CV.

Georgia Institute of Technology

• Co-advisors: David R. Ballantyne and Tamara Bogdanović (Summer 2026–Present).
• Research focus: Radio emission and detectability of dual active galactic nuclei.

Georgia Institute of Technology

• Completed during doctoral study; M.S. major GPA: 3.80/4.00.

University of Arizona

Georgia Institute of Technology

P. Abdolghader, R. Jafari, A. Das, B. Banerjee, E. P. Duchrist Crews, R. Trebino. Optics, 7(3), 42. doi:10.3390/opt7030042

Graduate Researcher, Center for Relativistic Astrophysics, Georgia Institute of Technology

Co-advisors: David R. Ballantyne (PI) and Tamara Bogdanović (Co-PI) · Funding: NSF AST-2407658, “The Population and Evolution of Dual AGNs at Radio Wavelengths: Predictions for the ngVLA”

• Develop a theoretical and computational framework for predicting radio emission from dual AGNs in post-merger galaxies, with applications to searches for SMBH pairs.
• Connect host-galaxy and SMBH properties from IllustrisTNG with pre-existing orbital-evolution calculations to model the evolving accretion and radio-emission properties of the pair.
• Model accretion from magnetized gas and relativistic jet power, considering the dependence on the black holes’ motion and the surrounding galactic environment.
• Calculate radio synchrotron spectra, including synchrotron self-absorption, to predict the fluxes and spectral properties of the two AGN cores.
• Investigate how radio detectability depends on projected separation, redshift, host-galaxy properties, and observing frequency, toward predictions for next-generation Very Large Array (ngVLA) surveys.

Graduate Researcher, School of Physics, Georgia Institute of Technology

Advisor: Rick Trebino

• Co-wrote the peer-reviewed paper.
• Wrote and implemented the computational code for computing runs in the differences between measured and retrieved FROG traces, used for the statistical characterization of pulse-train instability.
• Worked on the mathematical and analytical proofs in the paper, including Appendix A on the invariance of the weighted runs statistic under time–bandwidth-preserving rescaling.

Undergraduate Researcher, Theoretical Cosmology, University of Arizona

Advisor: Fulvio Melia

• Investigated the use of gamma-ray bursts as standard candles for extending the Hubble diagram beyond the redshift range accessible to conventional distance indicators.
• Incorporated the Platinum and LGRB95 gamma-ray-burst data sets into the analysis.

Undergraduate Researcher, Arizona Cosmology Lab, University of Arizona

Advisor: Tim Eifler

• Investigated intrinsic galaxy alignments using the tidal alignment and tidal torquing (TATT) model in the context of weak gravitational lensing.
• Implemented algorithms to generate synthetic data for predictions of Large Synoptic Survey Telescope (LSST) observations.
• Examined model parameters through statistical analysis and visualization, assessing their effects on cosmic shear and galaxy–galaxy lensing signals.

Summer Researcher, Asteroids Laboratory, University of Arizona

Advisor: Jekan Thanga

• Developed a CubeSat mission concept targeting the atmosphere of Venus, including instrument selection and mission-feasibility assessment.
• Designed a hybrid power-system concept for a proposed scientific base on Deimos, considering energy supply for an extraterrestrial environment.

PHYS 7127: Cosmology & Galaxies, Georgia Institute of Technology

Computational term project · Instructor: John Wise

• Used the Boltzmann solver CAMB with Planck 2018 parameters to compute CMB temperature and linear matter power spectra, located the first acoustic peak (ℓ ≈ 220) and compared its scale with the sound horizon at last scattering, and studied the effects of baryon fraction, curvature, low dark-matter density, early reionization and massive neutrinos.
• Wrote Python code to generate cosmological initial conditions at z = 99 in a (20 comoving Mpc)³, 64³ volume: Gaussian random density fields sampled from the CAMB matter power spectrum with FFTs, and Zel'dovich dark-matter particle displacements and velocities, for Planck 2018 and open (ΩΛ = 0) cosmologies.

ASTR 302, University of Arizona

Collaborators: R. Basant and A. Olson

• Obtained V-band observations with the Kuiper 61-inch telescope and reduced the imaging data using IRAF, including noise and cosmic-ray correction and photometry.
• Constructed light curves, determined the orbital period and primary and secondary eclipse depths, and estimated component radii for the brown dwarf and subdwarf B star.

PHYS 305, University of Arizona

• Applied finite-difference methods and eigenvalue calculations to solve the two-dimensional Schrödinger equation for different potentials.
• Analyzed energy levels and wave functions and visualized the resulting quantum states.

ATMO 436A, University of Arizona

Collaborator: G. Fabian

• Examined the cyclone’s formation, intensity, and contributing meteorological factors, alongside its effects on human life, the environment, and agriculture.
• Project report: doi:10.13140/RG.2.2.32826.98242.

Graduate Teaching Assistant, School of Physics, Georgia Institute of Technology

• Supported laboratory instruction in introductory electricity and magnetism, helping students carry out experiments and connect their observations to physical principles.
• Facilitated collaborative group problem-solving sessions, guiding students through conceptual reasoning, mathematical setup, and quantitative solutions.
• Proctored and graded course examinations.

Graduate Teaching Assistant, School of Physics, Georgia Institute of Technology

Instructor: Colin Parker

• Provided hands-on assistance with experimental setup, optical measurements, and laboratory procedures in geometrical and wave optics.
• Guided students through experiments on reflection and refraction, imaging, polarization, diffraction, and interferometry.
• Graded laboratory reports, evaluating experimental methods, quantitative data analysis, interpretation of results, and scientific communication.

CATS Academics, University of Arizona

• Tutored college algebra, Calculus I and II, and introductory mechanics; monitored student progress and coordinated with academic support staff to address learning needs.

Delta Thermal Inc., Tucson, Arizona

• Developed Python tools to analyze temperatures in MLX90640 thermal-camera images and an algorithm for automated image-translation estimation.
• Analyzed temperature time series from the Asarco Ray site, using AWS for data management and machine-learning methods to investigate temperature trends.

• Evaluated high-school student research projects in a virtual fair using video presentations, project boards, and the provided judging rubric, with attention to scientific methodology and clarity of presentation.

Jeevan Rekha Parishad, Bhubaneswar, India

• Taught students from disadvantaged backgrounds and provided preparation for Indian competitive examinations, including JEE Main and Advanced.
• Developed educational plans to support students’ academic development and participated in the organization’s community initiatives.

University of Arizona

University of Arizona

University of Arizona

University of Arizona

TIMESTEP Summer Tech Internship Symposium, Arizona Space Institute, University of Arizona

Internship symposium

PHYS 7127, Cosmology and Galaxies, Georgia Institute of Technology

Seminal-paper presentation on the work of V. C. Rubin, W. K. Ford, Jr., and N. Thonnard (1980)

ATMO 436A, University of Arizona

Course presentation

ASTR 300B, University of Arizona

Course presentation

ASTR 302 Final Project Presentation, Steward Observatory, University of Arizona

Course presentation

Electromagnetism; Quantum Mechanics I and II; Statistical Mechanics I; Mathematical Methods in Physics I.

Cosmology and Galaxies; Radiative Processes; Optics.

Computational Physics; Differential Equations; Classical Mechanics; Electricity and Magnetism I and II; Stellar Structure and Evolution; Dynamics and Mechanics in Astrophysics.

Python, MATLAB, C++, Java.

Numerical modeling, finite-difference methods, eigenvalue calculations, statistical analysis, time-series analysis, machine learning, photometric data reduction.

High-performance computing, AWS, Git, Jupyter, IRAF, Linux, LaTeX.