and Waveguide crossings using Lumerical FDTD, Tidy-3D, Matlab, and Python, while layouts were made in Klayout. Additional Experience in Machine Learning includes using Sci-kit Learn and TensorFlow to design and optimize delay lines in Photonic Chips for Optical Signal Processing. Strong interest in low-loss, high-fidelity photonic systems and emerging applications at the intersection of photonics, machine learning, and AI. EDUCATION Bachelor of Engineering School of Electrical Engineering and Computer Science , Islamabad , 3.49/4.00 (2026) INTERNSHIP EXPERIENCE Laboratoire d'analyse et d'architectures des systèmes (LAAS) - Centre national de la recherche scientifique (CNRS) (Remote Position) 26-Aug-2025 - 22-Jan-2026 Design and optimization of Tunable Mach-Zehnder Modulators, Loop Mirrors, and Optical Ring Resonators for Optical Signal Processing Applications in Silicon Nitride Platform. Key tasks include initial modeling and theoretical calculations, design of physical structures such as waveguides, MZI's, and Photonic Circuits, simulation of components in Lumerical FDTD, and generation of physical layout for electron-beam lithography. Post-fabrication tasks include signal analysis, filtering and post-processing of results to extract key performance metrics such as group index, free spectral range, and self-reflection. National University of Sciences and Technology - Electronic System Design Automation Centre (NUST - ESDAC) 12-Jun-2024 - 07-Sep-2024 Simulated and analyzed core photonic circuit components, including multimode interference (MMI) couplers, directional couplers, and grating couplers using MATLAB. Designed and optimized Mach–Zehnder interferometers based on MMI and directional coupler architectures on the SiO₂–Si–air platform. Key tasks include investigatation two-dimensional approximations of three-dimensional waveguide structures to evaluate modeling accuracy, and analysis of the impact of polarization states and wavelength variation on optical signal strength and device performance. FINAL YEAR PROJECT Thermally Tuned Mach-Zehnder Modulator Circuits for Optical Feedback Interferometry Design of Mach-Zehnder Modulator Circuits for Sensing Applications, particularly Optical Feedback Interferometry for displacement sensing. This includes design of individual components for fabrication by electron beam lithography machine, characterization circuits to inspect and verify the fabrication process, and finalized circuit for integration with OFI circuits. Additional aspects include processing of the results, as characterized by Optical Spectrum Analyzer. Overall work included analytical calculations, simulation using Lumerical FDTD, Heat Solver, FDE, and Interconnect, Matlab, and Python, with Layouts made in Klayout, while processing of results was performed using Python and Matlab. Key domains include optical signal processing, photonic integrated circuit design, digital signal processing, and linear systems theory.

Electrical Engineering undergraduate specializing in Photonic Integrated Circuits(PIC's) and Optical Signal Processing, with hands- on research in PIC design, testing and verification. Experienced in implementing digital signal processing and machine learning techniques to optical domain, in both design and processing stage. Additional experience is in the implementation of Machine Learning Techniques, and Neural Networks for Optical Signal Processing Purposes. Previous Projects include designing, simulating and optimizing thermally tuned Mach-Zehnder modulators, Multi-mode Interferometers, and Waveguide crossings using Lumerical FDTD, Tidy-3D, Matlab, and Python, while layouts were made in Klayout. Additional Experience in Machine Learning includes using Sci-kit Learn and TensorFlow to design and optimize delay lines in Photonic Chips for Optical Signal Processing. Strong interest in low-loss, high-fidelity photonic systems and emerging applications at the intersection of photonics, machine learning, and AI.