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Somayeh Khakpash

Somayeh Khakpash

Visiting Assistant Professor

sok215@lehigh.edu
Lewis Lab 402

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Research Areas

Additional Interests

  • Microlensing
  • Time-domain Astronomy
  • Data Science and Machine Learning Applications in Astrophysics

Research Statement

Khakpash studies microlensing and time-domain astronomy preparing for some of the largest sky surveys in the world. She uses advanced data science to spot and study rare cosmic events hidden in huge amounts of future telescope data.

Microlensing is like nature’s own magnifying glass: when an object — as small as a planet or as massive as a black hole — passes in front of a distant star, its gravity bends and focuses the star’s light. This brightening can reveal planets drifting alone in space or black holes that are otherwise invisible. These discoveries give us clues about how planets form and how matter is distributed in our galaxy.

With upcoming surveys like NASA’s Roman Space Telescope and the Rubin Observatory’s Legacy Survey of Space and Time (LSST) — both set to monitor millions of stars night after night — Khakpash is building automated tools to quickly detect and analyze these transients.

As part of her work, she has developed a deep learning model on the image level for magnification maps of lensed quasars and supernovae, enabling much faster and more efficient analysis of extragalactic microlensing light curves in preparation for the data-rich era of these upcoming surveys.
 

She also studies other cosmic events, such as a specific type of core-collapse supernovae (star explosions), creating data-driven templates that track how their brightness changes over time. These templates help astronomers classify stellar explosions and spot unusual behavior, opening windows into the life and death of stars.



 

Biography

Somayeh Khakpash received her Ph.D. in Physics in 2020 from Lehigh University, under the supervision of Professor Joshua Pepper. Her dissertation was titled, "Fast Methods For Characterizing and Classifying Microlensing Light Curves". She then became a postdoctoral researcher at University of Delaware where she worked on data-driven templates for supernovae. In 2022, she was awarded the LSST-DA Catalyst Fellowship at Rutgers University, a position she held until 2025, when she joined Lehigh University as a Visiting Assistant Professor. 

Selected publications:

1- Khakpash, S., Bianco, F., Vernardos G., Dobler G., Keeton, C., 2025 “Autoencoder Reconstruction of Cosmological Microlensing Magnification Maps”. ApJ 980, p.35.

2- Khakpash, S., Bianco, F., Modjaz, et. al., 2024 “Multi-filter UV to NIR Data-driven Light Curve Templates for Stripped Envelope Supernovae”. ApJS 275(2), p.37.

3- Khakpash, S., Pepper, J., Penny, M., Gaudi, S., and Street, R., 2021 “Classifying High-cadence Microlensing Light Curves I; Defining Features”. The Astronomical Journal, 161(3), p.23.

4- Khakpash, S., Penny, M. and Pepper, J., 2019. “A Fast Approximate Approach to Microlensing Survey Analysis”. The Astronomical Journal, 158(1), p.9.

5- N. Abrams, M. Hundertmark, S. Khakpash, et. al. 2023. “Microlensing Discovery and Characterization Efficiency in the Vera C. Rubin Legacy Survey of Space and Time”. ApJS 276 p.10.

6- R.A. Street, X. Li, S. Khakpash, et. al. 2023. “LSST Survey Strategy in the Galactic Plane and Magellanic Clouds”. ApJS 267 (1), p.15.

7- Sajadian, S., Kalantari, A., Fatheddin, H. and Khakpash, S., 2024. “Simulating Gravitational Microlensing Events by TESS: Predictions on Statistics and Properties”. The Astronomical Journal,169 p.34.