Hi, I’m Imran Khan
Working at the intersection of optics, imaging systems, and AI-driven analysis.
Applied scientist and engineer with training in physics and optics and industry experience in semiconductor metrology at Intel. My work focuses on imaging system characterization, sensor performance analysis, and Python-based data pipelines for large-scale experimental and manufacturing data. I have experience developing physics-informed algorithms, numerical models, and image-based analytics, with a growing focus on computer vision methods for scientific and industrial imaging. I’m interested in applied research and engineering roles where imaging systems, physical insight, and modern data-driven techniques come together.
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Education

Ph.D., Physics (Optics | Computational Modeling | Nano fabrication)

Aug 2016 to Oct 2021 | University of California, Merced.

M.S., Physics

2016 | Binghamton University (SUNY) , Binghamton, NY.

Experience

Metrological Process Engineer (CD-SEM) at Intel Corporation

Intel Corporation, Hillsboro, USA. | Nov, 2021 - August, 2025

    Worked on imaging system performance and sensor analytics for advanced semiconductor metrology equipment operating in high-volume manufacturing. Focused on improving measurement stability, sensor reliability, and system-level diagnostics through data-driven analysis and cross-functional engineering collaboration.

  • Improved measurement stability across a fleet of high-precision imaging tools by implementing automated calibration and Statistical Process Control (SPC) workflows to reduce drift and long-term variability.
  • Developed Python-based analytics to monitor high-dimensional sensor and system signals, enabling early detection of anomalies and shifting the team from reactive troubleshooting toward proactive performance monitoring.
  • Built automated multivariate analysis pipelines for tool performance comparison and precision evaluation, significantly reducing data processing time while improving consistency and reporting accuracy.
  • Designed image quality assessment workflows using Python and OpenCV to quantify sharpness, contrast, frequency-domain behavior, and texture metrics for imaging system performance validation.
  • Collaborated with hardware, electrical, and software teams to investigate optical and signal integrity issues, contributing to root cause analysis and optimization of imaging system acquisition parameters.

Graduate Research Scholar

University of California, Merced, California. | Aug, 2016 - Oct, 2021

    Computational Modeling & Nano-fabrication of Plasmonic Metastructures:

    During my PhD, I developed physics-based computational models to study light–matter interactions in three-dimensional plasmonic metastructures, combining rigorous electromagnetic theory with scalable numerical implementations. This work focused on understanding how collective scattering, absorption, and disorder in nano-assembled systems can be engineered to control far-field optical response.

    Key contributions included:
  • Developed a hybrid full-wave modeling framework combining the Method of Fundamental Solutions (MFS) and Foldy–Lax multiple-scattering theory to simulate scattering from dielectric cores coated with plasmonic nanoparticle assemblies.
  • Implemented Python and MATLAB solvers to compute far-field angular scattering, extinction and scattering spectra, anisotropy, and albedo across large design parameter spaces.
  • Performed systematic parameter sweeps (particle size, filling fraction, core geometry) to identify regimes of scattering suppression, angular redistribution, and broadband cloaking.
  • Nano-fabricated core–shell plasmonic structures, characterized geometry using SEM, and correlated experimental scattering measurements with simulation predictions.
  • Demonstrated strong agreement between modeled and measured optical response, validating the computational framework and enabling predictive metastructure design.
  • My research works resulted in peer-reviewed publications in JOSA A and Optics Express and laid the foundation for my current interest in surrogate modeling, physics-informed learning, and data-driven approaches for complex imaging and wave-based systems.

    Optical Metrology for Nanoscale Energy Transfer(UC Merced, 2017-2019)

    I conducted optical metrology experiments to probe non-radiative energy transfer in DNA-templated gold nanoclusters (AuNCs) and fluorophores. Using time-resolved photoluminescence (TRPL) and custom-built optical setups, I quantified changes in emission lifetime and intensity to distinguish FRET-like versus NSET-like transfer mechanisms in atomically precise gold nanoclusters.

  • Designing and aligning a high-stability TRPL measurement system optimized for dilute samples and weak emitters
  • Preparing and characterizing DNA-origami scaffolds with nanometer-precise AuNC/fluorophore placement (5–17 nm separation) to test distance-dependence limits of energy transfer models.
  • Measuring and analyzing photoluminescence intensity quenching and lifetime changes to identify whether energy transfer in AuNC systems follows Förster-type (FRET) or nanoparticle-based NSET models
  • Mentoring undergraduate researchers, co-developing experimental protocols, and contributing data to multiple CCBM projects.
  • Collective Motion with Kilobot Swarms (UC Merced, 2016-2017)

    Worked with large-scale Kilobot swarms (~110 units) to study collective motion and active-matter dynamics, integrating simulation models with hardware experiments using IR-based control. Contributed to system revival, firmware debugging, experimental design, and presented results at APS regional and national meetings.

Graduate Research Associate

Universal Instruments Corporation, Conklin, New York. | 2013-2014

  • Characterized thermomechanical properties of lead-tin-silver alloys for high-temperature electronic packaging.
  • Conducted DSC analysis to determine melting point depression and thermodynamic behavior.
  • Performed SEM-based microstructural analysis to link material composition with grain morphology.
  • Measured mechanical integrity using a Dage 4000 Plus bond tester and co-authored an IMAPS industry publication.
  • Co-authored an industry-facing publication for the International Microelectronics Assembly and Packaging Society (IMAPS), presenting findings to aid in the development of new industrial alloys.

Publications(Selected)
Certifications

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