GIEßEN, GERMANY

Daniele De
Gregorio

Systems Engineer | Physicist | Advanced Technology Enthusiast

I am interested in advanced technologies that help improve the future of humanity.

Professional headshot of Daniele De Gregorio, Systems Engineer and Physicist
WHO I AM

A physicist who builds precision systems at the edge of what’s measurable.

I am a Systems Engineer at KLA developing and calibrating complex electron-beam metrology tools that deliver nanometer-scale precision for the world’s most advanced semiconductor processes. My work sits at the intersection of hardware, software, statistical analysis, and fundamental physics.

Before KLA I completed my Master’s in Physics at LMU Munich’s Nano-Institute, where I used machine learning for the inverse design of achromatic metalenses and fabricated chiral metamaterials integrated with perovskite nanocrystals — work that was published in ACS Photonics.

PROFESSIONAL EXPERIENCE

Experience

KLA logo
2022 — PRESENT

Systems Engineer

• KLA • 2022–present
Systems Engineer → Applications Engineer → Systems Engineer

Supported a complex electron-beam metrology tool and worked with the three major semiconductor manufacturers.

Applications Engineer

Turned tool capability into production-ready solutions for customers.

  • Led demos and competitive evaluations that drove purchase decisions
  • Diagnosed fab yield issues and developed recipes and best-known methods
  • Partnered with sales, product, and engineering; trained customer teams on installations
Systems Engineer

Kept the multi-physics e-beam platform stable and production-ready.

  • Built nanometer-scale calibrations and monitoring systems
  • Root-caused drifts across optics, vacuum, detectors, and stage; drove hardware/software fixes
  • Collaborated on upgrades that extended tool life in high-volume manufacturing
ACADEMIC FOUNDATION

Education & Research

M.Sc. Physics — LMU Munich (Nano-Institute)

2018 — 2021
Machine Learning for Inverse Design of Achromatic Metalenses

Designed ultrathin metalenses using machine learning to achieve achromatic performance across broad wavelength ranges. Metalenses leverage semiconductor-derived nanofabrication techniques to replace bulky conventional optics.

Read master thesis (PDF)
Chiral Metamaterials + Perovskite Nanocrystals (Published)

Fabricated chiral silicon nanoantenna arrays using electron-beam lithography, chemical vapor deposition, and plasma etching. Deposited perovskite nanocrystal monolayers and demonstrated strong polarization-dependent two-photon photoluminescence enhancement.

Read ACS Photonics paper (2022)

B.Sc. Physics — LMU Munich

2015 — 2018
Bachelor Thesis: Experimental Particle Physics

“Studies of Interpolation Techniques in the Parameter Space of Signal Models for (BSM/SUSY) Searches” at the LHC. Investigated whether computationally expensive Monte Carlo collision simulations could be replaced by intelligent interpolation between existing signal points — a direct precursor to modern surrogate modeling techniques.

Read bachelor thesis (PDF)
ARTIFACTS & OUTPUT

Selected Work & Publications

M.SC. THESIS

Machine Learning for the Inverse Design of Achromatic Metalenses

LMU Munich • Nano-Institute • 2021
View PDF
PEER-REVIEWED

Strong Polarization Dependent Nonlinear Excitation of a Perovskite Nanocrystal Monolayer on a Chiral Dielectric Nanoantenna Array

ACS Photonics, 9 (11), 3506–3514 • 2022
D. De Gregorio et al.
Read on ACS Photonics
B.SC. THESIS

Studies of Interpolation Techniques in the Parameter Space of Signal Models for (BSM/SUSY) Searches

LMU Munich • Experimental Particle Physics • 2018
View PDF
LET’S CONNECT

Ready to build something extraordinary?

I’m always interested in conversations about advanced metrology, nanophotonics, deep-tech hardware, or opportunities where rigorous physics meets real engineering impact.

Get in touch